Heme Oxygenase-1 in the Pathogenesis and Diagnosis of Idiopathic Parkinson Disease

Heme oxygenase-1 in the pathogenesis and diagnosis of idiopathic Parkinson disease

Marisa Cressatti, M.Sc. Integrated Program in Neuroscience McGill University, Montreal

August 2020

A thesis submitted to McGill University in partial fulfillment of the requirements of the degree of Doctor of Philosophy in Neuroscience

©Marisa Cressatti 2020

1 Table of Contents 1. Abstract (English)...... 5 2. Abstract (French)...... 7 3. Acknowledgements...... 9 4. Contributions to Original Knowledge...... 11 5. Contributions of Authors...... 13 6. List of Abbreviations...... 15 7. Introduction...... 18 8. Comprehensive Literature Review...... 20 8.1. Neurodegenerative Disorders...... 20 8.2. Parkinson Disease...... 20 8.2.1. Prevalence...... 20 8.2.2. Risk Factors...... 21 8.2.3. Genetics...... 23 8.2.4. Motor Symptoms...... 24 8.2.5. Non-Motor Symptoms...... 25 8.2.6. Diagnosis...... 26 8.2.7. Other Parkinsonisms and Related Disorders...... 28 8.2.8. Biomarkers...... 28 8.2.9. Treatment...... 31 8.2.10. Brain Pathology and Pathomechanisms...... 34 8.2.10i. Neurodegeneration and Neurotransmitter Systems...... 35 8.2.10ii. Iron Deposition...... 38 8.2.10iii. a-Synuclein and Lewy Pathology...... 40 8.2.10iv. Neuroinflammation...... 44 8.2.10v. Mitochondrial Dysfunction...... 45 8.2.10vi. Autophagy-Lysosome Pathway...... 46 8.2.10vii. Ubiquitin-Proteasome System...... 47 8.2.10viii. Programmed Cell Death...... 48 8.2.11. Animal Models...... 50 8.3. MicroRNAs...... 53 8.3.1. MicroRNAs in Parkinson Disease...... 54 8.4. Extracellular Vesicles...... 55 8.4.1. Extracellular Vesicles in Parkinson Disease...... 57 8.5. Heme Oxygenase-1...... 58 8.5.1. Regulation and Physiology...... 59 8.5.2. Involvement in Neurological Conditions...... 61 8.5.3. Involvement in Parkinson Disease...... 66 9. Specific Aims...... 70 10. Chapter 1: Parkinsonian Features in Aging GFAP.HMOX1 Transgenic Mice Overexpressing Human HO-1 in the Astroglial Compartment...... 71 10.1. Chapter 1 Abstract...... 72 10.2. Chapter 1 Introduction...... 73

2 10.3. Chapter 1 Materials and Methods...... 74 10.4. Chapter 1 Results...... 80 10.5. Chapter 1 Discussion...... 85 10.6. Chapter 1 Reference List...... 91 10.7. Chapter 1 Tables and Figures...... 101 11. Transition 1: Expanding Parkinsonian Behavioural Profiles in GFAP.HMOX18.5-19m Mice...... 117 12. Chapter 2: Strategic Timing of Glial HMOX1 Expression Results in Either Schizophrenia- Like or Parkinsonian Behaviour in Mice...... 118 12.1. Chapter 2 Abstract...... 119 12.2. Chapter 2 Introduction...... 120 12.3. Chapter 2 Materials and Methods...... 123 12.4. Chapter 2 Results...... 129 12.5. Chapter 2 Discussion...... 130 12.6. Chapter 2 Reference List...... 135 12.7. Chapter 2 Figures...... 142 13. Transition 2: Elucidating Altered MicroRNA Profiles in the GFAP.HMOX18.5-19m Mouse Model of Parkinson Disease...... 153 14. Chapter 3: Glial HMOX1 Expression Promotes Central and Peripheral a-Synuclein Dysregulation and Pathogenicity in Parkinsonian Mice...... 154 14.1. Chapter 3 Abstract...... 155 14.2. Chapter 3 Introduction...... 156 14.3. Chapter 3 Materials and Methods...... 157 14.4. Chapter 3 Results...... 163 14.5. Chapter 3 Discussion...... 168 14.6. Chapter 3 Reference List...... 174 14.7. Chapter 3 Tables and Figures...... 182 15. Transition 3: Peripheral MicroRNA Changes from Mice to Humans...... 192 16. Chapter 4: Salivary MicroRNA-153 and MicroRNA-223 Levels as Potential Diagnostic Biomarkers of Idiopathic Parkinson’s Disease...... 193 16.1. Chapter 4 Abstract...... 194 16.2. Chapter 4 Introduction...... 195 16.3. Chapter 4 Materials and Methods...... 197 16.4. Chapter 4 Results...... 200 16.5. Chapter 4 Discussion...... 203 16.6. Chapter 4 Reference List...... 208 16.7. Chapter 4 Tables and Figures...... 214 17. Transition 4: Understanding the Reflection of Central Nervous System Changes in Peripheral Biofluids...... 222 18. Chapter 5: Characterization and Heme Oxygenase-1 Content of Extracellular Vesicles in Human Biofluids...... 223 18.1. Chapter 5 Abstract and Graphical Abstract...... 224 18.2. Chapter 5 Introduction...... 226 18.3. Chapter 5 Materials and Methods...... 228

3 18.4. Chapter 5 Results...... 233 18.5. Chapter 5 Discussion...... 235 18.6. Chapter 5 Reference List...... 243 18.7. Chapter 5 Tables and Figures...... 249 19. Discussion...... 264 19.1. HMOX1 Transducer Model...... 265 19.2. Why Astrocytes?...... 268 19.3. The Dopaminergic System...... 269 19.4. Other Neurotransmitter Systems...... 270 19.5. Iron...... 271 19.6. a-Synuclein...... 272 19.7. MicroRNAs...... 273 19.8. Biomarkers...... 274 19.9. Extracellular Vesicles...... 276 19.10. The Dopamine Paradox...... 279 19.11. Protective Effects of HO-1...... 281 19.12. Contributions to Original Knowledge...... 282 19.13. Limitations of the study...... 284 19.14. Future Directions...... 285 19.15. Overall Impact...... 286 20. Master Reference List...... 288

4 1. Abstract (English) The neurodegenerative movement disorder, Parkinson disease (PD) has emerged as one of the fastest growing neurological conditions in terms of both prevalence and mortality. Sorely lacking are diagnostic and neuroprotective therapeutic tools for the better management of this debilitating condition. The Schipper laboratory has been studying neurodegenerative disorders, like PD, for over two decades, doing so through the lens of a highly inducible stress protein, heme oxygenase-1 (HO-1). HO-1 catalyzes the conversion of heme into biliverdin, carbon monoxide and free ferrous iron in brain and other tissues. Astrocytes from PD basal ganglia show significant elevation of HO-1 protein, and extensive in vitro and in vivo evidence from our laboratory and others has directly implicated HO-1 in PD pathogenesis. Furthermore, dysregulated microRNA (miRNA) is thought to play a major role in neurodegenerative conditions, and altered miRNA profiles have been reported as a result of HMOX1 overexpression, the human gene encoding HO- 1. The objective of the current thesis was to evaluate the diagnostic and therapeutic implications of HO-1 in the context of PD. Chapters 1 and 2 describe the characterization of a novel transgenic GFAP.HMOX1 mouse model in which HMOX1 is overexpressed in astrocytes between 8.5 to 19 months of age, recapitulating key behavioural, pathological and biochemical features of human PD. Chapter 3 shows that similar to the human disorder, altered miRNA profiles are observed in brains of GFAP.HMOX1 mice relative to wild-type (WT) control mice, in particular α-synuclein- targeting miR-153 and miR-223. α-Synuclein is a key protein in PD pathogenesis and a major constituent of hallmark Lewy pathology. Not only are miR-153 and miR-223 downregulated in parkinsonian GFAP.HMOX1 substantia nigra and striatum, but also in the serum of GFAP.HMOX1 mice compared to age-matched WT controls. Peripheral alterations in miR-153 and miR-223 expression levels were additionally observed in the saliva of human PD patients relative to non- neurological (healthy) control subjects, described in Chapter 4. Finally, Chapter 5 bridges lessons learned from Chapters 1 through 4, exploring how central nervous system changes may be reflected in the periphery via extracellular vesicle transport of specific cargo, including HO-1. Disruption of the HO-1-miR-153/miR-223-α-synuclein axis may be an attractive approach towards neuroprotection in PD. Overall, the data presented herein further support astroglial HO-

5 1 as a potent driver of relevant cytopathology in PD and highlight its potential as a novel diagnostic and therapeutic target for the management of this debilitating condition.

6 2. Abstract (French) La maladie de Parkinson (MP) est un trouble du mouvement neurodégénératif. Parmi toutes les conditions neurologiques, la MP est une des affections dont la prévalence et la mortalité augmentent le plus rapidement. Les outils thérapeutiques, diagnostiques et neuroprotecteurs manquent pour une meilleure prise en charge de cette affection débilitante. Le laboratoire Schipper étudie les troubles neurodégénératifs, comme la MP depuis plus de deux décennies, à travers le prisme d'une protéine de stress hautement inductible, l'hème oxygénase-1 (HO-1). HO- 1 catalyse la conversion de l'hème en biliverdine, monoxyde de carbone et fer ferreux libre dans le cerveau et d'autres tissus. Les astrocytes des cerveaux MP montrent une élévation significative de la protéine HO-1, et de nombreuses preuves in vitro et in vivo dans notre laboratoire et d'autres ont directement impliqué HO-1 dans la pathogenèse de la MP. De plus, des microARN (miARN) sont dérégulés dans les conditions neurodégénératives, et suite à la surexpression de HMOX1, le gène humain codant pour HO-1. L'objectif de la thèse en cours était d'évaluer le potentiel diagnostique et thérapeutique de HO-1 dans le contexte de la MP. Les Chapitres 1 et 2 décrivent la caractérisation d'un nouveau modèle de souris transgénique GFAP.HMOX1 dans lequel HMOX1 est surexprimé dans les astrocytes de 8,5 à 19 mois. Ce modèle récapitule les principales caractéristiques comportementales, pathologiques et biochimiques de la MP humaine. Le Chapitre 3 montre que, comme pour le trouble humain, l’expression de certains miARN dans le cerveau des souris GFAP.HMOX1 est modifiée par rapport aux souris témoins de type sauvage. En particulier, ceux qui ciblent une protéine cruciale impliquée dans la neuropathologie de la MP, l’α-synucléine, comme miR-153 et miR-223. Non seulement miR-153 et miR-223 sont diminués dans la substantia nigra et le striatum des souris GFAP.HMOX1, mais aussi dans le sérum. Des altérations périphériques des niveaux d'expression de miR-153 et miR- 223 ont également été observées dans la salive de patients humains atteints de la MP par rapport à des sujets témoins non neurologiques (sains), comme décrit dans le Chapitre 4. Enfin, le Chapitre 5 jette un pont sur les enseignements tirés des Chapitres 1 à 4, explorant comment des changements dans le système nerveux central peuvent se refléter dans la périphérie via le transport vésiculaire extracellulaire de cargaisons spécifiques, y compris HO-1. La perturbation de l'axe HO-1-miR-153 / miR-223-α-synucléine offre une cible thérapeutique potentielle pour la

7 neuroprotection chez les patients souffrant de la MP. Dans l'ensemble, les données présentées ici soutiennent que l’expression de HO-1 dans les astrocytes est un puissant moteur de la cytopathologie de la MP et mettent en évidence le potentiel de cette protéine comme nouvel outil diagnostique et thérapeutique.

8 3. Acknowledgements I greatly (and naively) underestimated how difficult writing this dissertation would be, though in the end, the process was more rewarding than I could have ever imagined. The completion of the current Ph.D. dissertation would not have been possible without the tremendous help of countless individuals. First and foremost, I am eternally grateful to my supervisor, Dr. Hyman Schipper. Throughout the years, Dr. Schipper has offered endless support and new opportunities to grow, guiding me through the ups and downs so commonly encountered in research and academia. His mentorship has been invaluable, and is something I will cherish for years to come. None of this work would have been possible without the help, encouragements and support from members, both past and present, of our Schipper Lab team. Special mention goes to Dr. Wei Song, whose teachings helped shape me as a scientist, never hesitating to answer even the simplest of questions. Additional notable mentions include Adrienne Liberman, Ayda Tavitian, Carmela Galindez and Irene Yacoub, who made the lab fun and have left me with lasting friendships. Throughout my studies, I was fortunate to be able to train and work with some amazing volunteer and Honours project students, especially Joshua Benchaya, Ariana Turk, Eva Nkurunziza and Sara Marier. I am grateful to the support staff at the Lady Davis Institute (LDI), particularly Yvhans Chery, Kathy Forner, Véronique Michaud, Julie Labreche and Goldy Mansourian of the Animal Care Facility, Lilian Canetti of the Research Pathology Unit and Janik Jacmain of the Research Grants Office. Much of this work was done in collaboration with experts in other fields of research, and I am indebted to their assistance and backing, namely Dr. Mervyn Gornitsky, Dr. Ana Velly, Julia Galindez, Lamin Juwara and Dr. Shaun Eintracht. My Advisory Committee members, Dr. Kostas Pantopoulos and Dr. Ted Fon, have been with me throughout my graduate studies. I am thankful for their thoughtful comments, direction and input along the way. Dr. Heidi McBride has acted as a mentor, offering continuous support both inside and outside the lab, and I am appreciative for her teachings. I would also like to thank

9 the Integrated Program in Neuroscience administrative team for their excellent help and encouragement throughout my time at McGill University. I am beholden to the funding agencies that directly supported my project, namely the Fonds de la recherche en santé du Québec, Parkinson Canada and the LDI/TD Bank studentship. Last, but by no means least, I am endlessly grateful for the unwavering support of my friends and family. Dr. Clifford Lingwood, a longtime family friend, generously reviewed large parts of this dissertation, offering thoughtful commentary and edits. Cliff gave me my first exposure to research and academia back in 2011, when I worked as a co-op student in his lab at the Hospital for Sick Children in Toronto. Today, Cliff is always interested to hear about my research, and never fails to point out links between my previous work in his lab (HIV and glycosphingolipids) and my current studies, reminding me that science is always connected. I am also thankful to good friends Thibault Mesplede and Sienna Drake, for assistance with editing and creating figures, respectively. A number of dear friends have helped to keep me afloat throughout this journey, with special mention to members of poss, cocktail club and sandwich club. Finally, my family has always been my biggest and most enthusiastic fans. Honorable mentions include my Auntie Nellie, my siblings, Sarah, Justin, Ryan and Alex, and my niece and nephew, Olivia and Lukas. Olivia, in particular, has kept me humble by asking when I was going to get a “real job” on more than one occasion. My parents, mom and dad, are who I would like to acknowledge the most, for giving me the world to pursue my dreams. The final month of writing this dissertation was done so while reading Tolstoy’s Anna Karenina and amidst a global pandemic. The two are unrelated, yet both are equally unimaginable to have occurred at the same time as having to complete the writing of this thesis, and for that I am grateful.

10 4. Contribution to Original Knowledge The data presented in the current dissertation contributes original knowledge to the field of Parkinson disease (PD) research in the following ways: i. The first major contribution is the characterization of the novel GFAP.HMOX18.5-19m mouse model of PD. This model recapitulates numerous behavioural, neuropathological and biochemical features of the disease (see Chapters 1, 2 and 3), a feat that has proven difficult in many of the existing experimental models of parkinsonism. We recently donated the GFAP.HMOX1 mouse line to the Jackson Laboratory (Bar Harbor, Maine), thereby making it widely available to the neuroscience community at large. The GFAP.HMOX18.5-19m mouse provides new insight into the link between environmental and genetic factors via induction of heme oxygenase-1 (HO-1). The accumulation of exposures to environmental and epigenetic risk factors with advancing age may explain why onset of idiopathic PD occurs later in life. We hypothesize that HO-1 transduces salient exogenous and endogenous stimuli into PD-related cytopathology, and that chronic overexpression of this stress protein culminates in a self-reinforcing loop of neurodegenerative and parkinsonian hallmarks. This hypothesis identifies HO-1 as a potential disease-modifying target in the treatment of PD. ii. Acting downstream of HO-1, microRNA (miR)-153 and miR-223 were identified as negative regulators of a-synuclein (see Chapter 3), a key protein in PD neuropathology. Targeting these miRNAs may help stop or slow a-synuclein aggregation in PD brain, a novel therapeutic strategy with potential disease-modifying and neuroprotective effects. iii. Additionally, salivary miR-153 and miR-223 expression levels were found to be moderately good diagnostic biomarkers of idiopathic PD (see Chapter 4). The presence of these miRNA alterations in saliva is particularly relevant, considering saliva acquisition is a minimally invasive and highly accessible protocol for the elderly PD population. This has important implications for diagnosis of PD, confirmation of which is currently only available on autopsy. Furthermore, these peripheral changes in miR-153 and miR-223 were similarly observed in parkinsonian GFAP.HMOX18.5-19m mice (see Chapter 3) as well as human PD brain. Extracellular vesicles (EVs) may offer a suitable mechanism of action to explain this phenomenon. It is important to note that EV transport is not only relevant to miR-153 and

11 miR-223, but also to other major players involved in PD neuropathology, including a- synuclein, other PD-related proteins and miRNAs, including HO-1. iv. Understanding how peripheral pathologies reflect central nervous system (CNS) afflictions may accelerate our knowledge relating to CNS physiology in health and disease, and this was the focus of study for the final chapter of this dissertation. In this last chapter, we described the novel finding of HO-1 protein being predominantly transported by EVs in various circulating human biofluids (see Chapter 5). This is not only important for the HO-1 research community, but also for the biomarker community at large. Peripheral EVs may offer a unique ‘window’ into various CNS conditions, including PD. Overall, this doctoral dissertation has important implications that underscore HO-1 as a target for the development of diagnostic tools and definitive, disease-modifying approaches to the management of PD and related neurodegenerative disorders.

12 5. Contribution of Authors My contributions (M.C.) and the contributions of co-authors are described below, separated by chapter. i. Chapter 1: M.C. and W.S. contributed equally and co-first-authored this publication in Neurobiology of Aging. H.M.S. and W.S. designed the research; H.M.S. and W.S. generated the GFAP.HMOX1 mouse model; M.C., W.S., H.Z., A.L. and C.G. performed the experiments; M.C., W.S., H.Z. and A.L. analyzed the data; M.C., H.M.S. and W.S. wrote the manuscript; M.C. and H.M.S. managed the submission and editing process. Note that part of this work was included in my M.Sc. Thesis 2016 © (traditional monograph style) under the supervision of H.M.S. at McGill University: specifically, all data pertaining to messenger RNA quantification, Western blots and manganese superoxide dismutase immunofluorescence. Data contributing to the current Ph.D. thesis include Figures 1, 2, 3, 5A, 6E and F, 8, 9H and 11 as well as Table 2. W.S. consented to the inclusion of this co-first-authored publication in this manuscript style dissertation. ii. Chapter 2: M.C. and A.T. contributed equally and co-first-authored this publication in Antioxidant and Redox Signaling. M.C., H.M.S. and A.T. designed the research; M.C., A.T., W.S., A.Z.T. and C.G. performed the experiments; M.C., A.T., A.S. and A.L. analyzed the data; M.C., A.T. and H.M.S. wrote the manuscript; M.C., A.T. and H.M.S. managed the editing process. Data contributing to the current Ph.D. thesis include only Figures 7, 8, 9 and 10 (co- constructed with A.T.). A.T. consented to the inclusion of this co-first-authored publication in this manuscript style dissertation. Note that Figures 1, 2, 3, 4, 5 and 6 present data contributing to A.T.’s Ph.D. thesis (traditional monograph style). iii. Chapter 3: M.C. first-authored this publication in GLIA. M.C., H.M.S. and W.S. designed the research; M.C., W.S., A.Z.T., L.R.G., J.A.B., C.G. and A.L. performed the experiments; M.C. and A.L. analyzed the data; M.C. and H.M.S. wrote the manuscript; M.C. and H.M.S. managed the submission and editing process. Note that part of this work was included in my M.Sc. Thesis 2016 © (traditional monograph style) under the supervision of H.M.S. at McGill University: specifically, all data pertaining to microRNA quantification in vivo (brain only) and in vitro.

13 Data was re-analyzed for presentation in this manuscript (Figure 2), and additional data contributing to the current Ph.D. thesis include Figures 1, 3, 4, 5, 6, 7 and 8. iv. Chapter 4: M.C. first-authored this publication in Movement Disorders. M.C., H.M.S. and M.G. designed the research; O.C. and M.G. managed subject recruitment and sample collection; M.C., J.M.G., E.S.N. and S.M. performed the experiments; M.C., L.J., J.M.G. and A.M.V. analyzed the data; M.C. and H.M.S. wrote the manuscript; M.C. and H.M.S. managed the submission and editing process. Data contributing to the current Ph.D. thesis include all Figures and Tables. v. Chapter 5: M.C. first-authored this manuscript accepted for publication in Journal of Neurochemistry. M.C. and H.M.S. designed the research; M.C., J.M.G., A.M.V., S.E., A.L. and M.G. managed subject recruitment and sample collection; M.C., J.M.G. and N.O. performed the experiments; M.C., J.M.G., L.J., N.O. and A.M.V. analyzed the data; M.C. and H.M.S. wrote the manuscript; M.C. and H.M.S. managed the editing process. Data contributing to the current Ph.D. thesis include all Figures and Tables. In addition to the contributions made towards my Ph.D. thesis, I also contributed to and co- authored several other publications. This includes: i. Schipper H.M., Song W., Tavitian A., Cressatti M. (2019). The sinister face of heme oxygenase- 1 in brain aging and disease. Progress in Neurobiology, 172, 40-70.** ii. Song W., Kothari V., Velly A.M., Cressatti M., Liberman A., Gornitsky M., Schipper H.M. (2018). Evaluation of salivary heme oxygenase-1 as a potential biomarker of early Parkinson’s disease. Movement Disorders, 33, 583-591. iii. Song W., Tavitian A., Cressatti M., Galindez C., Liberman A., Schipper H.M. (2017). Cysteine- rich whey protein isolate (Immunocal®) ameliorates deficits in the GFAP.HMOX1 mouse model of Schizophrenia. Free Radical Biology and Medicine, 110, 162-175. iv. Lin S.H., Song W., Cressatti M., Zukor H., Wang E., Schipper H.M. (2015). Heme oxygenase-1 modulates microRNA expression in cultured astroglia: implications for chronic brain disorders. GLIA, 63(7), 1270-1284. **Note that Section 8.5 contains direct quotations of material from Schipper et al. (Schipper et al. 2019) written by M.C. and H.M.S., with consent from all co-authors.

14 6. List of Abbreviations

β, regression coefficients DGCR8, DiGeorge syndrome chromosomal 5-HIAA, 5-hydroxyindoleacetic acid region 8 5-HT, 5-hydroxytryptamine (serotonin) DJ-1 (PARK7), Daisuke-Junko-1 6-OHDA, 6-hydroxydopamine DMEM, Dulbecco’s Modified Eagle Medium 8-OHdG, 8-hydroxy-2’-deoxyguanosine DNAJC13, DnaJ heat shock protein family AADC, aromatic L-amino acid decarboxylase (Hsp40) member C13 AD, Alzheimer disease DNPH, 2,4-dinitrophenylhydrazine AGO, argonaute DOPAC, 3,4-dihydroxyphenylacetic acid ALG-2, apoptosis linked gene 2 product Drp1, dynamin-related protein 1 Alix, ALG-2-interacting protein X E, epinephrine ALS, amyotrophic lateral sclerosis ECH, enoyl CoA hydratase ANCOVA, analysis of covariance ECL, enhanced chemiluminescence ANOVA, analysis of variance EDTA, ethylenediaminetetraacetic acid Ara-C, β-D-arabinofuranoside EIF4G1, eukaryotic translation initiation ARAC, Alzheimer Risk Assessment Clinic factor 4 gamma 1 ASP, aspartate ELISA, enzyme-linked immunosorbent assay ATP13A2, ATPase cation transporting 13A2 EV, extracellular vesicle AUC, area under the curve EVD, EV-depleted Bach1, BTB and CNC homology 1 Fe-S clusters, iron-sulfur clusters BAK, Bcl-2 homologous antagonist killer FVB, Friend leukemia virus B BAX, Bcl-2-associated X protein GABA, gamma amino butyric acid BBB, blood-brain barrier GAD67, glutamate decarboxylase (GAD) 67 BCA, bicinchoninic acid assay GAPDH, glyceraldehyde 3-phosphate Bcl-2, B-cell lymphoma 2 dehydrogenase BECN1, beclin-1 GBA, β-glucocerebrosidase A BSA, bovine serum albumin GFAP, glial fibrillary acidic protein BTB, bric-a-brac-tramtrack-broad complex GIGYF2, GRB10-interacting GYF protein 2 cDNA, complementary DNA GLAST, glutamate aspartate transporter 1 CHCHD2, coiled-coil-helix-coiled-coil-helix GLU, glutamate domain containing 2 GPe, globus pallidus externus CI, confidence interval GPi, globus pallidus internus CMV, cytomegalovirus (human) GRB10, growth factor receptor bound CNC, cap’n’collar protein 10 CNS, central nervous system GSH, glutathione CO, carbon monoxide H/M ratio, heart-to-mediastinum ratio COMT, catechol-o-methyl transferase H&Y, Hoehn and Yahr CSF, cerebrospinal fluid HC, hippocampus CtsB/D, cathepsin B/D HD, Huntington disease DA, dopamine Hdac6, histone deacetylase 6 DAT, dopamine transporter HIV, human immunodeficiency virus DBS, deep brain stimulation HO-1/2/3, heme oxygenase-1/2/3

15 HPLC-EC, HPLC with electrochemical MLR, multivariable logistic regression detection MnSOD, manganese superoxide dismutase HPLC, high performance liquid MoCA, Montreal Cognitive Assessment chromatography MPP+, 1-methyl-4-phenylpyridinium HRP, horseradish peroxidase MPTP, 1-methyl-4-phenyl-1,2,3,6- Hsp70, heat-shock protein of 70 kDa tetrahydropyridine HTRA2, HtrA serine peptidase 2 MRI, magnetic resonance imaging HVA, homovanillic acid mRNA, messenger RNA I23I-MIBG, I23I-metaiodobenzylguanidine MSA, multiple system atrophy IF, immunofluorescence mTOR, mammalian target of rapamycin IFN-γ, interferon-γ MS, multiple sclerosis IHC, immunohistochemistry MVE, multivesicular endosome IL-1, interleukin-1 NAC, non-β-amyloid component IL-1b, interleukin-1b NE, norepinephrine IL-6, interleukin-6 NF-κB, nuclear factor kappa-light-chain- IRP1/2, iron regulatory protein 1/2 enhanced of activated B cells JGH, Jewish General Hospital Notch1, notch homolog 1 Keap1, Kelch-like enoyl CoA hydratase Nrf2, nuclear factor erythroid 2-related (ECH)-associated protein 1 factor 2 L-dopa, levodopa NTA, nanoparticle tracking analysis L1CAM, L1 cell adhesion molecule protein Nurr1, nuclear receptor related-1 protein Lamp2, lysosome-associated membrane OPA-1, dynamin-like 120 kDa protein protein 2 p62, ubiquitin binding protein p62 LC3B, microtubule-associated protein 1B- PARK2, Parkinson disease gene 2, also light chain 3 known as parkin LCL, lymphoblastoid cell lines PARP, poly-(ADP-ribose) polymerase LEDD, L-dopa equivalent daily dose PD, Parkinson disease LGD, L1CAM/GLAST-depleted PEG, poly-(ethylene glycol) LMX1b, LIM homeobox transcription factor PEST, proline-glutamic acid-serine- 1 beta threonine LRRK2, leucine-rich repeat kinase 2 PET, positron emission tomography MANOVA, multivariate ANOVA PFC, prefrontal cortex MAO-A/B, monoamine oxidase A/B PGC1-a (PPARGC1A), peroxisome MAPT, microtubule-associated protein tau proliferator-activated receptor gamma co- MARE, Maf response elements activator 1-alpha MCI, mild cognitive impairment PINK1 (PARK6), PTEN-induced kinase 1 MDS-UPDRS, MDS-sponsored revision of Pitx3, pituitary homeobox 3 the Unified Parkinson’s Disease Rating Scale PPI, pre-pulse inhibition of the acoustic MDS, Movement Disorder Society startle response MEM, Minimum Essential Medium Eagle pre-miRNA, precursor miRNA Mfn1/2, mitofusion 1/2 pri-miRNA, primary miRNA miRNA, microRNA PTEN, phosphatase and tensin homolog MISEV2018, minimal information for studies PUMA, p53 upregulated modulator of of EVs apoptosis

16 PVDF, polyvinylidene difluoride SNCA, gene encoding for α-synuclein Q1, lower interquartile SOD1, copper-zinc superoxide dismutase Q3, upper interquartile SPECT, single-photon emission computer RAB39B, Ras-related protein Rab-39B tomography RBC, red blood cell STM, striatum RBD, REM sleep behaviour disorder STN, subthalamic nucleus REM, rapid eye movement TCA, trichloroacetic acid RIC3, resistance to inhibitors of TEM, transmission electron microscopy cholinesterase 3 TG, transgenic RIPA, radioimmunoprecipitation assay TGF-b, transforming growth factor-b buffer TH, tyrosine hydroxylase RISC, RNA-induced silencing complex TNF-a, tumor necrosis factor-a RNS, reactive nitrogen species TRE2, tetracycline-response-element 2 ROC, receiver operating characteristic TSG101, tumor susceptibility gene 101 ROS, reactive oxygen species protein RRID, research resource identifier (see tTA, tetracycline activator scicrunch.org) UCH-L1, ubiquitin carboxy-terminal RT-qPCR, reverse transcriptase quantitative hydrolase L1 polymerase chain reaction UPS, ubiquitin-proteasome system S100B, S100 calcium-binding protein B UTR, untranslated region SCZ, schizophrenia VMAT2, vesicular monoamine transporter 2 SEM, standard error of the mean VPS35, vacuolar protein sorting-associated siRNA, small interfering RNA protein 35 Sirt1, NAD-dependent deacetylase sirtuin-1 VTA, ventral tegmental area SN, substantia nigra WT, wild-type SNAP, soluble N-ethylmaleimide sensitive YOP, year of purchase factor attachment protein SNARE, SNAP receptor

17 7. Introduction The neurodegenerative movement disorder, Parkinson disease (PD) has emerged as one of the fastest growing neurological conditions in terms of both prevalence and mortality (Dorsey et al. 2018a, Darweesh et al. 2018). Although symptomatic pharmacotherapy is available, there currently exists no treatment that unequivocally mitigates neuronal attrition and clinical decline in this condition. Cardinal symptoms of PD include bradykinesia, rigidity, rest tremor and postural instability. Non-motor symptoms, such as hyposmia (loss of sense of smell), rapid eye movement (REM) sleep behaviour disorder (RBD), constipation and other autonomic dysfunctions, depression and anxiety, complete the clinical picture. Neuropathological hallmarks of the disease comprise progressive nigrostriatal dopamine depletion, formation of α-synuclein-containing proteinaceous inclusions (Lewy bodies and neurites) and variable changes in other neurotransmitter systems (Kalia and Lang 2015). Sorely lacking are diagnostic and neuroprotective therapeutic tools for the better management of this debilitating condition. The Schipper laboratory has been studying neurodegenerative disorders, like PD, for over two decades, doing so through the lens of a highly inducible stress protein, called heme oxygenase-1 (HO-1) (Schipper et al. 2019). HO-1 catalyzes the conversion of heme into biliverdin, carbon monoxide and free ferrous iron in brain and other tissues. Astrocytes from PD basal ganglia show significant elevation of HO-1 protein (Schipper et al. 1998), and extensive in vitro and in vivo evidence from our laboratory and others has directly implicated HO-1 in PD pathogenesis (Schipper et al. 2019). The objective of the current thesis was to evaluate the diagnostic and therapeutic potential of HO-1 in the context of PD. Chapters 1 and 2 describe the characterization of a novel transgenic GFAP.HMOX18.5-19m mouse model in which the human gene encoding HO-1, HMOX1 is overexpressed in astrocytes between 8.5 to 19 months of age, recapitulating key behavioural, pathological and biochemical features of human PD (Song et al. 2017a, Tavitian et al. 2019). Chapter 3 shows that similar to the human disorder, altered microRNA (miRNA) profiles are observed in brains of GFAP.HMOX18.5-19m mice relative to wild-type (WT) control mice, in particular α-synuclein-targeting miR-153 and miR-223 (Cressatti et al. 2019b). Not only are miR- 153 and miR-223 downregulated in GFAP.HMOX18.5-19m substantia nigra and striatum, but also in

18 the serum of GFAP.HMOX18.5-19m mice compared to age-matched WT controls (Cressatti et al. 2019b). Peripheral alterations in miR-153 and miR-223 expression levels were additionally observed in the saliva of human PD patients relative to non-neurological (healthy) control subjects (Cressatti et al. 2019a), described in Chapter 4. Finally, Chapter 5 bridges lessons learned from Chapters 1 through 4, exploring how central nervous system changes may be reflected in the periphery via extracellular vesicle transport of specific cargo, including HO-1. Disruption of the HO-1-miR-153/miR-223-α-synuclein axis may be an attractive approach towards neuroprotection in PD. Overall, the data presented herein further support astroglial HO- 1 as a potent driver of relevant cytopathology in PD and highlight its potential as a novel diagnostic and therapeutic tool for the management of this disease.

19 8. Comprehensive Literature Review 8.1. Neurodegenerative Disorders Neurodegenerative disorders are among the leading source of disability worldwide (Dorsey et al. 2018a). This includes Alzheimer disease (AD), Parkinson disease (PD), Huntington disease (HD), amyotrophic lateral sclerosis (ALS) and prion disorders. Many neurodegenerative conditions share common cellular and molecular mechanisms, such as increased oxidative stress, mitochondrial damage and misfolded protein aggregation (Jellinger 2010). One of the fastest growing of these disorders, with regard to age-standardized rates of prevalence, disability and deaths, is PD (Dorsey et al. 2018a), making research in this field imperative. Prior to the seminal findings of Jean-Martin Charcot in 1872 (see Section 8.2), the classification system of neurological disease like PD was primitive, and disorders were largely grouped by primary symptoms, for instance tremor or weakness (Goetz 2011). The PD field of research has significantly advanced since then. 8.2. Parkinson Disease 2017 marked the 200-year anniversary since James Parkinson’s landmark publication on what he then called “the shaking palsy” (Parkinson 1817). In 1817, Parkinson described this neurological syndrome as “Involuntary tremulous motion, with lessened muscular power, in parts not in action and even when supported; with a propensity to bend the trunk forward, and to pass from a walking to a running pace: the senses and intellects being uninjured” (Parkinson 1817). Though symptoms of parkinsonism can be found in earlier descriptions, some as far back as ancient Chinese sources (‘Nei-Jing’, 500 BC) and traditional Indian texts (‘Indian Ayurveda’, 5000 BC) (Manyam 1990, Zhang et al. 2006), it was not until 1872 that Jean-Martin Charcot coined the term “Parkinson disease” (Charcot and Bourneville 1872). For most of history, PD was considered a rare disorder. During the period of Parkinson and Charcot, 22 people of 15 million in England and Wales died of the condition annually (Dorsey et al. 2018b). This is clearly not nearly the case today. 8.2.1. Prevalence Between 1990 and 2015, the number of individuals living with PD worldwide increased 118% to 6.2 million (Dorsey et al. 2018a). The burden of PD appears to be shifting in response to changes

20 in aging and industrialization (Dorsey et al. 2018b). Global life expectancy, independent of PD, has risen by six years in the past two decades owing to advances in modern medicine (Dorsey et al. 2018b). Declining tobacco smoking rates may also lead to a higher incidence in PD, considering lower PD risk among smokers (see Section. 8.2.2). Finally, the bi-products of growing industrialization, including specific pesticides, solvents and heavy metals, which have been linked to PD and may also be contributing to its rise (Dorsey et al. 2018b). The combination of an increasingly older population, improved longevity, decreasing smoking rates and environmental factors may explain projections that posit a burden of PD exceeding 17 million globally by 2040 (Dorsey et al. 2018a, Rossi et al. 2018, Wanneveich et al. 2018). PD appears more prevalent in Europe, North America and South America (Kalia and Lang 2015). In Canada, the number of individuals living with PD is expected to more than double by 2050 (Bach et al. 2011). The current mean survival as measured by the years from baseline (PD diagnosis) to death ranges on average from 6.5 to 11.6 years (Backstrom et al. 2018). Taken together, this highlights the growing importance of novel neuroprotective therapeutics for people living with PD, which will also lessen the burden of care on caregivers and easing the strain on our healthcare system. 8.2.2. Risk Factors Though previously considered caused purely by environmental factors, PD is more likely the result of a complicated interplay of environmental and genetic factors (Kalia and Lang 2015). i. Environmental Risk Factors: Aging is the greatest risk factor for PD (Hindle 2010, Kalia and Lang 2015). This is alarming, considering that by 2036, the Canadian population aged 65 years or over is expected to increase 2.6 times to reach 3.3 million, and increase 3.9 times to be more than 5.1 million by 2061 (Statistics Canada, 2010). Sex is another important risk factor for PD, with a male-to-female ratio of approximately 3:2 (de Lau and Breteler 2006). Other positively- associated environmental risk factors of the disease (in decreasing order of association) include pesticide exposure, prior head injury, rural living, β-blocker usage, agricultural occupation and well-water drinking (Kalia and Lang 2015). With respect to pesticides and PD, this relationship appears strongest for exposure to herbicides and insecticides, particularly with prolonged durations of exposure (Brown et al. 2006). Paraquat, maneb and rotenone pesticides have been

21 heavily implicated in PD (Kamel 2013, Pezzoli and Cereda 2013), and chronic administration of these toxins in rodents has led to the development of animal models of the human disorder (see Section 8.2.11). Negatively-associated environmental risk factors of the disease, on the other hand, (in decreasing order of association) include tobacco smoking, coffee drinking, vigorous exercise, non-steroidal anti-inflammatory drug use, calcium channel blocker usage and alcohol consumption (Kalia and Lang 2015). Considering the gastrointestinal involvement of PD, it has been speculated that the association between smoking, coffee and PD risk could be mediated by gut microbiota (Scheperjans et al. 2015). Adding to the complexity of environmental factors implicated in PD pathogenesis is the broad spectrum of day-to-day human exposure, ranging from microbes and viruses to climate, lifestyle, socioeconomic conditions and host-environment interactions (Chen and Ritz 2018). The fact that idiopathic PD takes decades to develop and involves an extended prodromal (pre-motor) phase (see Section 8.2.6) suggests causative environmental exposures that initiate PD pathology begin decades before disease diagnosis (Chen and Ritz 2018). ii. Genetic Risk Factors: A family history of PD or tremor is associated with 2-5% increased risk of the idiopathic disease, suggesting a contribution of genetics, together with environmental factors, to PD (Kalia and Lang 2015, Maiti et al. 2017). Many epigenetic modifications, sparked by environmental triggers (nutritional, chemical or physical) or inherited, have been linked to PD (Kalia and Lang 2015, Surguchov et al. 2017). The study of monogenic forms of PD has led to the most convincing evidence regarding genetic risk factors. The gene that encodes α-synuclein, SNCA, was the first gene linked to PD (Polymeropoulos et al. 1997). The most common causes of dominantly and recessively inherited PD are mutations in leucine-rich repeat kinase 2 (LRRK2) and parkin (Parkinson disease gene 2 [PARK2]), respectively (Corti et al. 2011). The greatest genetic risk factor for developing PD is caused by heterozygous mutations in GBA, which encodes the lysosomal enzyme deficient in Gaucher disease, called β-glucocerebrosidase A (Kalia and Lang 2015, Sidransky and Lopez 2012). Many studies suggest that 5-10% of PD patients carry a GBA mutation in at least one allele, and it has been reported that the penetrance and lifetime risk of developing PD for GBA mutation carriers varies in an age-dependent manner from 20% at 70 years to 30% at 80 years (Anheim et al. 2012, Billingsley et al. 2018). This also highlights the

22 importance of the lysosomal pathway in the pathogenesis of PD (see Section 8.2.10vi) (Sidransky and Lopez 2012). Furthermore, the rise of genome-wide association studies in the past decade has led to the identification of numerous single-nucleotide polymorphisms significantly associated with increased disease risk, including GBA, LRRK2 and SNCA, among many others (Nalls et al. 2014). It has been widely demonstrated that common variability within these loci confer risk and predisposes to genetically complex PD (Billingsley et al. 2018). 8.2.3. Genetics Less than 10% of PD cases have a strict familial etiology, with the majority of cases being idiopathic (Thomas and Beal 2007). The past 20 years have been marked by important discoveries in the genetics of PD. Several genes have been proposed to mediate autosomal dominant forms of PD. The first gene identified was SNCA (Polymeropoulos et al. 1997), and extensive evidence shows deleterious point mutations in and multiplications of the SNCA gene cause a severe early- onset form of PD with an autosomal dominant pattern of inheritance (Billingsley et al. 2018). Genetic variants in LRRK2 (also known as PARK8) account for the majority of all known heritable PD, also being autosomal dominant in nature (Billingsley et al. 2018). Notably, the frequency of this variant varies depending on ethnic background, with highest frequencies among North African Arab Berbers and Ashkenazi Jewish populations (Healy et al. 2008, Lesage et al. 2006). Other autosomal dominant genes identified include vacuolar protein sorting-associated protein 35 (VPS35), eukaryotic translation initiation factor 4 gamma 1 (EIF4G1), DnaJ heat shock protein family (Hsp40) member C13 (DNAJC13) and coiled-coil-helix-coiled-coil-helix domain containing 2 (CHCHD2) (Kalia and Lang 2015). Many of these genes play a role in synaptic vesicle release and neurotransmission, endosome trafficking, autophagy, protein synthesis and mitochondrial function (Kalia and Lang 2015). Unlike autosomal dominant PD, which tends to have an age of onset similar to the idiopathic form (age greater than 55 years), recessively inherited parkinsonism is more frequently associated with early onset (age less than 40 years) (Kalia and Lang 2015). PARK2, phosphatase and tensin homolog (PTEN)-induced kinase 1 (PINK1 or PARK6), Daisuke-Junko-1 (DJ-1 or PARK7) and ATPase cation transporting 13A2 (ATP13A2) were identified as mediating autosomal recessive forms of PD, resulting from either homozygous or compound heterozygous mutations in these genes. Parkin and PINK1 work in concert to dispose of damaged

23 mitochondria during mitophagy, while DJ-1 seems to protect mitochondria from oxidative stress (Kalia and Lang 2015). ATP13A2, on the other hand, encodes a type P5B ATPase that localizes to the endosomal and lysosomal compartments (Park et al. 2018). Though genetic forms of PD are rare, research in this field has led to major advances in the understanding of the pathophysiology of idiopathic PD. In addition to overlap in pathology and molecular mechanisms, symptomatic profiles and treatment strategies of genetic and idiopathic forms of PD are similar. 8.2.4. Motor Symptoms Cardinal motor symptoms of PD include bradykinesia, muscular rigidity and rest tremor (Kalia and Lang 2015), though these motor features are highly heterogeneous (Postuma et al. 2015). Bradykinesia is defined as slowness of movement and, as movements are continued, a decrease in amplitude and speed or progressive hesitations and halts are observed (Postuma et al. 2015). Finger tapping, hand movements, pronation/supination movements, toe tapping and foot tapping can be used to evaluate bradykinesia (Goetz et al. 2008, Postuma et al. 2015). Limb bradykinesia must be noted to establish a diagnosis of PD, though bradykinesia can also occur in voice, face and axial/gait domains. Rigidity is defined as slow passive movement of major joints with the patient in a relaxed position and the examiner manipulating the limbs and neck (Goetz et al. 2008, Postuma et al. 2015). This symptom also involves velocity-independent resistance (lead-pipe resistance) to passive movement, not solely reflecting failure to relax (Goetz et al. 2008, Postuma et al. 2015). The ‘cogwheel’ phenomenon, the combination of rigidity and tremor resulting in a jerky movement, is often present, though isolated cogwheeling without lead-pipe rigidity does not fulfil minimum requirements for rigidity (Postuma et al. 2015). A 4- to 6-Hz tremor in the fully resting limb defines rest tremor, which is suppressed during movement initiation (Postuma et al. 2015). Note that kinetic and postural tremors alone do not qualify as parkinsonism criteria (Berg et al. 2015, Postuma et al. 2015). Postural instability and shuffling gait are also prominent features of parkinsonism, though often appear during late-stage PD (Postuma et al. 2015). The presence of postural and gait abnormalities early in disease suggest an alternative diagnosis, such as multiple system atrophy (MSA) or progressive supranuclear palsy (Kollensperger et al. 2008).

24 Empirical clinical observations suggest two major subtypes: tremor-dominant PD and non-tremor-dominant PD. Tremor-dominant PD, relatively absent of other motor symptoms, is often associated with a slower rate of progression and less functional disability than non-tremor- dominant PD. The latter includes phenotypes described as akinetic-rigid syndrome and postural instability gait disorder (Kalia and Lang 2015). 8.2.5. Non-Motor Symptoms A broad array of non-motor symptoms, often appearing decades before motor manifestations and PD diagnosis, complete the clinical picture of PD. Non-motor symptoms include sleep dysfunction (sleep-maintenance insomnia, excessive daytime somnolence or symptoms of rapid eye movement (REM) sleep behaviour disorder (RBD)), autonomic dysregulation (constipation, daytime urinary urgency, erectile dysfunction or symptomatic orthostatic hypotension), olfactory deficits (hyposmia or anosmia), psychiatric disturbances (depression, anxiety, apathy or hallucinations), pain or cognitive impairment (Berg et al. 2015, Kalia and Lang 2015, Postuma et al. 2015). Many of these symptoms are commonly associated with reduced quality of life (Duncan et al. 2014, Martinez-Martin et al. 2011). Furthermore, prodromal PD (see Section 8.2.6) involves non-motor features before the onset of classical motor symptoms in PD. This premotor phase is classically characterized by impaired olfaction, constipation, depression or RBD (Kalia and Lang 2015). Hyposmia has been proposed as a major preclinical marker of PD (Ansari and Johnson 1975, Doty et al. 1992, Ponsen et al. 2004), and eventually affects up to 90% of patients (Chaudhuri et al. 2006). The risk of developing PD after a mean interval of 10 years from initial reports of constipation is increased roughly 3-fold relative to persons with normal bowel function (Abbott et al. 2001). Not only can symptoms of depression precede development of PD, depression is also associated with future development of cognitive impairment or dementia in PD (Chaudhuri et al. 2006, Marinus et al. 2018). Further, RBD heralds the onset of motor symptoms in up to 40% of patients (Olson et al. 2000, Schenck et al. 1996). Because the pathogenic process that causes PD is likely already underway during this prodromal period, disease-modifying therapy, once available, could be administered during this phase to prevent or delay the progression of the disease. This underlines the necessity for accurate and early diagnosis of PD.

25 8.2.6. Diagnosis The gold standard for diagnosing PD has been the presence of dopaminergic neuron degeneration in the substantia nigra pars compacta and Lewy pathology at post-mortem pathological examination (Kalia and Lang 2015). The UK Parkinson’s Disease Society Brain Bank and the Movement Disorder Society (MDS) PD criteria are used clinically to make a diagnosis of PD (Gibb and Lees 1988, Postuma et al. 2015). This involves satisfaction of the following three tenets: 1) Diagnosis of a parkinsonian syndrome based on the presence of cardinal motor features, namely bradykinesia plus one or more of muscular rigidity, rest tremor (4-6 Hz) or postural instability (typically later stages in PD and not caused by primary visual, vestibular, cerebellar or proprioceptive dysfunction). 2) There should be no red flags that suggest an alternate cause of parkinsonism, including: (i) history of repeated strokes with stepwise progression of parkinsonian features; (ii) history of repeated head injury; (iii) history of definite encephalitis; (iv) neuroleptic (dopamine receptor blocker or dopamine-depleting agent) treatment at onset of symptoms (drug-induced parkinsonism); (v) 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP) exposure (see Section 8.2.11); (vi) minimal or no response to large doses of levodopa (L-dopa; if malabsorption excluded); (vii) sustained remission; (viii) strictly unilateral features after three years; (ix) early severe autonomic failure in the first five years of disease (orthostatic hypotension, severe urinary incontinence or urinary retention); (x) early severe dementia with disturbances of memory, language and praxis; (xi) Babinski sign (extensor plantar reflex); (xii) cerebellar abnormalities (cerebellar gait, limb ataxia or oculomotor signs); (xiii) presence of a cerebral tumor or communicating hydrocephalus on computerized tomography scan or magnetic resonance imaging (MRI); or (xiv) parkinsonian features restricted to the lower limbs. 3) At least three of the following features are required for a positive diagnosis of PD, specifically unilateral onset, rest tremor present, progressive disorder, persistent asymmetry affecting the side of onset most, excellent response (70-100%) to L-dopa, severe L- dopa-induced chorea, L-dopa response for five years or more and clinical course of ten years or more (Gibb and Lees 1988, Postuma et al. 2015). PD diagnosis is frequently accompanied by a score reflecting severity of symptoms. The most commonly used scales for PD progression are the MDS-sponsored revision of the Unified

26 Parkinson’s Disease Rating Scale (MDS-UPDRS) or the Hoehn and Yahr (H&Y) Staging Scale (Goetz et al. 2004, Goetz et al. 2008). Since its development in 1980s, the UPDRS has become the most widely used clinical rating scale for PD (Goetz et al. 2008). The full MDS-UPDRS rates 65 items, including questions/evaluations anchored with either 5 responses that are linked to commonly accepted clinical terms (0 = normal; 1 = slight; 2 = mild; 3 = moderate; 4 = severe) or yes/no responses (Goetz et al. 2008). The MDS-UPDRS takes into account non-motor aspects of experiences of daily living (Part I), motor aspects of experiences of daily living (Part II), motor examination (Part III) and motor complications (Part IV). This extensive and rigorous rating scale is widely used in clinical research studies, though its application is time-consuming and laborious. In contrast, the H&Y staging scale was originally designed as a simple five-point scale (1-5), though the test was eventually revised to include some 0.5 increments (Goetz et al. 2004). The modified H&Y scale is based on the fact that the severity of overall parkinsonian dysfunction relates to bilateral motor involvement and compromised balance and gait (Goetz et al. 2004). Therefore, increasing parkinsonian motor impairment can be charted as follows, 1.0: unilateral involvement only; 1.5: unilateral and axial involvement; 2.0: bilateral involvement without impairment of balance; 2.5: mild bilateral disease with recovery on pull test; 3.0: mild to moderate bilateral disease, some postural instability and physically independent; 4.0: severe disability, though still able to walk or stand unassisted; and 5.0: wheelchair bound or bedridden unless aided. Though limitations and ambiguities exist, the H&Y scale offers simple staging assessment and scores have been shown to correlate with standard PD rating scales like UPDRS (Martinez-Martin et al. 1994). While accuracy of PD diagnosis has been estimated at 80% (Rizzo et al. 2016), early-stage PD (H&Y stage 1) is particularly prone to misdiagnosis, with studies reporting as low as 26% and 53% accuracy in patients with less than three and five years disease duration, respectively (Adler et al. 2014). PD symptomology often overlaps with other neurodegenerative diseases and parkinsonisms, such as progressive supranuclear palsy, MSA and corticobasal degeneration (see Section 8.2.7), further complicating accurate diagnosis. This is particularly important considering misdiagnosis can lead to implementation of incorrect treatment regimens and worsening symptoms (Adler et al. 2014). PD involves a prolonged latency period (10-20 years), and 70-80%

27 dopamine is lost before PD signs and symptoms manifest (Schapira 1999). The stage wherein early signs or symptoms of PD neurodegeneration are present, but classical clinical diagnosis based on fully evolved motor parkinsonism is not yet possible, is referred to as prodromal PD (Berg et al. 2015). An MDS task force recently proposed that early PD should be divided into three stages: preclinical PD (neurodegenerative processes have commenced, but there are no evident signs or symptoms); prodromal PD (signs and symptoms are present, but are yet insufficient to define disease); and clinical PD (diagnosis of PD based on presence of classical motor signs) (Berg et al. 2015). Biomarker research that differentiates PD from other parkinsonisms is particularly relevant during this prodromal stage for accurate and early diagnosis. 8.2.7. Other Parkinsonisms and Related Disorders PD is among numerous disorders also classified under neurodegenerative disease, other forms of parkinsonism and synucleinopathies. Other neurodegenerative disorders were already discussed in Section 8.1. Among the class of parkinsonisms are included progressive supranuclear palsy, corticobasal degeneration, essential tremor, functional or psychogenic movement disorder, dystonic tremor, drug-induced parkinsonism, vascular parkinsonism, normal pressure hydrocephalus and L-dopa-responsive dystonia. Unlike PD, these other forms of parkinsonism lack presynaptic dopaminergic terminal deficiency (Kalia and Lang 2015). Synucleinopathies (involving accumulation and aggregation of pathogenic α-synuclein) include MSA, dementia with Lewy bodies, RBD and other rare disorders such as various neuroaxonal dystrophies. The overlap in signs, symptoms and pathological processes between PD and other neurodegenerative, parkinsonian and synucleinopathic disorders highlights the importance of using neurological controls in PD biomarker research. 8.2.8. Biomarkers A biomarker is defined as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological response to a therapeutic intervention” (Biomarkers Definitions Working Group 2001). Sensitivity (the proportion of true positives correctly identified by the marker among people with disease) and specificity (the proportion of true negatives correctly identified by the marker among people without disease) are key performance measures of a diagnostic test (Altman and Bland 1994).

28 Further, receiver operating characteristic (ROC) curves allow analysis of biomarker performance/accuracy by calculating area under the curve (AUC) and likelihood ratios (Deeks and Altman 2004, Pletcher and Pignone 2011). In the case of PD, a diagnostic biomarker has the potential to confirm a pre-mortem diagnosis. Three broad categories of biomarkers exist for PD, namely genetic markers, imaging markers and biochemical markers. i. Genetic Markers: Characterization of monogenic forms of PD has allowed identification of genes and gene products critical for determining the underlying cause(s) of PD pathology (Miller and O'Callaghan 2015, Xie et al. 2019). Autosomal dominant genes associated with PD include SNCA, LRRK2, VPS35, EIF4G1, PARK3, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), growth factor receptor bound protein 10 (GRB10)-interacting GYF protein 2 (GIGYF2), HtrA (meaning “high temperature requirement”) serine peptidase 2 (HTRA2), DNAJC13, resistance to inhibitors of cholinesterase 3 (RIC3) and CHCHD2. Autosomal recessive genes associated with PD include PARK2, PINK1, DJ-1 (PARK7) and ATP13A2. Other genes found to be associated with PD include GBA, Ras-related protein Rab-39B (RAB39B), PARK12 and PARK16. ii. Imaging Markers: Distinct abnormalities in brain function and structure have been noted in PD. Single-photon emission computer tomography (SPECT) and positron emission tomography (PET) scans can detect loss of dopaminergic and other neurons using radiotracers and computer techniques to generate 3D images. Dopamine transporter (DAT)-SPECT imaging can monitor degeneration of presynaptic terminals in dopaminergic neurons using DAT gamma- emitting ligands (I23I-iometopane, I23I-ioflupane, I23I-altropane) (Emamzadeh and Surguchov 2018). SPECT can also be used to monitor dopamine D2 receptors (using I23I-iodobenzamide, I23I- epidepride) as well as the number of vesicular acetylcholine transporters (using I23I- iodobenzovesamicol) (Emamzadeh and Surguchov 2018). Relating to the latter, dopaminergic neuron death and reduced dopamine levels in PD are associated with increased acetylcholine (Niethammer et al. 2012). PET scan radiotracers can be used to detect the presence of presynaptic DAT in dopaminergic neurons of striatum and substantia nigra (using 18F and/or 11C radiolabeled dopamine analogs), vesicular monoamine transporter 2 (VMAT2) loss (with 18F or 11C radiolabeled dihydrotetrabenazine) or reduction in acetylcholinesterase activity (with 11C- MP4A) (Emamzadeh and Surguchov 2018). Another radiotracer able to distinguish between PD

29 and MSA is I23I-metaiodobenzylguanidine (I23I-MIBG), which allows quantification of postganglionic sympathetic cardiac innervation via the heart-to-mediastinum (H/M) ratio (Orimo et al. 2012). The H/M ratio of I23I-MIBG uptake is diminished in idiopathic PD patients, but not in patients with MSA (Orimo et al. 2012). While SPECT and PET imaging reveal function of an organ, MRI is another imaging technique that gauges anatomy and structure. Diffusion weighted imaging is a form of MRI that measures the rate of water diffusion through a tissue, with greater diffusivity (greater mobility of water molecules) representing higher cell death and reduced region volume (Emamzadeh and Surguchov 2018). This technique has been reported to differentiate between PD and MSA (Chung et al. 2009) as well as PD and progressive supranuclear palsy (Seppi et al. 2003). MRI can also detect the reduced volume of caudate and putamen (striatum) in PD patients compared to controls (Saeed et al. 2017). Finally, transcranial B-mode sonography, used to monitor the blood flow velocity of brain vessels by measuring the frequency of ultrasound waves and their echoes, is used to show higher echogenicity of the substantia nigra in PD brains (Emamzadeh and Surguchov 2018). The latter may be due to increased iron deposition and gliosis in PD substantia nigra (Skoloudik et al. 2014). iii. Biochemical Markers: From a practical point of view, the ideal biomarker would be quick and inexpensive to measure and readily quantifiable in accessible clinical samples, such as blood, cerebrospinal fluid (CSF) or saliva (Kalia 2019). Hundreds of studies have identified potential neurochemical markers of PD, which include: (i) decreased CSF orexin (hypocretin) (Fronczek et al. 2007), a neuropeptide hormone expressed by a small number of dorsolateral hypothalamus neurons and shown to regulate sleep-wake cycle, cardiovascular responses, heart rate and blood pressure (Emamzadeh and Surguchov 2018); (ii) increased 8-hydroxy-2’- deoxyguanosine (8-OHdG) levels in CSF and serum (Kikuchi et al. 2002), indicating increased oxidative DNA damage; (iii) altered peripheral proteasome and caspase activity (changes in proteasome 20S activity, ATP levels) (Blandini et al. 2006); (iv) low CSF concentrations of 3,4- dihydroxyphenylacetic acid (DOPAC) and other dopamine metabolites in pre-clinical PD (Goldstein et al. 2018); (v) changes in peripheral microRNA (miRNA) levels (see Section 8.3); (vi) altered α-synuclein levels (soluble, aggregated and post-translationally modified forms) in CSF, blood and saliva, with general consensus reporting reduced total α-synuclein, higher oligomeric

30 α-synuclein and higher oligomeric to total α-synuclein ratios in PD patients compared to controls (Al-Nimer et al. 2014, Bougea et al. 2019, Daniele et al. 2018a, Daniele et al. 2018b, Devic et al. 2011, Gao et al. 2015, Kang et al. 2016, Vivacqua et al. 2016, Vivacqua et al. 2019); (vii) variable DJ-1 levels reported in CSF, blood, saliva and urine (Devic et al. 2011, Jang et al. 2018, Lin et al. 2012, Waragai et al. 2007); (viii) decreased plasma and CSF apolipoprotein A1 (Swanson et al. 2015, Wang et al. 2010a), the main constituent of high-density lipoprotein particles and involved in cholesterol metabolism; (ix) altered cargo content of circulating extracellular vesicles (EVs) (see Section 8.4); and (x) increased salivary heme oxygenase-1 (HO-1) concentrations in early-stage (H&Y stage 1) PD (see Section 8.5.3) (Song et al. 2018). Validation of an easily quantifiable biomarker of idiopathic PD would address a major unmet clinical imperative by facilitating rapid and accurate diagnosis of this condition, assisting in patient and family counseling and possibly accelerating the early implementation and surrogate monitoring of effective neuroprotective therapies, as they become available. 8.2.9. Treatment In 1817, James Parkinson devoted a chapter of his original monograph to “considerations respecting the means of cure” in which he hoped for the identification of a treatment by which “the progress of the disease may be stopped” (Parkinson 1817). And though 200 years later we still lack a cure that stops or slows neurodegeneration in this condition, we have made significant strides in treating the symptoms of PD. Classical anti-parkinsonian interventions can include any combination of medications and, less commonly, surgery. In addition to a neurologist or movement disorder specialist, an interdisciplinary team intervention approach for the management of PD can also include a nurse, a speech and language therapist, a physiotherapist, a social worker, a psychiatrist, an occupational therapist, a sexologist and a dietician (Giladi et al. 2014). The mainstay of pharmacological treatment for motor symptoms of PD are medications that enhance intracerebral dopamine concentrations or stimulate dopamine receptors. Many of these drugs were designed to target elements of dopamine metabolism. In the pre-synaptic terminal, the amino acid tyrosine is converted by tyrosine hydroxylase (TH) to L-dopa (Axelrod and Weinshilboum 1972), which is converted into dopamine by aromatic L-amino acid

31 decarboxylase (AADC) (Kuhar et al. 1999). Dopamine is transported into the synaptic space by DAT and VMAT2 (Erickson and Eiden 1993, Lohr et al. 2017), where it undergoes one of two fates, namely (i) conversion to homovanillic acid (HVA) by either monoamine oxidase B (MAO-B) or catechol-o-methyl transferase (COMT) (Mannisto and Kaakkola 1999), or (ii) re-uptake by DAT and subsequent conversion into DOPAC by MAO-A (Lohr et al. 2017). Finally, DOPAC is converted into HVA by COMT (Mannisto and Kaakkola 1999). The use of the dopamine precursor, L-dopa, for treatment of PD was discovered in the 1960s (Birkmayer and Hornykiewicz 1961, Cotzias et al. 1967) and, today, is the most commonly prescribed medication for treatment of PD symptoms (Schapira 2009). Dopamine cannot cross the blood-brain barrier (BBB) while its precursor can, though large doses are required to produce an effect since rapid turnover in the periphery occurs before reaching the brain (Schapira 2009). In order to combat the latter, AADC inhibitors (benserazide and carbidopa) are often given concurrently with L-dopa to prevent peripheral breakdown, allowing more L-dopa to cross the BBB (Schapira 2009). These drugs include L-dopa + carbidopa immediate release (e.g. Sinemet), L-dopa + benserazide (e.g. Prolopa) and L-dopa + carbidopa controlled release (e.g. Sinemet CR), which are administered orally, and L-dopa + carbidopa administered via intestinal gel (e.g. Duodopa). COMT inhibitors can also be prescribed in combination with L-dopa in order to slow or prevent its breakdown in peripheral tissues (Schapira 2009). These drugs include entacapone (e.g. Comtan), entacapone + L-dopa + carbidopa (e.g. Stavelo), tolcapone (e.g. Tasmar) and opicapone (e.g. Ogentys), which are all administered orally. Dopamine agonists are another form of anti-parkinsonian medication that acts as synthetic agents to stimulate dopamine’s actions in the brain (Schapira 2009). These drugs include bromocriptine (e.g. Parlodel), pramipexole (e.g. Mirapex) and ropinirole (e.g. Requip), which are administered orally, and rotigotine (e.g. Neupro), which is administered via patch. MAO-B inhibitors prevent the metabolism of dopamine in the brain, resulting in increased neural dopamine levels (Schapira 2009). These drugs include rasagiline (e.g. Azilect) and selegiline (e.g. Eldepryl), which are administered orally. Bradykinesia and rigidity reliably respond to dopaminergic treatments early in the disease (Kalia and Lang 2015). Finally, anticholinergic agents have been postulated to correct the imbalance between dopamine and acetylcholine levels observed in PD (Kalia and Lang 2015). These drugs include benztropine (e.g. Cogentin),

32 amantadine (e.g. Symmetrel), trihexyphenidyl (e.g. Artane) and procyclidine (e.g. Kenadrin), which are all administered orally. Tremor is inconsistently responsive to dopamine replacement therapy, however these anticholinergic agents have been be shown to be effective for tremor (Kalia and Lang 2015). Common adverse reactions to anti-parkinsonian medications include nausea, daytime somnolence, edema, impulse control disorders (pathological gambling, hypersexuality, binge eating and compulsive spending), hallucinations and drug-induced dyskinesia (Kalia and Lang 2015). Notably, long-term dopaminergic treatment by late-stage PD can lead to major complications, such as motor and non-motor fluctuations, severe dyskinesia and psychosis (Kalia and Lang 2015). In addition to medications aimed to alleviate the motor symptoms of PD, a number of medications exist for treatment of typical non-motor symptoms, including psychiatric symptoms, sleep disorders, autonomic dysfunction and fatigue (Kalia and Lang 2015). Finally, regular exercise programs are often encouraged as an effective therapeutic intervention, with evidence supporting beneficial outcomes with regards to physical functioning, quality of life, strength, balance and gait speed (Goodwin et al. 2008). When medications cannot moderate severe symptoms of PD, surgery and deep brain stimulation (DBS) are considered as the final options for treatment. DBS involves sending electrical impulses to certain regions of the basal ganglia by a neurostimulator device implanted into the brain, similar in action to a pacemaker (Eisinger et al. 2019). In PD, there is decreased globus pallidus externus (GPe) activity and increased subthalamic nucleus (STN), globus pallidus internus (GPi) and substantia nigra pars reticularis activity (Eisinger et al. 2019). According to the ‘rate model’, this is summarized as: (1) increased activity of striatal indirect-pathway neurons, leading to increased inhibition of GPe, disinhibition of STN and subsequent increased excitation of GPi and substantia nigra reticulata, and (2) decreased activity of striatal direct-pathway neurons (DeLong and Wichmann 2007, Eisinger et al. 2019). Taken together, this results in excessive inhibition of components of the motor circuit in the thalamus, cortex and brainstem (DeLong and Wichmann 2007). Stimulation of the STN or GPi via DBS has been shown to improve motor symptoms and quality of life (Deuschl et al. 2006, Okun et al. 2009, Schuepbach et al. 2013, Weaver et al. 2009, Williams et al. 2010), as well as even some non-motor symptoms (anxiety and pain) (Witjas et al. 2007, Witt et al. 2008). The STN is typically the target linked to greater

33 medication reduction, while the GPi may be preferable for dyskinesia control and when long- term flexibility in medication management is required (Eisinger et al. 2019). However, several adverse outcomes have been associated with DBS, including negative cognitive outcomes and the possibility of brain infection (Bronstein et al. 2011, Eisinger et al. 2019). In recent years, the development of gene therapy has offered new avenues for therapeutics in the treatment of PD. Using adeno-associated viral vectors carrying human gene copies, gene therapy targets include AADC, glutamate decarboxylase (GAD), glial cell line-derived neurotrophic factor and neurturin (Emamzadeh and Surguchov 2018). A number of clinical trial programs are also underway, aimed at: (i) inhibiting α-synuclein misfolding and aggregation (NPT200-11 and NPT088); (ii) increasing α-synuclein degradation (Nilotinib); (iii) decreasing extracellular α-synuclein via active (immunizing patients with modified α-synuclein to generate endogenous protective antibodies) or passive (injecting antibodies targeting α-synuclein) immunotherapy approaches; (iv) increasing GBA activity (Ambroxol and LTI291); (v) reducing GBA-related glycosphingolipids (Venglustat); and (vi) inhibiting LRRK2 kinase (DNL201) (Sardi and Simuni 2019). Another, albeit controversial, therapeutic avenue for the treatment of PD is the use of dopamine cell-replacement therapy, though research is still needed to improve graft function and reproducibility by increasing the survival and purity of mesencephalic dopaminergic neurons in the graft, accelerating their functional maturation and rendering them less susceptible to attack by the immune system (Parmar et al. 2020). Human clinical trials of pluripotent stem cell-derived dopaminergic neuron therapies are currently underway (Barker et al. 2017). As discussed in Section 8.2.2, the causes of PD are heterogeneous, and it is likely that multiple cellular processes are variably involved in the neurodegenerative process in PD. Thus, earlier expectations by Parkinson and others that a single agent could be capable of stopping or reversing the disease course may have been naïve (Kalia and Lang 2015). A more effective strategy may be to target select dysfunctional pathological or molecular mechanisms with a combination of drugs mitigating one or more of these pathways. 8.2.10. Brain Pathology and Pathomechanisms The exact etiology of neurodegeneration in PD patients is not well understood. The onset and progression of PD likely involves a complex interplay of molecular pathways, including (i)

34 dopaminergic neuron degeneration and variable changes in other neurotransmitter systems; (ii) iron deposition; (iii) α-synuclein-containing inclusions called Lewy bodies or neurites; (iv) neuroinflammation; (v) mitochondrial dysfunction; (vi) impairment of the autophagy-lysosome pathway; (vii) dysregulation of the ubiquitin-proteasome system (UPS); and (viii) aberrant cell death. Inherent in PD pathology is the significant overlap between many of these distinct pathways, with oxidative stress acting as a common underlying mechanism. Oxidative stress leads to cellular dysfunction and eventual cell death. Reactive oxygen species (ROS), contributing to oxidative stress, are continuously produced by all body tissues. When there is an imbalance between ROS production and cellular antioxidant activity, oxidative stress ensues (Blesa et al. 2015). The mitochondria, a major target in PD pathology, are the main site of ROS generation within the cell (Blesa et al. 2015). Although the precise mechanism remains unknown, many of the pathways thought to be involved in PD pathogenesis contribute to ROS production and/or are triggered by resultant oxidative stress. i. Neurodegeneration and Neurotransmitter Systems: PD is characterized by progressive neurodegeneration throughout the nigrostriatal tract, most marked in the substantia nigra pars compacta, though degeneration also affects neurons throughout the basal ganglia and extending to the locus coeruleus, olfactory bulb, sympathetic ganglia and dorsal motor nucleus of the vagus (autonomic nervous system) (Lang and Lozano 1998, Sulzer and Surmeier 2013). The substantia nigra is predominantly composed of neurons which secrete dopamine, an excitatory or inhibitory neurotransmitter (depending on the receptor it binds) that regulates the excitability of striatal neurons (Maiti et al. 2017). Dopamine is involved in controlling select bodily movements and emotional responses (Maiti et al. 2017). Since the landmark observation in 1960, hundreds of studies have confirmed the degeneration of dopaminergic neurons of the substantia nigra and decreased striatal dopamine levels in PD (Ehringer and Hornykiewicz 1960, German et al. 1989, German et al. 1992, Greffard et al. 2006, Hirsch et al. 1988, Pakkenberg and Brody 1965). Inadequate dopamine levels result in less inhibition of the activity of striatal neurons (indirect pathway), allowing them to fire excessively and ultimately explaining cardinal hypokinetic motor signs observed in PD (Maiti et al. 2017). At the time of diagnosis, 50-90% of dopaminergic neurons have already been lost (Kordower et al. 2013). Selective depletion of dopaminergic neurons in

35 the substantia nigra underscores the uniquely vulnerable nature of this brain region. Dopamine oxidation to o-quinones has been proposed to play a role in the degeneration of dopaminergic neurons containing neuromelanin, since these o-quinones can participate in neurotoxic reactions that promote oxidative stress (Bisaglia et al. 2010, Segura-Aguilar et al. 2014). Neuromelanin is the catecholamine-derived pigment within the dopaminergic neurons of the substantia nigra and norepinephrine neurons of the locus coeruleus, the two neuronal populations most targeted in PD (Hirsch et al. 1988, Zucca et al. 2017). Neuromelanin pigment appears as a black and insoluble molecule composed of oxidized dopamine polymers, proteins, lipids and metal ions (Zucca et al. 2017), and it accumulates with normal aging (Zecca et al. 2002, Zecca et al. 2004a). While controversy exists surrounding the functional role of neuromelanin, it seems dual protective and toxic roles may be occurring, depending on the cellular context and conditions. Neuromelanin is an effective metal chelator, and most commonly serves to trap iron via the neuromelanin-iron complex, contributing to neuroprotection from oxidative reactions (Zucca et al. 2017). On the other hand, when neuromelanin-containing organelles accumulate high levels of toxins and iron during aging and, more relevantly, during PD, neurodegenerative processes can be triggered, including oxidative stress, mitochondrial dysfunction, impairment of the proteasome system and α-synuclein aggregation (LaVoie et al. 2005, Van Laar et al. 2009, Zucca et al. 2017). Additionally, neuromelanin released by degenerating neurons can activate microglia, which elaborate pro- inflammatory cytokines and nitric oxide. The latter, in turn, may promote additional neuronal death and further release of neuromelanin, thereby completing a self-amplification mechanism of neuroinflammation and neurodegeneration (Zucca et al. 2017). Neuromelanin concentration in PD substantia nigra is approximately 50-60% the level of age-matched control subjects, due to the degeneration of neurons containing neuromelanin (Sulzer et al. 2018, Zecca et al. 2002, Zecca et al. 2004a). In addition to excess free radicals, levels of key antioxidant and trophic factors are reduced in PD substantia nigra, including glutathione (GSH) (Jenner et al. 1992, Sian et al. 1994). GSH is considered the major antioxidant of neurons and acts either alone or in concert with enzymes within the cells to reduce superoxide and hydroxyl radicals, hydrogen peroxide and peroxynitrite (Smeyne and Smeyne 2013). In contrast to the substantia nigra, dopaminergic neurons within the olfactory bulb actually increase in PD and experimental parkinsonisms and its

36 association with hyposmia (a cardinal non-motor symptom of PD) is consistent with the notion that olfactory transmission within the glomerular layer of the olfactory bulb is inhibited by dopamine (Ennis et al. 2001, Huisman et al. 2004, Pifl et al. 2017). Serotonin is another monoamine neurotransmitter with excitatory or inhibitory activity (depending on the receptor it binds) implicated in the pathophysiology of PD. A reduction in serotonin levels in select brain regions (cerebral cortex, basal ganglia, brainstem and spinal cord) and changes in serotonin transporter and receptor activities in various brain nuclei have been observed in PD (Fahn et al. 1971, Halliday et al. 1990, Huot et al. 2011, Maiti et al. 2017, Raisman et al. 1986). Serotonin is partly responsible for several motor and non-motor symptoms, such as tremor, cognitive impairment, depression, psychosis and drug-induced dyskinesia (Huot et al. 2017). Depletion of serotonergic neurons may also contribute, along with nigral dopaminergic neurons, to the strong association between PD and RBD (Olson et al. 2000, Onofrj et al. 2002, Trenkwalder 1998). Acetylcholine is another neurotransmitter with both inhibitory and excitatory properties, active at the neuromuscular junction as well as within the autonomic nervous system. Acetylcholine plays a significant role in cognition and is downregulated in several neurodegenerative conditions, most notably in AD and PD (Liu et al. 2015, Tagliavini and Pilleri 1983). This typically presents as differential patterns of neuronal loss in the nucleus basalis of Meynert, which is predominantly composed of cholinergic neurons. In post-mortem brain tissue of PD patients with cognitive decline, neuronal loss and the presence of Lewy bodies were found within the nucleus basalis of Meynert, supporting the notion that the cholinergic system is involved in cognitive dysfunction observed in PD (Maiti et al. 2017). Selective loss of cholinergic neurons is also observed in the brainstem of PD patients (Jellinger 1991, Zweig et al. 1989), and these neurons have been shown to play a role in REM sleep modulation (Monti and Monti 2000). Thus, the frequency of RBD among PD patients may also be explained by cholinergic neuron degeneration or dysfunction. Finally, gamma amino butyric acid (GABA) is an inhibitory neurotransmitter that controls the calcium influx either directly (via GABAergic receptors) or indirectly (via astrocyte networks) (Allaman et al. 2011). In PD, mitochondrial damage renders calcium homeostasis impaired,

37 leading to calcium excitotoxicity. This contributes to neurodegeneration in the substantia nigra, where calcium buffering is controlled by GABA activity (Maiti et al. 2017). GABAergic projections from the basal ganglia output nuclei are reported to be tonically overactive and show variable amounts of abnormal oscillatory activity in human PD and experimental parkinsonism (Alexander 2004, Emir et al. 2012, Gwiazda et al. 2002, Kish et al. 1986, Ondo and Hunter 2003, Oz et al. 2006). ii. Iron Deposition: Abnormal iron deposition was first reported in the basal ganglia of PD brain in 1924 (Lhermitte et al. 1924). While iron accumulation is present in the normal aging brain (select regions), the iron retention is exacerbated in PD (Ward et al. 2014). This transition metal participates in electron-transfer reactions and is essential for normal cellular functions (Zucca et al. 2017). Iron can redox cycle between ferrous (Fe2+) and ferric (Fe3+) oxidation states and in most biological systems these states are in equilibrium (Zucca et al. 2017). However, iron complexes display large variability of stability constants, depending on the oxidation state and ligand to which iron is bound (Zucca et al. 2017). The major roles of iron include: (i) oxygen transport, storage and delivery as a heme cofactor in hemoglobin and myoglobin, as well as a heme cofactor in many oxidase and oxygenase (e.g. HO-1) enzymes and electron transfer proteins (cytochromes); (ii) formation of iron-sulfur (Fe-S) clusters, with functions ranging from general cell metabolism to DNA repair; and (iii) DNA synthesis, since ribonucleotide reductase (involved in the synthesis of the DNA precursor) is iron-dependent (Zucca et al. 2017). Besides the liver, the brain contains one of the highest tissue iron concentrations (Bush et al. 1995, Hallgren and Sourander 1958, Zecca et al. 2004b). In the brain, iron functions as a crucial element in: (i) generation of ATP by electron transport in mitochondria; (ii) synthesis and metabolism of neurotransmitters, including dopamine, norepinephrine, epinephrine and serotonin, via iron- dependent enzymes; (iii) uptake, extracellular concentration, interaction with receptors and catabolism of neurotransmitters; and (iv) myelination (Zucca et al. 2017). When iron levels exceed the cellular iron sequestration capacity of storage proteins or other molecules, the iron in the labile iron pool (defined as the pool of chelatable and redox-active iron in complexes of low stability (Kakhlon and Cabantchik 2002)) may increase, becoming harmful and leading to oxidative damage and cell death (Zucca et al. 2017). Iron can participate in Fenton chemistry,

38 wherein ferrous iron is oxidized by hydrogen peroxide to ferric iron, forming a hydroxide ion and hydroxyl radical in the process (Wardman and Candeias 1996). The hydroxyl radical is among the most harmful of ROS (Dlouhy and Outten 2013), and can directly damage nuclear and mitochondrial DNA, affect DNA expression by epigenetic modification, form protein carbonyl derivatives and release Fe-S clusters to further feed ROS production via Fenton chemistry (Zucca et al. 2017). Relating specifically to PD, oxidation of catecholamines, like dopamine, via ferric iron forms highly reactive and toxic quinone species (Paris et al. 2005, Sulzer and Zecca 2000). These breakdown products of dopamine are even more neurotoxic than hydroxyl radicals (Zhou et al. 2010). This may further explain the unique vulnerability of dopaminergic neurons within the substantia nigra, considering iron accumulation occurs in PD in a number of neurochemically distinct regions yet does not stimulate widespread neuron loss (Hare and Double 2016). The formation of toxic products from the iron-dopamine couple may be responsible for producing a far more damaging chemical microenvironment (Hare and Double 2016). Neuromelanin- containing dopaminergic neurons of PD nigra show increased levels of redox-active iron (Faucheux et al. 2003, Jellinger et al. 1992), as do hallmark Lewy bodies within this brain region (Castellani et al. 2000). Further, aggregation of α-synuclein, hyper-phosphorylated tau and β- amyloid can be triggered by elevated iron levels as a consequence of disrupted iron homeostasis (Hashimoto et al. 1999, House et al. 2004, Li et al. 2010, Yamamoto et al. 2002). While intracellular iron levels are controlled by iron regulatory proteins 1 and 2 (IRP1/2), their activity is unaltered in PD substantia nigra despite elevated iron levels (Faucheux et al. 2002), suggesting a failure of normal iron regulatory mechanisms (Hare and Double 2016). Reasons for the high accumulation of iron particularly in the substantia nigra of PD patients may include: (i) increased permeability or dysfunction of BBB during the disease; (ii) increased pro-inflammatory state; (iii) elevated expression of lactoferrin receptors (involved in iron uptake via lactoferrin), as observed in PD nigral neurons; (iv) upregulation of a specific isoform of the divalent metal ion transporter 1 in the PD nigra; (v) decreased ferroxidase activity of ceruloplasmin, a ferroxidase essential for normal brain iron homeostasis, in both the substantia nigra and CSF of PD patients; (vi) dysregulation of transferrin/transferrin receptor type 2-mediated iron transport in dopaminergic

39 neurons of PD patients; (vii) impaired iron efflux; and (viii) mutations in genes coding proteins involved in iron transport, binding and metabolism (Zucca et al. 2017). Additionally, mutant forms of transferrin, a critical protein for neuronal iron uptake, are associated with increased susceptibility to PD (Borie et al. 2002, Rhodes et al. 2014). Neurodegenerative mechanisms originating from iron toxicity can eventually lead to classical apoptosis signaled by oxidative stress or to the more recently identified ferroptosis (see Section 8.2.10viii), which is a non-apoptotic, iron-dependent and oxidative form of cell death (Dixon et al. 2012, Li et al. 2020). Importantly, treatment of experimental parkinsonism and human PD patients with the iron chelator, deferiprone, reduced dopaminergic dysfunction, decreased nigral iron deposition and improved symptomatic profiles (Devos et al. 2014, Martin-Bastida et al. 2017), directly implicating iron in PD pathogenesis. iii. α-Synuclein and Lewy Pathology: Shortly after the discovery of SNCA mutations causing a rare monogenic form of PD in 1997 (Polymeropoulos et al. 1997), α-synuclein protein aggregates were identified as a major component of hallmark Lewy bodies and a key player in PD pathology (Spillantini et al. 1997). α-Synuclein is a 14 kDa protein (140 amino acids) and a member of the synuclein family, which also contains β- and γ-synuclein (Clayton and George 1998). In the cytoplasm, α-synuclein is intrinsically disordered, though it becomes α-helical in conformation when bound to phospholipids of cellular membranes (Burre et al. 2013). Although physiological α-synuclein has largely been considered a natively unfolded monomer that acquires α-helical secondary structure when interacting with phospholipids (Weinreb et al. 1996), native α-synuclein may exist physiologically as a folded helical tetramer that is resistant to fibrillization and thus distinct from pathological oligomers (Bartels et al. 2011, Bengoa-Vergniory et al. 2017, Dettmer et al. 2013, Luth et al. 2015, Wang et al. 2011b). Additionally, α-synuclein can localize to mitochondria (Chinta et al. 2010), as well as undergo secretion and transfer to nearby cells (Hansen et al. 2011, Li et al. 2008). Accumulation of α-synuclein in the mitochondria is associated with decreased mitochondrial membrane potential, respiratory chain dysfunction, mitochondrial DNA damage and oxidative stress in PD (Devi et al. 2008, Parihar et al. 2009). Though the precise function of α-synuclein remains elusive, a current consensus is that α-synuclein functions to promote membrane curvature, thereby contributing to synaptic trafficking and vesicle budding

40 (Chandra et al. 2003, Varkey et al. 2010). Accordingly, α-synuclein is associated with presynaptic terminal soluble N-ethylmaleimide-sensitive factor attachment protein (SNAP) receptor (SNARE) complexes, involved in vesicle fusion (Burre et al. 2010). Finally, α-synuclein has been shown to play a role in compartmentalization, storage, release and recycling of neurotransmitters (Nemani et al. 2010, Vekrellis et al. 2011). By structure, α-synuclein protein consists of three domains, namely an amino terminus (residues 1-60), a central hydrophobic region (residues 61-95) called the non-β-amyloid component (NAC) domain and a carboxyl terminus (residues 101-140) that is highly negatively charged and prone to be unstructured (Jakes et al. 1994). The N-terminus is involved in mediating lipid binding properties of the protein, the NAC region has been identified as the aggregation domain and the C-terminus is affiliated with calcium binding and inhibition of protein aggregation (Clayton and George 1998, Ueda et al. 1993). The N-terminus is also particularly significant for the pathological dysfunction of α-synuclein as many of the rare point mutations are located in this region (Dehay et al. 2015). A number of autosomal dominant mutations in the SNCA gene have been found to cause familial PD, including A53T, E46K, H50Q, G51D, A53E, A53V and A30P (Meade et al. 2019). The various mutations result in unique α-synuclein aggregation rates and the oligomers that become populated (Meade et al. 2019). In addition to these missense mutations, autosomal dominant familial PD has also been observed with SNCA gene duplication or triplication (Chartier-Harlin et al. 2004, Singleton et al. 2003). Falling in line with the role of α-synuclein in PD pathogenesis, instances of SNCA triplication are more severe than gene duplication. Overall, this highlights the importance of intracellular concentrations in driving increased likelihood of α-synuclein misfolding, propagation and ultimately to an earlier onset of the disease phenotype relative to idiopathic PD (Meade et al. 2019). After Spillantini demonstrated that a-synuclein is the major component of Lewy bodies in PD (Spillantini et al. 1997), Braak went on to map the neuroanatomical distribution of Lewy body pathology in hundreds of brains of autopsy cases with and without clinically diagnosed PD (Braak et al. 2003). Lewy bodies are spherical cytoplasmic inclusions 8-30 µm in diameter with a dense eosinophilic core and loose fibrillary rim (Baba et al. 1998). Key features that affect the pathogenicity of Lewy bodies include size, subcellular localization, b-pleated sheet conformation

41 as well as hyper-phosphorylation and poly-ubiquitination of constituent a-synuclein (Chu and Kordower 2015). In addition to a-synuclein, Lewy bodies are also composed of ubiquitin, hyperphosphorylated tau, b-amyloid, neurofilaments and molecular chaperones, among other constituents (Baba et al. 1998). Braak described Lewy body pathology in stages, expanding from: the enteric plexus, motor component of the vagus nerve and olfactory bulb (stage 1); to the locus coerulus, caudal raphe nuclei and magnocellular reticular formation (stage 2); to the substantia nigra, amygdala central subnucleus, pedunculopontine tegmental nucleus and Maynert’s nucleus (stage 3); to the cerebral cortex (stage 4); to the tertiary sensory association areas and prefrontal cortex (stage 5); and finally, to the secondary then primary motor and sensory areas (stage 6) (Braak et al. 2003). Lewy bodies are also detected in peripheral neurons of autonomic nervous system, including those innervating the salivary glands and gastrointestinal tract (Braak et al. 2006). The spreading theory was further fueled by pathological analysis of graft tissue from human PD subjects who received transplant of embryonic mesencephalon, which revealed Lewy body-like pathology in grafted tissue 14 years after transplant (Kordower et al. 2008). Similar to Braak’s findings that a-synuclein pathology gradually spreads throughout the neuraxis as PD progresses, a prion-like mechanism may explain how this pathology can transfer from host to graft (Kordower and Brundin 2009). With the propensity to aggregate, a-synuclein may be acting in similar fashion to a prion protein and directly contribute to propagation of the neurodegenerative process (Masuda- Suzukake et al. 2013, Olanow and Brundin 2013). While precise mechanisms of abnormal a- synuclein aggregation remain disputed, there is fair consensus implicating oxidative reactions in this process (Deas et al. 2016, Goedert 2001). Dimerization of Tyr125 is the initial and rate- limiting step that ultimately leads to a greater potential for self-interaction of this protein (Takahashi et al. 2002). The dimerized a-synuclein serves as the template for native a-synuclein monomers to refold into oligomers, protofibrils and fibrils rich in b-sheets. α-Synuclein oligomers, protofibrils and fibrils contribute to neuronal death via oxidative stress, energy failure, excitotoxicity and neuroinflammation (Kim et al. 2014, Marques and Outeiro 2012). Phosphorylation, oxidation, nitration and glycation modifications of a-synuclein enhance its propensity for aggregation (Vicente Miranda et al. 2017). Of particular importance,

42 phosphorylation is a necessary event during the formation of Lewy bodies, as de-phosphorylation specifically at Ser129, ameliorates the phenotype (Anderson et al. 2006). Furthermore, a- synuclein aggregation is thought to be a key driving force in PD pathogenesis, supported by the fact that young asymptomatic mice with a-synuclein pre-formed fibrils, prepared from older symptomatic mice, accelerated a-synuclein hyper-phosphorylation at Ser129, aggregated a- synuclein and decreased survival time (Luk et al. 2012, Sacino et al. 2014). Extensive in vitro and in vivo experiments, pioneered by Virginia Lee and John Trojanowski, have shown that a- synuclein fibrils are taken up by neurons, seed aggregation of endogenous a-synuclein, are transported along the axon and then can be released and taken up again by other adjacent neurons, in a prion-like manner (Guo and Lee 2014, Paumier et al. 2015, Volpicelli-Daley et al. 2014). Dopamine metabolism is impacted by a-synuclein. In PD patients, cells without a- synuclein immunoreactivity displayed the greatest expression of TH, cells with non-aggregated a-synuclein displayed diminished, but detectable TH, and the expression of TH was virtually undetectable in nigral neurons with a-synuclein immunoreactive inclusions (Chu et al. 2006). Moreover, a-synuclein has been shown to interact with dopamine and dopamine quinones, resulting in long-lived protofibril intermediates, cross-linked proteins and aggregates (Conway et al. 2001, Thakur et al. 2017). The attendant oxidative stress may contribute to cellular compromise and death (Perez and Hastings 2004). It is of particular interest that very soon after the discovery of a-synuclein, the protein was shown to contain binding sites for divalent metals, such as copper, manganese and iron (Binolfi et al. 2006, Lingor et al. 2017, Rasia et al. 2005). Upon phosphorylation, a-synuclein gains a higher affinity for the ferrous ion at the C-terminus of the protein (Lu et al. 2011). a-Synuclein even contains an iron-responsive element in its 5’- untranslated region (UTR), meaning increased levels in iron (as seen in PD) could lead to increased translation of a-synuclein protein (Friedlich et al. 2007, Lingor et al. 2017). As discussed in Section 8.2.10ii, iron has also been shown to increase the propensity of a-synuclein aggregation (Kostka et al. 2008, Uversky et al. 2001). Importantly, the pro-aggregative effect of iron on a-synuclein can be enhanced in the presence of dopamine (Ostrerova-Golts et al. 2000). Various other events can trigger aberrant processing, folding and degradation of a-synuclein,

43 including inflammation, lysosomal failure and ubiquitin-proteasome pathway dysfunction, as discussed in the following sections (Chu and Kordower 2007, Olanow and Brundin 2013). iv. Neuroinflammation: Sustained inflammatory responses, T cell infiltration and glial cell activation, hallmarks of neuroinflammation, are common features observed in human PD patients and experimental parkinsonism (Hirsch et al. 2012, Lv et al. 2015, Wang et al. 2015a). While glial activation may be beneficial to the host during early phases of the neurodegenerative process (Hu et al. 2012, Wang et al. 2013), long-term over-activation of microglia and astrocytes in the PD brain significantly upregulates pro-inflammatory cytokine expression which contributes to the acceleration of nigral dopaminergic neuron degeneration (Wang et al. 2015a). Activated glia not only release cytokines, but also expel glutamate (excitotoxicity), ROS and reactive nitrogen species (RNS), ultimately increasing dopaminergic neuron vulnerability (Jenner 2003). Reactive microglia and astrocytes have been observed in various regions of PD brain, most notably the substantia nigra and striatum (Bartels et al. 2010, Gerhard et al. 2006, McGeer et al. 1988, Yamada et al. 1992a), and further biochemical analyses in both the midbrain and CSF of PD patients revealed higher levels of pro-inflammatory mediators, such as tumor necrosis factor-a (TNF-a), interleukin-1b (IL-1b), interferon-γ (IFN-γ), transforming growth factor-b (TGF-b), interleukin-6 (IL-6) and interleukin-1 (IL-1) (Blum-Degen et al. 1995, Koziorowski et al. 2012, Mogi et al. 1995, Mount et al. 2007). Neuroinflammation observed in PD patients may be due to deficient regulation of immune responses associated with advancing age, exposure to infectious agents (e.g. bacteria, viruses) or exotoxins (e.g. MPTP, pesticides), neuromelanin or deposition of insoluble protein fibrils (e.g. a-synuclein) (Caggiu et al. 2019). In fact, activated microglia have been shown to accumulate around a-synuclein-positive aggregates in PD brain (Yamada et al. 1992b). The neurotoxicity induced by excessive, mutant or misfolded a-synuclein may be partially caused by glial-mediated inflammatory responses. Furthermore, mounting evidence indicates that many PD-associated genes are involved in the neuroinflammatory response. Microglial activation, astrogliosis and pro-inflammatory cytokine release were observed in various animal models of experimental parkinsonism, including a-synuclein transgenic (TG) mice, LRRK2 mutant mice and Parkin, Pink1 or Dj-1 knock-out mice (Wang et al. 2015a), in addition to

44 classical toxin models (Caggiu et al. 2019). It remains ambiguous whether neuroinflammation is a primary cause or consequence of the neurodegenerative process during progression of PD. v. Mitochondrial Dysfunction: Considering the important role of mitochondria in energy metabolism, calcium homeostasis, cellular quality control and stress response pathways and regulation of cell death, it is not surprising that an impairment of mitochondrial function results in cellular damage and neurodegeneration. As such, mitochondrial dysfunction has been implicated as an integral component of PD pathogenesis (Hauser and Hastings 2013). A number of endogenous and exogenous inhibitors of mitochondrial function, including MPTP, rotenone, paraquat, nitric oxide, the dopamine quinone aminochrome and others, induce phenotypes consistent with sporadic PD (Park et al. 2018). For instance, 1-methyl-4-phenylpyridinium (MPP+; toxic derivative of MPTP) and rotenone inhibit mitochondrial complex I (NADH:ubiquinone oxidoreductase) of the electron transport chain and increases superoxide formation (Lambert and Brand 2004, Nicklas et al. 1985, Ramsay et al. 1986), and, indeed, complex I activities are reduced in PD patients (Winklhofer and Haass 2010). Furthermore, the majority of genetic PD loci are directly associated with mitochondria, including SNCA, LRRK2, PARK2, PINK1, DJ-1, ATP13A2 and CHCHD2. a-Synuclein has a non-canonical mitochondrial targeting sequence that localizes it to mitochondrial membranes, impacting mitochondrial structure and function (Mullin and Schapira 2013). Further, mutant a-synuclein induces mitochondrial fragmentation, impairs calcium exchange and reduces mitochondrial energy production (Paillusson et al. 2017, Ryan et al. 2015). Healthy mitochondria are maintained by parkin via regulation of their biogenesis and degradation in a process called mitophagy (Pickrell and Youle 2015). In the early stages of mitochondrial degradation, parkin is recruited to damaged or dysfunctional mitochondria and activated by PINK1, a PD-related protein, leading to ubiquitination of outer mitochondrial membrane proteins and subsequent proteasomal degradation (Park et al. 2018). The process of mitophagy removes dysfunctional mitochondria from the healthy mitochondrial pool and facilitates their degradation via the autophagy-lysosomal pathway (Park et al. 2018). Loss of parkin or PINK1 impairs various aspects of mitochondrial biology, including degradation (mitophagy), morphology and trafficking (Pickrell and Youle 2015). Importantly, approximately 90% of cellular ROS are produced by mitochondria (Perfeito et al. 2012). Increased formation of

45 mitochondrial ROS combined with defective ROS removal by mitochondrial defense systems leads to oxidative damage to mitochondrial DNA, proteins and lipids as well as disruption in redox signaling pathways, as observed in PD (Winklhofer and Haass 2010). Being highly dynamic organelles, mitochondria are constantly undergoing fission and fusion (Venderova and Park 2012). This dynamic nature permits quick response to changing intracellular conditions. Fusion of neighbouring mitochondria allows the damaged organelle to restore its function and protect mitochondrial DNA (Nakada et al. 2001, Ono et al. 2001), optimizing ATP production (Chan 2006). Fission, on the other hand, is important for removal of damaged mitochondria via mitophagy (see above). Disruption of the balance between fusion and fission can negatively impact mitochondrial transport and distribution (Venderova and Park 2012). Mitochondrial fragmentation, as observed with the autophagic (see Section 8.2.10vi) and apoptotic (see Section 8.2.10viii) pathways, may be caused by shifting mitochondrial dynamics. Although some suggest this fragmentation is caused by a decrease in fusion, most evidence points towards an excess in fission: In response to apoptotic stimuli, for example, dynamin- related protein 1 (Drp1; a key molecule in fission) translocates from the cytoplasm to the mitochondrial membrane where it co-localizes with pro-apoptotic proteins, B-cell lymphoma 2 (Bcl2)-associated X protein (BAX) and Bcl-2 homologous antagonist killer (BAK), and results in fission (Venderova and Park 2012). In experimental parkinsonism, a downregulation in fusion and upregulation in fission have similarly been documented (Celardo et al. 2014, Henchcliffe and Beal 2008). vi. Autophagy-Lysosome Pathway: The pathways by which the majority of cytosolic and misfolded proteins are degraded include the UPS (reviewed in the next section) and the autophagy-lysosome pathway. As observed in PD, impairment of either of these systems may lead to the accumulation and aggregation of proteins, resulting in cellular toxicity and neurodegeneration (Pan et al. 2008). The autophagy-lysosome pathway can be divided into three distinct pathways, namely macroautophagy, microautophagy and chaperone-mediated autophagy. Long-lived, stable proteins, entire organelles (e.g. mitochondria) and large membrane proteins and protein complexes (e.g. oligomers and aggregates) likely utilize macroautophagy as their primary degradation method (Cuervo et al. 2004, Hideshima et al. 2005, Levine and Klionsky

46 2004). In this multi-step process, the autophagosome fuses with lysosomes to form the autophagolysosomes, which degrades its contents via hydrolytic enzymes. This activity also disintegrates the inner membrane within the autophagolysosome, allowing recycling of vacuolar contents into amino acids and energy as needed by the cells (Pan et al. 2008). Chaperone- mediated autophagy involves the additional step of a specific cytosolic protein-molecular chaperone (heat-shock protein of 70 kDa [Hsp70]) complex to facilitate lysosomal degradation by hydrolases (Crotzer and Blum 2005). Dysfunction can occur at many of the above-mentioned steps, any of which may consequently cause the accumulation or aggregation of unwanted proteins, ultimately leading to neurodegeneration (Pan et al. 2008). Importantly, a-synuclein is cleared by autophagy in addition to the UPS. Certain mutant a-synuclein proteins can evade the autophagy-lysosome degradation pathway (Cuervo et al. 2004), and other factors may also contribute to the degradation destiny of a-synuclein, such as (i) folding state; (ii) localization (e.g. cytosolic, membrane-bound, extracellular); (iii) presence of post-translational modifications; and (iv) aggregation state (e.g. monomeric, oligomeric, protofibrillar, fibrillar) (Dehay et al. 2013). A reduced number of intraneuronal lysosomes, decreased levels of lysosomal-associated proteins and accumulation of undegraded autophagosomes have been observed in post-mortem idiopathic PD brains (Alvarez-Erviti et al. 2010, Anglade et al. 1997, Chu et al. 2009, Dehay et al. 2010), suggesting dysfunction of the autophagy-lysosome pathway. Furthermore, PD-linked mutations in LRRK2 and ATP13A2, as well as increased risk of PD among GBA mutation carriers, genes which have been shown to play a role in the autophagy-lysosome pathway, further validate its impairment in PD (Dehay et al. 2013). In addition to contributing to accumulation of aggregated proteins in PD, like a-synuclein, abnormal regulation of autophagic pathways may also lead to apoptosis and eventual cell death (Chu 2006, Klionsky 2006). vii. Ubiquitin-Proteasome System: The UPS is responsible for degradation of short polypeptides into small intracellular and plasma-membrane proteins in normal cells, as well as degradation of misfolded or damaged proteins in the cytosol, nucleus or endoplasmic reticulum (Pan et al. 2008). The system involves the targeting of susceptible proteins by ubiquitin and only the unfolded ubiquitinated proteins can pass through the narrow pore of the proteasome barrel (Pan et al. 2008). Proteasomal degradation yields short peptide fragments (2-25 residues) that

47 are further degraded by peptidases into their constituent amino acids and are then recycled to form new proteins (Olanow and McNaught 2006). Proteins that are excessively misfolded or aggregated, such as α-synuclein, may resist degradation and can even inhibit proteasomal function by blocking the inner chamber of the proteasome (Grune et al. 2004). Proteasome structure and function are altered in PD substantia nigra, and altered levels of expression of proteasome activators are also correlated with PD (Larsen and Sulzer 2002, McNaught et al. 2003, Rubinsztein 2006). Furthermore, PD is associated with SNCA mutations (which could result in excess levels of misfolded and aggregated proteins that resist proteolysis and cause secondary damage to the proteasome); PARK2 mutations (which could prevent ubiquitination of target proteins); and UCH-L1 mutations (which could impair de-ubiquitination of ubiquitinated proteins, thereby preventing their degradation and limiting the supply of ubiquitin monomers necessary for clearing additional proteins) (Olanow and McNaught 2006). Inhibition of proteasomal function has been shown to contribute to oxidative stress, protein aggregation, inflammatory reactions, mitochondrial dysfunction and apoptosis, though proteasomal damage and UPS dysfunction could also be a secondary event and occur as a consequence of any of these PD pathological hallmarks (Olanow and McNaught 2006). viii. Programmed Cell Death: Apoptosis has been recognized as the main mechanism of programmed cell death encompassing the neurodegeneration observed in PD. Apoptosis can occur in response to abnormal intrinsic calcium concentrations (excitotoxicity), DNA damage, afferent or efferent trophic factor deprivation, activation of cell death receptors and oxidative stress (Guiney et al. 2017). In this energy-dependent step-wise process, cells undergo shrinkage, membrane blebbing, chromatin condensation, nuclear DNA fragmentation and formation of apoptotic bodies, which are subsequently removed by phagocytosis (Venderova and Park 2012). Notably, the membrane integrity of apoptotic bodies remains intact, and phagocytosis occurs without activating an inflammatory response (Venderova and Park 2012). Initiator caspases are responsible for starting apoptosis and carrying out cleavage and activation of executioner caspases, which continue downstream events of apoptosis. Caspase activation can be triggered by two well-characterized apoptotic pathways: the mitochondria-mediated pathway (intrinsic; mediated by the Bcl-2 family and permeability transition pore), and the cell surface death

48 receptor pathway (extrinsic; mediated by the TNF/nerve growth factor receptor superfamily) (Guiney et al. 2017, Venderova and Park 2012). Apoptosis in PD has been characterized by the identification of DNA fragmentation, apoptotic chromatin changes as well as elevated caspase-3 (executioner caspase) activity and other pro-apoptotic proteins (e.g. BAX, p53) in dopaminergic neurons of post-mortem substantia nigra (Anglade et al. 1997, Hartmann et al. 2000, Mogi et al. 2000, Tatton 2000, Tompkins et al. 1997). The intrinsic, mitochondria-mediated apoptosis pathway is predominant in PD, involving the generation of ROS, cytochrome c release, ATP depletion and caspase-3 activation (Fiskum et al. 2003), though some evidence for the extrinsic, death receptor pathway also exists (Hayley et al. 2004, Mogi et al. 2000, Simunovic et al. 2009). Localization of α-synuclein to the mitochondrial membrane leads to oxidative stress and release of cytochrome c, which trigger mitochondria-mediated apoptosis (Martinez-Fabregas et al. 2014, Parihar et al. 2008). Certain mitochondrial- and PD-associated genes may also play a role, as mutant SNCA, LRRK2 or PINK1 or depletion of PINK1 are associated with apoptosis in neurons (Klinkenberg et al. 2010, MacLeod et al. 2006, Saha et al. 2000, Wang et al. 2011a), while DJ-1 and PARK2 are protective against apoptosis (Jiang et al. 2004, Junn et al. 2005). Other possible triggers include the presence of ROS, nuclear DNA mutations, accumulation of mitochondrial DNA deletions and mitochondrial dysfunction (Venderova and Park 2012). Alternative methods of programmed cell death may also exist in PD. The same stimulus can trigger multiple cell death pathways, depending on its intensity and duration, brain region, cell type, levels of intracellular calcium as well as the bioenergetic state of the cell (Eguchi et al. 1997, Oppenheim et al. 2001). Autophagic cell death is characterized by the presence of large cytoplasmic vacuoles and expression of molecular markers of autophagy (Venderova and Park 2012), and cell death can be prevented by chemically or genetically inhibiting autophagy (Galluzzi et al. 2012). However, activation of autophagy in a dying cell may not necessarily mean autophagy is the cause of cell death. Autophagy may be employed as a means to increase energy in order to prompt apoptosis. Further, increased autophagic vacuolization may also be a consequence of problems with fusion of autophagosomes with lysosomes and/or with elimination of unwanted cellular components (Venderova and Park 2012). Nevertheless, morphological indications of autophagic cell death alongside apoptosis has been reported in PD

49 (Anglade et al. 1997). Should a cell be unable to sustain the high energetic demands of the apoptotic process, it may switch to necrosis, characterized by rapid bioenergetic failure and loss of membrane integrity (Galluzzi et al. 2007). This results in swelling of the cytoplasm and its organelles, membrane rupture and bursting of the cell, which unlike apoptosis triggers an inflammatory response. Two other types of necrotic cell death exist, namely parthanatos (dependent on activation of poly-(ADP-ribose) polymerase [PARP] in response to DNA strand breaks) and necroptosis (ordered cellular explosion resulting in rapid mitochondrial dysfunction and excessive ROS production) (Venderova and Park 2012). Necroptosis is activated by TNF-α, which has been extensively implicated in PD pathogenesis (Guiney et al. 2017). Ferroptosis is a newly recognized alternative method of programmed cell death that could be playing an important role in PD (Guiney et al. 2017). This iron-dependent cell death pathway involves depletion of intracellular GSH levels (which in turn leads to an increase in the labile iron pool (Hider and Kong 2011, Kaur et al. 2009)) and lipid peroxidation (Yang et al. 2014), with distinct morphological changes, such as shrunken mitochondria, increased mitochondrial membrane density, reduction in or vanishing of cristae and mitochondrial outer membrane rupture (Dixon et al. 2012). Iron is the catalyst for ferroptosis, and increased availability of catalytic iron is a hallmark of PD, likely via nigral iron elevation, GSH depletion, lipid peroxidation and enhanced ROS generation (Guiney et al. 2017). Importantly, agents that inhibit ferroptosis have shown therapeutic potential in PD. Deferiprone treatment in early-stage PD patients displayed slowed progression of motor deficits, reduced existing motor symptoms and increased CSF GSH peroxidase activity (Devos et al. 2014). Furthermore, the GSH synthesis precursor, N- acetylcysteine, improved PD neurodegeneration in a phase II clinical trial (Monti et al. 2016). The fact that multiple cell death pathways may be converging in PD to induce nigral neurodegeneration may account for the numerous cell death pathways evident in the disease. 8.2.11. Animal Models Animal models have proven to be invaluable tools to study PD, both in terms of pharmacological advancements in symptomatic therapies and better understanding of disease pathomechanisms. Two broad categories of animal models exist in PD research: toxin models and genetic models. Toxin models are best suited for testing therapeutic interventions aimed at counteracting motor

50 symptoms of PD. A number of pharmacological and toxic agents have been used over the years to model PD with varying degrees of success and reproducibility (Hamadjida et al. 2019, Le et al. 2014). This includes treatment of rodents, among other model systems, with reserpine, haloperidol, amphetamine-type psychostimulants (e.g. methamphetamine, 3,4- methylenedioxymethamphetamine), inflammogens (e.g. lipopolysaccharide), UPS inhibitors (e.g. lactacystin, epoxomicin) and pesticides/herbicides (e.g. paraquat, maneb) (Cicchetti et al. 2009, Hamadjida et al. 2019, Le et al. 2014). Of the toxin models, the two most common employ the neurotoxins 6-hydroxydopamine (6-OHDA) in rats and MPTP in mice and monkeys (Blesa and Przedborski 2014, Le et al. 2014). 6-OHDA is a selective catecholaminergic neurotoxin that cannot cross the BBB, therefore typically this toxin is injected unilaterally into either the substantia nigra pars compacta, medial forebrain bundle or striatum (Blandini et al. 2008). In the brain, 6-OHDA undergoes auto-oxidation, which generates hydrogen peroxide as well as superoxide and hydroxyl radicals (Hamadjida et al. 2019). As much as 90% dopaminergic neuronal death occurs over a brief time course (12 h to 2-3 days) within the substantia nigra (Przedborski et al. 1995). Further recapitulating the pathological process of PD in humans, injecting 6-OHDA into the striatum results in retrograde degeneration of dopaminergic striatal terminals prior to death of dopaminergic neurons in the nigra (Sauer and Oertel 1994). Motor impairments (rotational behaviour, gait impairments) accompany nigrostriatal dopaminergic neurodegeneration in the 6- OHDA model as well as some non-motor abnormalities (depression, anxiety, gastrointestinal dysfunction), though Lewy body pathology is not observed (Hamadjida et al. 2019). Like 6-OHDA, MPTP is a relatively selective catecholaminergic neurotoxin. Its discovery came in the early 1980s, after a group of young individuals from northern California developed a parkinsonian syndrome following inadvertent intravenous injection of a narcotic meperidine analogue, later identified as MPTP (Langston et al. 1983). At the time, the chemist working with MPTP also developed parkinsonism (Langston and Ballard 1983) and later, likely unrelated though unfortunately coincidental, journalist and author of the book “The Case of the Frozen Addicts” which details this MPTP story, Jon Palfreman, was diagnosed with PD. MPTP can cross the BBB, after which it is converted by MAO-B to its active metabolite, MPP+ (Langston et al. 1983, Le et al. 2014). MPP+ is then taken up by dopaminergic neurons of the substantia nigra via DAT, where it inhibits the

51 mitochondrial electron transport chain complex I activity, resulting in the release of ROS (Langston et al. 1983, Le et al. 2014). Systemic administration of MPTP in nonhuman primates, and to a lesser degree in mice, results in some of the following behavioural phenotypes: changes in locomotor activity, bradykinesia, rigidity, abnormal posture, tremor, motor ‘freezing’, dyskinesia, stereotypy, alterations in REM sleep and cognitive impairment (Le et al. 2014). Pathologically, MPTP primarily causes damage to the nigrostriatal dopaminergic pathway, and minimal evidence of α-synuclein-containing inclusions exists (Blesa and Przedborski 2014). Finally, chronic systemic exposure of rodents to another mitochondrial complex I inhibitor, rotenone, causes many features of PD, including motor abnormalities, nigrostriatal dopaminergic neurodegeneration, intracellular inclusions that resemble Lewy bodies, increased oxidative damage, enhanced iron deposition and microgliosis, though this model has proven difficult to replicate (Le et al. 2014). Overall, neurotoxic models lack the progressive nature of the disease, as the pathological lesion is produced acutely (i.e. hours to days), yet resulting phenotypes often resemble late-stage PD (Blesa and Przedborski 2014, Le et al. 2014). Lesions are primarily if not exclusively dopaminergic, and animals frequently lack the hallmark PD proteinaceous Lewy body inclusions (Blesa and Przedborski 2014, Le et al. 2014). Genetic models of PD include overexpressing wild-type (WT) or mutant (most often A53T) α-synuclein protein, viral vector-mediated overexpression of α-synuclein, stereotactic injection of fibrilized α-synuclein, overexpressing WT or mutant Lrrk2 and knock-out of Parkin, Dj-1 or Pink1, among others. Many of the genetic models involving α-synuclein recapitulate hallmark Lewy body inclusion pathology in the substantia nigra, with varying degrees of dopaminergic neurodegeneration and attendant motor deficits (Le et al. 2014, Visanji et al. 2016). Notably, fibrillar seeding models of α-synuclein show promise, particularly with modeling the progressive nature of sporadic pathology seen in human PD (Polinski et al. 2018). While other TG or knock- out genetic models simulate the molecular mechanisms of genetic forms of PD, their pathological and behavioural phenotypes are often divergent from the human condition (Blesa and Przedborski 2014, Le et al. 2014). Taken together, clearly there is no model (toxin or genetic) that holistically represents the molecular mechanisms, pathophysiology, progressive nature of the disease and preclinical and clinical states of PD (Le et al. 2014). Despite the limitations discussed

52 throughout this section, continued research in animal models of PD is essential for the elucidation of key disease mechanisms and eventual discovery of disease-modifying, not only symptomatic, therapeutics. As discussed in the Introduction (see Section 7), Chapters 1, 2 and 3 of the current dissertation describe a novel transducer model of PD, namely the GFAP.HMOX18.5-19m mouse. 8.3. MicroRNAs MiRNAs control a range of physiological and pathological functions, and altered miRNA profiles have been documented in many neurodegenerative conditions, including PD (Abe and Bonini 2013, Leggio et al. 2017, Nelson et al. 2008). These short, non-coding RNA species post- transcriptionally regulate gene expression by binding to the 3’-UTR of their target messenger RNA (mRNA), thereby resulting in targeted mRNA cleavage (full complementarity) or targeted mRNA degradation and protein translation repression (partial complementarity) (Bartel 2004). Alterations in miRNA profiles observed in disease are caused by either genomic events, such as mutations, deletion amplifications or transcriptional changes, or defects in biogenesis, including mutations or the dysregulation of enzymes that regulate this process (Bartel 2004, Ha and Kim 2014, Lin and Gregory 2015). The biogenesis of miRNAs is a tightly regulated and highly conserved pathway (Bartel 2004, Ha and Kim 2014), beginning with their transcription in the nucleus by RNA polymerase II. Following transcription of the primary miRNA (pri-miRNA) transcript, Drosha and the cofactor protein DiGeorge syndrome chromosomal region 8 (DGCR8) bind to the transcript. Drosha is a type III RNase and mediates the cleavage of the 3’ and 5’ strands of the pri-miRNA, generating the precursor miRNA (pre-miRNA) (Leggio et al. 2017). The exportin-5 complex mediates subsequent translocation of the pre-miRNA from the nucleus into the cytosol. The cytosolic type III RNase, Dicer, and cofactor transactivation response element RNA-binding protein bind the pre-miRNA and cleave the terminal loop, resulting in a miRNA duplex (Leggio et al. 2017). The miRNA duplex is then incorporated into the RNA-induced silencing complex (RISC), where processing of the duplex is mediated by the argonaute (AGO) family of proteins in conjunction with several cofactors. Once unwinding and strand selection takes place, the mature miRNA is capable of mRNA target recognition (Leggio et al. 2017). The first study linking miRNA dysregulation and PD was published in 2007, in which Kim and colleagues showed that specific deletion of Dicer in midbrain dopaminergic neurons is coupled with dopaminergic neuron

53 degeneration and reduced mobility in mice (Kim et al. 2007). Since then, miRNAs have been associated with PD in the context of pathophysiology, regulation of PD-related genes, development of innovative therapeutics and potential biomarkers of the disease (see Section 8.3.1). 8.3.1. MicroRNAs in Parkinson Disease The pioneering work conducted by Kim et al. and later by others suggests that Dicer is essential for midbrain dopaminergic neuron differentiation and maintenance (Chmielarz et al. 2017, Cuellar et al. 2008, Kim et al. 2007, Pang et al. 2014). Furthermore, patients with a specific chromosomal deletion in DGCR8, a gene that encodes the enzyme involved in miRNA biogenesis, showed a higher occurrence of PD in adulthood (Butcher et al. 2013). Post-mortem analysis of patients with this syndrome, called chromosome 22q11.2 deletion syndrome, displayed midbrain dopaminergic neuron loss and Lewy body pathology (Butcher et al. 2013). Several miRNAs have been suggested as potential regulators of α-synuclein at both the transcript and protein level. This includes miR-433 (via fibroblast growth factor 20), miR-16-1 (via Hsp70), miR-34b/c, miR-7 and miR-153 (Doxakis 2010, Kabaria et al. 2015, Wang et al. 2008, Zhang and Cheng 2014). Notably, the 3’-UTR of SNCA is double the length of its coding sequence and contains several post-transcriptional regulatory elements (Leggio et al. 2017). LRRK2 has been found to be regulated by miR-205 and miR-138-2-3p (Cardo et al. 2014, Cho et al. 2013), and mutant LRRK2 contributes to the dysregulation of let-7 and miR-184* initiating cell death pathways in neurons (Gehrke et al. 2010). Other, albeit indirect, targets of miR-34b/c include parkin and DJ-1 (Minones-Moyano et al. 2011), and DJ-1 has also been found to be post- transcriptionally regulated by miR-494 and miR-4639-5p (Chen et al. 2017, Xiong et al. 2014). In addition to targeting PD-related genes, miRNAs have been shown to regulate inflammation, a key pathomechanism involved in PD. In particular, miR-155 upregulates and miR-7 downregulates the inflammatory process likely in response to α-synuclein (Louafi et al. 2010, Prajapati et al. 2015, Thome et al. 2016, Zhou et al. 2016). Various miRNA-based strategies are now being explored as potential disease-modifying treatment avenues for PD, including the use of miRNA mimics or inhibitors via novel delivery modalities as well as employing chemical modifications of endogenous miRNAs (Leggio et al. 2017). While much of the evidence described herein was

54 discovered in experimental models of parkinsonism, some of these miRNA alterations have been confirmed in human post-mortem PD brain (Leggio et al. 2017). Considering post-mortem analyses represent the endpoint of the disease, many studies are now underway to assess miRNA profiles in PD biofluid specimens to reflect disease progression. Circulating miRNAs are known to be abundant, tissue-specific, highly stable and readily quantifiable (Mushtaq et al. 2016), thus serving as potentially useful, non-invasive biomarkers of disease. MiRNAs have been detected in CSF, serum, plasma, saliva and urine of PD patients and analyzed against non-neurological (healthy) and neurological controls (Leggio et al. 2017, Roser et al. 2018). Of note, Botta-Orfila and colleagues identified three significantly reduced miRNAs (miR-19b, miR-29a and miR-29c) in serum of idiopathic and familial (LRRK2 G2019S mutation) PD patients compared to non-neurological controls, a finding that was confirmed in two additional validation sets (Botta-Orfila et al. 2014). Downregulation of miR-19b was similarly observed in serum of idiopathic RBD patients, and was identified as a possible predictor of PD, appearing five years before PD diagnosis (Fernandez-Santiago et al. 2015). The prodromal PD population, including patients with RBD, represents a key demographic to identify novel biomarkers for earlier diagnosis of idiopathic PD. A recently updated list of dysregulated miRNAs in biofluids across PD and other neurodegenerative disorders was published by Juzwik et al. (Juzwik et al. 2019) as well as van den Berg et al. (van den Berg et al. 2020). As an example, the α-synuclein- targeting miRNA, miR-153, was significantly increased in CSF of PD patients, distinguishing PD patients from controls with a sensitivity and specificity of 93% (Gui et al. 2015). It is important to note that when comparing the commonality in miRNA expression profiles between different biofluids of PD patients, only minimal overlap exists (Burgos et al. 2014) suggesting that miRNA changes may be biofluid-specific. Stability of circulating miRNAs is maintained either via binding to AGO proteins (Arroyo et al. 2011, Turchinovich et al. 2013, Wang et al. 2010b) or transport by EVs (Blandford et al. 2018), thus miRNA profiling of biofluid EVs holds considerable promise for PD biomarker development. 8.4. Extracellular Vesicles EVs have emerged as a rich source of potential biomarkers, considering these membranous structures facilitate intercellular transport of DNA, RNA (including miRNAs), proteins and lipids

55 (Margolis and Sadovsky 2019). All cells are capable of releasing EVs, which are highly heterogeneous in size, cargo, membrane composition, biogenesis and biological function (Margolis and Sadovsky 2019). Based on the current knowledge of their biogenesis, EVs can be broadly divided into two main categories, namely exosomes and microvesicles (van Niel et al. 2018). Exosomes (30 – 150 nm in diameter) are intraluminal vesicles formed by the inward budding of the endosomal membrane during maturation of multivesicular endosomes (MVEs), which are intermediates within the endosomal system, and secreted upon fusion of MVEs with the cell surface (van Niel et al. 2018). Microvesicles (50 – 1000 nm in diameter), on the other hand, are generated by the outward budding and fission of the plasma membrane and the subsequent release of vesicles into the extracellular space (van Niel et al. 2018). Other subpopulations proposed include apoptotic bodies, oncosomes, ectosomes and microparticles (Thery et al. 2018). EV composition and type of recipient cell dictate the EV-target cell interaction, which could encompass binding of EVs to surface-exposed receptors or ligands and triggering intracellular signaling cascades, phagocytosis or micropinocytosis or fusion of EVs with the cell membrane (Yanez-Mo et al. 2015). Ultimately, this plays a role in modifying the physiological state of the recipient cell in health and disease (Yanez-Mo et al. 2015). The release of EVs in the extracellular space allows for their recovery from biological fluids, and isolation methods include differential ultracentrifugation, flotation on density gradients, separation by size exclusion chromatography, poly-(ethylene glycol) (PEG) precipitation, immunoprecipitation and commercial kits that are partly based on these methods (van Niel et al. 2018). Combining multiple isolation procedures is encouraged to clearly separate subpopulations based on size, density and composition, also aiding in the elimination of free- floating soluble proteins or protein aggregates, lipoparticles, viruses and cell debris (Thery et al. 2018, van Niel et al. 2018). Furthermore, EV isolation can be cell-type specific, with immunoaffinity techniques allowing for enrichment of neuron-derived EVs via L1 cell adhesion molecule protein (L1CAM) antibodies or astrocyte-derived EVs via glutamate aspartate transporter 1 (GLAST) antibodies (Goetzl et al. 2016, Mustapic et al. 2017, Thery et al. 2018). As such, study of EVs in the context of various central nervous system (CNS) afflictions, including PD,

56 has been extensive (Badhwar and Haqqani 2020, Hornung et al. 2020, Upadhya et al. 2020), both in terms of pathological mechanisms and diagnostic biomarker discovery. 8.4.1. Extracellular Vesicles in Parkinson Disease In the CNS, EVs play an important role in synaptic physiology, neuron-neuron and neuron-glia communication as well as axon damage regeneration (Porro et al. 2019). They can travel across endothelial cells of the BBB via receptor-mediated endocytosis, releasing their contents into biological fluids (Alvarez-Erviti et al. 2011, Porro et al. 2019). Not only is EV release induced and accelerated by oxidative stress, but EV cargo (e.g. TNF-α) can also contribute to the exacerbation of oxidative stress levels within cells (Cai et al. 2018, Chen et al. 2016). Intriguingly, neural-derived blood EVs from pre-clinical AD (up to 10 years before diagnosis) display differences in lysosomal proteins, suggesting early insult to the autophagy-lysosome pathway in neurodegenerative disease pathogenesis (Goetzl et al. 2015). In certain neurodegenerative conditions, EVs have been reported to sequester and spread pathogenic proteins, such as α-synuclein, amyloid precursor protein, phosphorylated tau and prions (Coleman et al. 2012, Emmanouilidou et al. 2010, Rajendran et al. 2006, Saman et al. 2012, Trotta et al. 2018). Germane to PD, uptake of EV- containing α-synuclein oligomers contributes to seeding aggregation pathology, dopaminergic neurodegeneration, glial cell activation, neuroinflammation and cytotoxicity (Danzer et al. 2012, Desplats et al. 2009, Grey et al. 2015, Russo et al. 2012). In fact, vesicular α-synuclein is more prone to aggregation than cytosolic α-synuclein (Lee et al. 2014), perhaps lending further support to the spreading hypothesis of PD (see Section 8.2.10iii). Neuroinflammation, as seen in PD, may also be modulated by EVs carrying miRNAs targeting inflammatory mediators (Paschon et al. 2016). Finally, several PD-related genes have been linked to EV biology, namely LRRK2, VPS35, ATP13A2, PARK2 and GBA (Porro et al. 2019, Tofaris 2017). A number of studies have evaluated EVs as potential biomarkers of PD. In a large case- control sample cohort, L1CAM-enriched EVs from plasma contained significantly higher levels of α-synuclein and tau among PD patients compared to controls, an effect that was also associated with disease severity and duration (Shi et al. 2016, Shi et al. 2014). In another study conducted by Cao et al., salivary EV levels of oligomeric α-synuclein and oligomeric to total α-synuclein ratios were significantly elevated in PD patients compared to healthy controls (Cao et al. 2019). Beyond

57 α-synuclein and tau, other EV cargo may be used for biomarker development in PD research, including increased serine phosphorylated LRRK2, syntenin 1 (involved in EV release) and DJ-1 in addition to changes in miRNA profiles (Tofaris 2017, Wu et al. 2017). Further, a recent pilot study reported that the number of L1CAM-enriched EVs (neuron derived) isolated from saliva was significantly greater in PD subjects compared to healthy controls (Rani et al. 2019). Gui and colleagues isolated EVs from CSF of PD patients and found 16 upregulated and 11 downregulated miRNAs (Gui et al. 2015). Among those upregulated miRNAs was miR-153, previously identified as targeting α-synuclein (Gui et al. 2015). Additional studies have similarly reported altered miRNA expression levels in biofluid EVs from PD patients (Cao et al. 2017, Cardo et al. 2013, Patil et al. 2019), highlighting the potential usefulness of combinatory methods of altered miRNA, and even protein, signatures. For instance, Dos Santos and colleagues identified a panel of altered miRNAs in CSF EVs from PD patients compared to healthy controls, a model that was proven even more robust when combining these miRNA profiles with changes in PD-related proteins (e.g. DJ- 1, UCH-L1, α-synuclein) (Dos Santos et al. 2018). Despite enormous biomarker, and even therapeutic, potential, the field of EV research is limited by inconsistencies in isolation techniques and irreproducibility among research groups (Margolis and Sadovsky 2019, Thery et al. 2018). The development and widespread deployment of effective technologies that allow better EV isolation, size characterization, elimination of potential contaminants and definition of cargo composition will help to address these limitations (Margolis and Sadovsky 2019). 8.5. Heme Oxygenase-1 What is clear from each of the sections outlined above is that PD involves a complex interplay of diverse pathological and molecular mechanisms. Over the past two decades, the Schipper laboratory has adduced considerable evidence that unites core features of PD pathophysiology into a single neuropathological ‘lesion’ (Schipper et al. 2019). This lesion entails self-reinforcing positive feedback loops ensuring that the advent of one component obligates the appearance of others, thereby driving the degenerative process long after initiating insults may have dissipated (Schipper 2004a, Schipper et al. 2019). The core neuropathological features include: i) oxidative stress and associated protein, lipid and nucleic acid modifications; (ii) excessive deposition of non-transferrin bound iron; iii) mitochondrial membrane damage and bioenergetic failure; and

58 iv) macroautophagy (including mitophagy) in the affected neural tissues (Schipper et al. 2019). The pivotal transducer of noxious stimuli into precisely this core cytopathological signature involves the sustained upregulation of a key stress protein in astrocytes of the aging and diseased CNS, namely HO-1. The following sections contain material that has been directly quoted from a previously published review (Schipper et al. 2019), with consent from all other co-authors. 8.5.1. Regulation and Physiology HO (E.C. 1:14:99:3; heme-hydrogen donor:oxygen oxidoreductase) is remarkably conserved from algae to humans, and was first described in 1968 by Tenhunen and colleagues as the mechanism of heme catabolism (Tenhunen et al. 1968). “The HOs localize primarily to the endoplasmic reticulum where they serve, in concert with NADPH cytochrome P450 reductase, to cleave heme to biliverdin, carbon monoxide (CO) and free ferrous iron (Fig. 1). Biliverdin is further metabolized by biliverdin reductase to the bile pigment, bilirubin (Ryter and Tyrrell 2000). Two isoforms of HO have been identified in mammalian cells, HO-1 (a.k.a. Hsp32) and HO-2. A third member, HO-3, was shown to be a pseudogene specific to rats (Scapagnini et al. 2002). HO-1 and HO-2 exhibit 43% amino acid sequence homology in humans and differ with respect to regulation, molecular weight, electrophoretic mobility, tissue distribution and antigenicity. Despite these differences, the isozymes exhibit identical cofactor and substrate specificities (Dennery 2000, Loboda et al. 2008). Unlike HO-2, HO-1 contains a destabilizing carboxy terminus PEST (proline-glutamic acid- serine-threonine) sequence that renders the protein sensitive to rapid degradation. HO-1 mRNA and protein have half-lives of approximately 3 hours and 15-21 hours, respectively (Dennery 2000).” Due to its highly inducible nature and specific involvement in disease, the remainder of Section 8.5 will focus on HO-1.

Figure 1. Heme degradation pathway. CO, carbon monoxide; CYTP450R, cytochrome P450 reductase; Fe2+, ferrous iron.

59 “HMOX1 in humans localizes to chromosome 22q12 and contains four introns and five exons. The regulatory portion of the mammalian Hmox1 gene includes a 500-bp promoter, a proximal enhancer and at least two distal enhancers. Diverse elements in its regulatory region render Hmox1 dynamically responsive to a plethora of oxidative and inflammatory stimuli including heme, dopamine, β-amyloid, hydrogen peroxide, helper T cell cytokines, heavy metals, ultraviolet light, hyperoxia, prostaglandins, nitric oxide, peroxynitrite, lipopolysaccharide, oxidized lipid products and various growth factors (Dennery 2000, Kinobe et al. 2006, Loboda et al. 2008, Schipper 2000).” “The expression of mammalian Hmox1 is controlled by numerous transcription factors, with species-specific predominance of one or several signaling pathways. In stressed neural tissues, Hmox1 induction is heavily potentiated by nuclear factor erythroid 2- related factor 2 (Nrf2) transcription factor binding to Maf response elements (MARE), whereas repression of the gene is largely effected by the heme-regulated protein, bric-a-brac-tramtrack- broad complex (BTB) and cap’n’collar (CNC) homology 1 (Bach1) (Kitamuro et al. 2003, Ogawa 2002, Sun et al. 2002, Suzuki et al. 2003). Further, the disabling of Kelch-like enoyl CoA hydratase (ECH)-associated protein 1 (Keap1) under oxidative stress permits cellular Nrf2 protein levels to accumulate and bind to MAREs for transactivation of Hmox1 (Canning et al. 2015, Kitamuro et al. 2003, Loboda et al. 2016).” “In humans, polymorphisms in the lengths of GT sequences (from 11-40) within the HMOX1 promoter impact the magnitude of HO-1 expression profiles. Long GT repeats code for less stable (Z-conformational) DNA with blunted transcriptional activity resulting in lower resting and stimulated HO-1 protein levels. Short-GT polymorphisms are associated with robust HO-1 activity, enhanced protection against atherosclerosis-associated conditions (e.g coronary artery disease) and HIV-induced CNS neuroinflammation as well as increased aggressiveness of malignant neoplasms (Exner et al. 2004, Gill et al. 2018, Jozkowicz et al. 2007, Loboda et al. 2008).” “Heme metabolism occurs in all mammalian cells.” “Oxidative stress may transiently increase the intracellular pool of free heme by facilitating the release of loosely-bound heme or by altering the conformation, and facilitating the degradation of hemoproteins such as respiratory burst enzymes, myoglobin, cytochromes and various peroxidases (Loboda et al. 2008,

60 Ryter and Tyrrell 2000). In stressed cells, HO-1 upregulation may confer protection by accelerating the conversion of pro-oxidant heme to biliverdin and bilirubin, bile pigments with substantial radical-scavenging capacities (Baranano and Snyder 2001, Dore et al. 1999, Llesuy and Tomaro 1994, Nakagami et al. 1993, Stocker et al. 1987).” “Under certain circumstances, however, iron and CO liberated by heme cleavage may augment oxidative tissue injury by enhancing the formation of ROS within mitochondria and other subcellular organelles (Desmard et al. 2007, Frankel et al. 2000, Ryter and Tyrrell 2000, Zhang and Piantadosi 1992). The magnitude and duration of Hmox1 induction and the chemistry of the redox micro-niche may determine whether HO-1 behaves as an antioxidant or pro-oxidant in any given condition (Galbraith 1999, Suttner and Dennery 1999).” This highlights the Janus-faced nature of HO-1, with both beneficial and detrimental effects as evidenced in the following sections. 8.5.2. Involvement in Neurological Conditions “In light of the remarkable responsiveness of HMOX1 to oxidative stress, one could safely surmise that highly variable patterns of neural HO-1 mRNA and protein expression would be encountered in the broad spectrum of adult and paediatric brain disorders featuring local or systemic perturbations of redox homeostasis (Schipper 2004c).” i. Central Nervous System Aging: “Numbers of neuroglia immune-positive for HO-1 have been reported to progressively increase in the normal human brain between the ages of 3 and 84 (Hirose et al. 2003). An initial study of the mature human brain revealed moderate-to-robust HO-1 immunoreactivity in dopaminergic neurons of the substantia nigra, choroid plexus epithelial cells, ependymal cells, the cerebrovascular endothelium and within glial and extracellular corpora amylacea (Schipper 2004b). Subsequent surveys revealed prominent HO-1 immunostaining in olfactory neuroepithelium of normal elderly human subjects and progressive upregulation of HMOX1 between the 2nd and 7th decades of life in human photoreceptors, retinal ganglion cells, optic nerve and astrocytes (Mydlarski et al. 2003, Perry et al. 2003). These patterns of HO-1 expression may serve as molecular markers of human CNS loci that are particularly prone to oxidative stress during normal aging.” ii. Schizophrenia: Schizophrenia is a hyperdopaminergic neurodevelopmental condition that afflicts approximately 1% of the population world-wide, and primarily involves disordered

61 thought, affect and behaviour. The disease is characterized neuropathologically by altered regional brain volumes and cytoarchitectonics, ventriculomegaly, oxidative substrate modifications, mitochondrial damage (bioenergetic failure), macroautophagy, suppressed brain reelin and GAD67 expression and dysregulation of other genes and miRNAs implicated in neuronal proliferation, migration and differentiation (Bakhshi and Chance 2015, Schipper et al. 2019). During gestation and in the early postnatal period, a number of stressors have been identified as risk factors or triggers of human neurodevelopmental illnesses, such as schizophrenia, autism and attention deficit-hyperactivity disorder (Brown 2011). Many of these stressors (e.g. anoxia-ischemia, pro-inflammatory cytokines, dopamine) are also associated with HMOX1 induction (Mehindate et al. 2001, Schipper 2004b, Schipper et al. 1999), which is enhanced in prefrontal cortex of patients with schizophrenia and associated with perturbed redox homeostasis and mitochondrial dysfunction in this brain region (Prabakaran et al. 2004). A genome-wide methylation analysis of DNA extracted from peripheral blood samples revealed that significant hypomethylation of the HMOX1 promoter in schizophrenia patients, potentially contributing to HO-1 overexpression in this disease (Rukova et al. 2014, Schipper et al. 2019). Intriguingly and in contradistinction to parkinsonian GFAP.HMOX18.5-19m mice alluded to earlier (see Section 8.2.11), shifting the window of astroglial HMOX1 transgene expression in GFAP.HMOX1 mice from embryogenesis until 12 months, results in a neurodevelopmental phenotype (Song et al. 2012a, Song et al. 2012b). Akin to human schizophrenia and other animal models of the disease, the GFAP.HMOX10-12m mice exhibit: (i) dysgenesis of the hippocampal dentate gyrus; (ii) impaired prepulse inhibition of the startle response in the males, hyperlocomotion and stereotypy; (iii) deficient neurovascular coupling; (iv) elevated basal ganglia concentrations of dopamine and its metabolites, DOPAC and HVA, and elevated serotonin and its metabolite, 5-hydroxyindoleacetic acid, which explain the behavioural hyperkinesia; (v) induction of nuclear receptor related-1 protein (Nurr1) and pituitary homeobox 3 (Pitx3) mRNA and protein, transcription factors that promote dopaminergic neuron differentiation and maintenance, with downregulation of their targeting miR-133b and miR-145; (vi) increased TH and DAT gene expression, which mediate the hyperdopaminergia; (vii) diminished D1-receptor binding in nucleus accumbens; and (viii) downregulation of neuronal reelin and GAD67, which

62 may contribute to deviant neuronal migration and synaptic plasticity in human schizophrenia (Schipper et al. 2019, Song et al. 2012a). Importantly, treatment of GFAP.HMOX10-12m mice with a cysteine-rich whey protein isolate Immunocal®, acting as a precursor of GSH, rescues many behavioural, pathological and biochemical deficits observed in these mice (Song et al. 2017b). iii. Stroke: Brain ischemia, also known as stroke, occurs when there is an insufficient amount of blood flow to the brain, resulting in cerebral hypoxia. “In 2000, Beschorner and co- workers published on cerebral HO-1 expression profiles in persons succumbing at different time intervals to closed traumatic brain injury or focal ischemic infarction (Beschorner et al. 2000). Within the first 24 hours of the stroke, HO-1 immunoreactivity in the peri-infarct zones primarily implicated the astrocytic population, became steadily more prominent over the ensuing few weeks and declined to levels approaching baseline after several months. Microglial/macrophage HO-1 expression was typically minimal in regions of bland infarction, but was more intense in the vicinity of associated hemorrhage. Weak-to-intermediate HO-1 staining of scattered neurons and endothelial cells was observed for a few months post-infarction. Both Beschorner’s group and Orihara and co-workers (Orihara et al. 2003) reported that in brain trauma specimens, HMOX1 induction occurs early, is robust and long-lived in microglia/macrophages, with milder expression of the gene in neurons, astroglia and endothelial cells.” Similarly, robust neuroprotection and survival of GFAP.HMOX1 TG mice acutely overexpressing HO-1 in astrocytes was shown in two models of acute intracerebral hemorrhage (Chen-Roetling et al. 2017, Chen-Roetling et al. 2015). Although heme-derived bilirubin may confer acute cytoprotection, as seen in patients with stroke and CNS trauma, other products of the HO-1 reaction may contribute to longer-term mismanagement of brain iron homeostasis and neurometabolic failure, as conceptualized for the aging-related neurodegenerations (Schipper et al. 2019). vi. Multiple Sclerosis: “Multiple sclerosis (MS) is an immune-mediated disease of the human CNS with a pathological signature featuring immunocyte infiltration, altered cytokine production, oligodendroglial degeneration, astrogliosis, microglial activation, multifocal demyelination and axonal degeneration (Schipper 2004b). Excessive neural iron accumulation and oxidative stress have been documented in MS and a rodent model of the disease, experimental autoimmune encephalomyelitis (Lassmann and van Horssen 2016, LeVine and

63 Chakrabarty 2004). In 2001, the Schipper laboratory reported that proportions of glial fibrillary acidic protein (GFAP)-positive astrocytes immunoreactive for HO-1 were significantly increased in spinal cord plaques from post-mortem MS patients relative to normal spinal white matter (Mehindate et al. 2001), a finding subsequently corroborated by others (van Horssen et al. 2008). The enhanced elaboration of proinflammatory cytokines, such as IL-1b and TNF-a (Mehindate et al. 2001), or MS-related proteins, such as myelin basic protein (Businaro et al. 2002), may be responsible for HMOX1 induction in MS tissues. In addition, expression of Nrf2, a positive regulator of HMOX1, is markedly increased in MS tissues and localizes to glial cells and oxidative substrate damage in areas of active demyelination (Licht-Mayer et al. 2015, van Horssen et al. 2010).” “In 2007, Stahnke et al. (Stahnke et al. 2007) reported upregulation of HO-1 protein in oligodendrocytes within early MS lesions and in microglia, macrophages and astrocytes in acute disseminated encephalomyelitis. Finally, as further evidence for a deleterious role of HO-1 in MS, suppression of HO activity was shown to ameliorate neural oxidative stress and locomotor impairment in mice with experimental autoimmune encephalomyelitis (Chakrabarty et al. 2003).” v. Alzheimer disease: “AD is a degenerative dementia featuring unrelenting neuronal loss, reactive astro- and microgliosis and the deposition of neurofibrillary tangles (containing hyperphosphorylated tau), senile plaques (consisting of β-amyloid) and corpora amylacea in the basal forebrain, hippocampus and associated cortices (Selkoe 1991). Pathological iron deposition, oxidative substrate modifications, mitochondrial deficits and mitophagy (the ‘core’ features) have been consistently implicated in the pathogenesis of this illness (Beal 1995, Mattson 2002, Reichmann and Riederer 1994). In both AD and PD, non-neuronal (glial and endothelial) cellular compartments exhibit pathological iron deposition and enhanced production of ferritin, the major intracellular iron storage protein (Schipper 1998). Increased glial iron was also evident in preclinical AD and mild cognitive impairment (MCI) patients, a frequent harbinger of impending Alzheimer dementia (Smith et al. 2010). The transferrin route of iron mobilization utilized by most systemic tissues contributes minimally to the aberrant sequestration of brain iron in these neurodegenerative states as densities of transferrin binding sites are unaltered or vary inversely with levels of stored iron in the affected regions (Schipper 1999). The latter realization prompted

64 several groups to investigate alternative mechanisms for aberrant iron sequestration in the aging and degenerating CNS, including potential participation of melanotransferrin (p97), lactoferrin (Jefferies et al. 1996, Schipper 1999, Schipper 1998) and HO-1. In the AD brain, immunoreactive HO-1 protein is detectable in neurons, astrocytes, choroid plexus epithelial cells, ependymocytes, some vascular endothelial and smooth muscle cells, senile plaques, neurofibrillary tangles and corpora amylacea (Schipper et al. 1995, Smith et al. 1994). 86% of GFAP-positive astroglia in AD hippocampi were immunolabeled for HO-1, whereas the fraction of hippocampal astrocytes expressing HO-1 in age-matched, cognitively- normal subjects was only 6-7%. Similarly, immunoblots of protein extracts obtained from AD hippocampus and temporal cortex revealed HO-1 bands which were approximately 4-fold more intense than those seen in normal brains (Schipper et al. 1995). Butterfield and colleagues also reported increased expression of HO-1 in the inferior parietal lobe of AD patients (Calabrese et al. 2006). Induction of the HMOX1 gene occurs relatively early in the natural history of AD as evidenced by the near-maximal overexpression of glial HO-1 protein documented in persons afflicted with MCI (Schipper et al. 2006). Oxidative stress, accruing from the production of pro- inflammatory cytokines (Mehindate et al. 2001) or from the pathological amyloid burden (Butterfield and Boyd-Kimball 2018, Butterfield et al. 2002, Ham and Schipper 2000), may trigger the upregulation of HO-1 in the AD hippocampi and cerebral cortices.” HO-1 protein or mRNA levels were noted to be suppressed in AD choroid plexus epithelium, CSF, plasma and blood mononuclear cells compared to control values (Anthony et al. 2003, Schipper et al. 2000). The decreased CSF HO-1 levels in AD may reflect diminished synthesis and secretion of the protein by the choroid plexus or impaired transudation of HO-1 from the peripheral circulation.” “In AD and some MCI samples, but not in the control specimens, HO-1 levels correlated significantly with increased cholesterol precursors, decreased total cholesterol and increased oxysterol concentrations (Hascalovici et al. 2009).” “Daily intraperitoneal injections of the APPswe/PS1ΔE9 TG mouse model of AD with OB- 28 (15 mg/kg), an azole-based, brain-permeable and selective inhibitor of HO-1, from 3 to 10 months of age suppressed HO-1 activity in the cerebral cortex and hippocampus with no overt adverse effects (Gupta et al. 2014). Relative to saline-injected controls, TG mice treated with OB-

65 28 showed reduced neuroinflammation (monitored by astroglial activation) without any alteration in the degree of brain amyloid deposition. Moreover, performance on a complex maze learning task was substantially superior in TG mice receiving OB-28 relative to the saline-treated TG controls (Gupta et al. 2014). These observations provide proof-of-concept that targeted blockade of neural HO-1 activity may mitigate neuroinflammatory reactions and behavioural deficits in a rodent model of AD independently of brain amyloid burden. Germane to this study, Hui et al. previously reported that hyper-phosphorylation of tau, a hallmark process in the natural history of AD, is augmented in an iron-dependent fashion in the CNS of mice over-expressing HO- 1 driven by the β-actin promoter (Hui et al. 2011).” Whether HO-1 inhibitors, like OB-28, have similar neuroprotective effects in other animal models of neurodegeneration (e.g. PD) remains to be tested. 8.5.3. Involvement in Parkinson Disease “In a human neuropathological survey, neuromelanin-containing (dopaminergic), but rarely other, neurons of the normal substantia nigra pars compacta exhibited moderate HO-1 immunoreactivity (Schipper et al. 1998). HMOX1 induction in these cells is commensurate with the fact that, during normal aging, nigral dopaminergic neurons are subjected to elevated levels of ROS arising from the iron-catalyzed oxidation and enzymatic deamination of dopamine (Stokes et al. 1999). Cytoplasmic Lewy bodies within affected dopaminergic neurons of the PD substantia nigra exhibited prominent HO-1 immunoreactivity (Castellani et al. 1996, Schipper et al. 1998). Moreover, 77% of GFAP-positive astrocytes in the PD substantia nigra were immunoreactive for HO-1, whereas the glial fraction expressing HO-1 in the age-matched control specimens was a mere 19% (Schipper et al. 1998). In both the PD and control preparations, proportions of GFAP- positive astroglia co-expressing HO-1 in other salient extrapyramidal territories, such as the striatum, globus pallidus, were relatively low (Schipper et al. 1998). Plausible inducers of HMOX1 in astrocytes of the PD substantia nigra, as described in Section 8.5.1, include environmental or endogenous MPTP-like neurotoxins, dopamine-derived ROS and proinflammatory cytokines (Mehindate et al. 2001, Schipper 1999). In turn, the resulting local enhancement of HO-1 activity may exacerbate many of the disparate features (e.g. the non-transferrin iron deposition, mitochondrial complex I deficits and neuroinflammation) documented in the PD basal ganglia

66 (Beal 1996, Schipper 2001b).” The local uptick in glial HO-1 activity seen in PD may accelerate the deposition of non-transferrin iron and mitochondrial complex I deficits documented in PD- affected neural tissues (Schipper 2001a). This glial mitochondrial iron mediates the oxidation of dopamine to neurotoxic o-quinone radicals (Schipper 2001a), and oxidizes the pro-neurotoxin, MPTP, to the dopamine neurotoxin, MPP+ (Di Monte et al. 1995). Relating further to PD pathology, “HMOX1 transfection of human M17 neuroblastoma was shown to stimulate proteasomal catabolism of WT a-synuclein (Song et al. 2009), but had no effect on proteasomal degradation of A30P α-synuclein, a mutant protein implicated in familial autosomal-dominant PD (Polymeropoulos et al. 1997). Insofar as non-digestible α- synuclein aggregates are cytotoxic (Volles and Lansbury 2002), the imperviousness of A30P a- synuclein protein to HO-1-directed proteolysis may contribute to Lewy body formation and parkinsonism in persons with this mutation (Song et al. 2009).” Furthermore, dopaminergic-like PC12 neurons grown in co-culture with HMOX1-transfected primary astrocytes are significantly more vulnerable to dopamine- and hydrogen peroxide-mediated cell death than PC12 cells grown atop control astrocytes (Song et al. 2007). Moreover, core cytopathology implicated in PD (oxidative stress, mitochondrial damage and macroautophagy) is abrogated in HMOX1- transfected primary astrocytes treated with the competitive HO inhibitor, tin mesoporphyrin (Zukor et al. 2009). Our glia-centric focus on HO-1 expression is pivotal to our group’s longstanding perspective on mechanisms of neurodegeneration in parkinsonian brain. This approach is based on the following observations: 1) HO-1 is significantly upregulated in astrocytes, not neurons, of PD substantia nigra relative to normal, age-matched controls (Schipper et al. 1998). 2) The excess iron reported in PD brain largely implicates glial cells (Schipper et al. 2019). 3) Hmox1 induction by stressors implicated in PD (e.g. dopamine, MPTP-like xenobiotics, heavy metals) is a common pathway leading to iron-mediated dysfunction in aging astroglia (Schipper et al. 2019). 4) Progressive accumulation of glial mitochondrial iron within subcortical brain regions enhances the vulnerability of nearby dopaminergic neurons to oxidative injury and may render the senescent CNS prone to PD (Schipper et al. 2019).

67 While the association of GT repeat lengths in the HMOX1 promoter with PD appears to be minimal or nil (Funke et al. 2009, Kimpara et al. 1997), a number of other reports have linked polymorphisms in HMOX1 to the disease. One such study disclosed a strong association between rs2071746 (A/T), a single nucleotide polymorphism that enhances HMOX1 promoter activity/transcription, and clinical idiopathic PD (Ayuso et al. 2014). Another group found a synergistic association of HMOX1 rs2077146TT polymorphism with pesticide exposure, specifically increasing the risk for PD (Infante et al. 2011). Finally, several polymorphisms in the promotor region of NRF2 and the Nrf2 binding region of the microtubule-associated protein tau (MAPT) promoter, known transcriptional activator of HMOX1, have been associated with PD (Ran et al. 2017, Wang et al. 2016). Unlike AD (see Section 8.5.2v), no differences were observed in HO-1 protein/mRNA levels in plasma and mononuclear cells of PD patients relative to normal, age-matched controls (Schipper et al. 2000). “In 2010, Mateo and colleagues reported elevated serum HO-1 concentrations in PD, but not in AD, further underscoring disparities of systemic HO-1 behaviour between these conditions (Mateo et al. 2010). In a recent study, we queried whether immunoreactive HO-1 protein is detectable in human saliva, and whether salivary HO-1 concentrations are altered in idiopathic PD (Song et al. 2018). We found that (i) mean HO-1 protein concentrations were significantly higher in saliva of PD patients relative to control values, (ii) that salivary HO-1 levels did not vary with sex, age, exposure to L-DOPA or equivalents or comorbidities and (iii) that patients with early (H&Y stage 1) PD exhibited significantly higher mean salivary HO-1 concentrations than control subjects and PD patients with more advanced disease (H&Y stages 2-3) (Song et al. 2018). It is unclear whether salivary HO-1 originates as a transudate from plasma or is actively secreted by the salivary glands. In support of the latter, immunoreactive HO-1 has been demonstrated in normal salivary gland acini and duct epithelia and in benign salivary gland pleomorphic adenomas (Fan et al. 2011).” “Salivary changes in HO- 1 concentrations may also be associated mechanistically with the prominent autonomic innervation of the salivary glands and the relatively early appearance of Lewy pathology in the PD autonomic nervous system (Del Tredici et al. 2010, Devic et al. 2011, Roberts and Brown 2015).” “A salivary neurodiagnostic confers advantages over other biofluids and neuroimaging

68 modalities because its collection is non-invasive, inexpensive and does not require advanced training of personnel (Wang et al. 2015b).” Easily quantifiable biomarkers for early and accurate diagnosis and novel therapeutic strategies that stop or slow disease progression are sorely lacking in the management of PD; in this regard, the current dissertation aims at elucidating the diagnostic and therapeutic potential of HO-1.

69 9. Specific Aims The four Aims of the current doctoral dissertation used complimentary and translational experimental designs, advancing from mice to humans, to test the following hypotheses that stem directly from our laboratory’s prior work on the role of heme oxygenase-1 (HO-1) in aging and parkinsonian neural tissues: 1. Hypothesis 1: Overexpression of HMOX1 from mid-to-late life in the GFAP.HMOX18.5- 19m mouse model recapitulates behavioural, pathological and biochemical features of Parkinson disease (PD). 2. Hypothesis 2: Altered microRNA (miRNA) profiles contribute to dysregulation of hallmark pathological pathways in GFAP.HMOX18.5-19m mice. 3. Hypothesis 3: Salivary miR-153 and miR-223 expression levels are potential diagnostic biomarkers of human PD relative to non-neurological (healthy) controls. 4. Hypothesis 4: HO-1 is transported from the central nervous system (CNS) to peripheral biofluids in human via extracellular vesicles (EVs) and, more specifically, in CNS- derived EVs.

70 10. Chapter 1: Parkinsonian Features in Aging GFAP.HMOX1 Transgenic Mice Overexpressing Human HO-1 in the Astroglial Compartment

Published in Neurobiology of Aging (2017).

Author List: Wei Song1*, Marisa Cressatti1,2*, Hillel Zukor1,2, Adrienne Liberman1, Carmela Galindez1, and Hyman M. Schipper1,2,3 *These authors contributed equally to this work.

1Bloomfield Centre for Research in Aging, Lady Davis Institute, Jewish General Hospital, Montreal, Quebec H3T 1E2, Canada 2Department of Neurology and Neurosurgery 3Department of Medicine, McGill University Montreal, Quebec H3G 1Y6, Canada

Correspondence should be addressed to Hyman Schipper, Lady Davis Institute, Jewish General Hospital, 3755 Cote Sainte-Catherine Road, Montreal, Quebec H3T 1E2, Canada. E-mail: [email protected].

Short Title: HO-1 and Parkinson disease

71 10.1. Chapter 1 Abstract Epigenetic influences mediating brain iron deposition, oxidative mitochondrial injury and macroautophagy in Parkinson disease (PD) and related conditions remain enigmatic. Here, we show that selective overexpression of the stress protein, heme oxygenase-1 (HO-1) in astrocytes of GFAP.HMOX1 transgenic mice between 8.5 and 19 months of age results in nigrostriatal hypodopaminergia associated with locomotor incoordination and stereotypy; downregulation of TH, DAT, LMX1b, Nurr1, Pitx3 and DJ-1 mRNA and/or protein; overproduction of a-synuclein and ubiquitin; oxidative stress; basal ganglia siderosis; mitochondrial damage/mitophagy; and augmented GABAergic systems (increased GABA, GAD67 and reelin). The neurophenotype of these GFAP.HMOX18.5-19m mice is highly consistent with parkinsonism and differs dramatically from the schizophrenia-like features previously documented in younger GFAP.HMOX10-12m mice. Common stressors may elicit either early-onset developmental (schizophrenia) or later-life degenerative (PD) brain disorders depending on whether the glial HO-1 response is engaged prior to or following the maturation of dopaminergic circuitry. Curtailment of glial HO-1 transduction at strategic points of the life course may confer neuroprotection in human degenerative and developmental CNS disorders.

Keywords: Astrocyte, dopamine, heme oxygenase-1, mitochondrial dysfunction, oxidative stress, Parkinson disease, a-synuclein.

72 10.2. Chapter 1 Introduction Idiopathic Parkinson disease (PD) is a movement disorder of uncertain etiology that afflicts 1-2% of the population over 65 years of age. Although symptomatic pharmacotherapy is available, there currently exists no treatment that unequivocally attenuates neuronal attrition and clinical decline in this condition. PD is characterized pathologically by progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta, formation of a-synuclein- and ubiquitin-containing fibrillar inclusions (Lewy bodies) in this cell population and variable changes in other neurotransmitter systems (Kalia and Lang 2015). In addition to these defining features, PD shares with other human neurodegenerative disorders a set of ‘core’ neuropathological mechanisms which may drive disease progression irrespective of etiology and potentially be amenable to therapeutic intervention. In PD, Alzheimer disease and other aging-related CNS disorders, excessive brain iron deposition (siderosis), oxidative stress, mitochondrial insufficiency (bioenergetic failure) and mitophagy (macroautophagy) may constitute a generic neuropathological ‘lesion’ which may propel the degenerative process forward long after initiating insults have relented (Schipper 2004). Our laboratory has adduced considerable evidence that the establishment of this ‘core’ pathology is contingent on the astrocytic overexpression of heme oxygenase-1 (HO-1) in the affected neural tissues (Schipper 2004, Schipper and Song 2015). Heme degradation in humans and other mammals is mediated by inducible HO-1 (a.k.a. HSP32) and constitutively-expressed HO-2. In brain and other tissues, these enzymes reside within the endoplasmic reticulum where they act, in concert with NADPH cytochrome P450 reductase, to oxidize heme to biliverdin, free ferrous iron and carbon monoxide (CO). Biliverdin is catabolized further to the bile pigment, bilirubin by biliverdin reductase (Ryter and Tyrrell 2000). The Hmox1 promoter contains numerous response elements which render the gene exquisitely sensitive to induction by dopamine (DA), MPTP-like xenobiotics, IL-1β, TNFα, hydrogen peroxide, heavy metals (factors implicated in the pathophysiology of PD) as well as heme, β-amyloid, lipopolysaccharide, hyperoxia and ultraviolet light (Schipper and Song 2015). The acute up-regulation of HO-1 may confer cytoprotection by accelerating the breakdown of pro-oxidant heme to the radical-scavenging bile pigments, biliverdin and bilirubin (Dore et al.

73 1999, Llesuy and Tomaro 1994, Nakagami et al. 1993, Stocker et al. 1987) and there is ample literature on HO-1-mediated neuroprotection in rodent models of ischemic and hemorrhagic stroke, spinal cord injury and excitotoxicity (Ahmad et al. 2006, Benvenisti-Zarom and Regan 2007, Fukuda et al. 1996, Huang et al. 2005, Lin et al. 2007, Panahian et al. 1999). In developmental and degenerative CNS conditions, on the other hand, the sustained liberation of heme-derived iron and CO accruing from the chronic over-production of neural HO-1 may exacerbate intracellular oxidative damage in mitochondria and other subcellular compartments (Frankel et al. 2000, Piantadosi et al. 2006, Ryter and Tyrrell 2000, Schipper et al. 2009). In chemically stressed or HMOX1-transfected astroglia (Schipper and Song 2015, Zukor et al. 2009), and in conditional GFAP.HMOX1 transgenic mice overexpressing human HO-1 in astrocytes (Song et al. 2012a, Song et al. 2012b), heme degradation products promote mitochondrial sequestration of non-transferrin iron, oxidative substrate modifications within this organelle and robust mitophagy. Moreover, these gliodystrophic changes significantly enhance the susceptibility of nearby neuronal elements to free radical injury (Schipper and Song 2015, Song et al. 2012a, Zukor et al. 2009). In the current study, GFAP.HMOX1 mice were manipulated to selectively express the HMOX1 transgene in astrocytes between 8.5 and 19 months of age, thereby simulating the age range of onset of PD and other human neurodegenerative conditions. In striking contradistinction to the schizophrenia-like features documented in younger GFAP.HMOX10-12m mice (Song et al. 2012a), GFAP.HMOX18.5-19m mice exhibit locomotor incoordination, nigrostriatal hypodopaminergia, evidence of early a-synucleinopathy, basal ganglia siderosis, mitochondrial damage/mitophagy and other abnormalities consistent with parkinsonism. 10.3. Chapter 1 Materials and Methods Animal Husbandry All animal studies adhered to the policies and guidelines for the Animal Care Program of McGill University certified by the Canadian Council on Animal Care (CCAC) and the US National Institutes of Health (NIH) Public Health Service (PHS), and were approved by the McGill University Institutional Animal Care and Use Committee (Protocol Number: 2001-2739). Mice were housed 3-5 per cage with 12 h light-dark cycles and ad libitum access to food and water. For

74 GFAP.Flag.HMOX1 mice, the transgene cascade leads to activation of human HO-1 coding sequence through the upstream promoter drive of glial fibrillary acidic protein (GFAP) and the “valve-controller” of tetracycline activator (tTA). This design confers two advantages: 1) The GFAP promoter selectively targets HMOX1 gene expression to the astrocytic compartment; 2) The Tetracycline (Tet)-Off system permits temporal control of transgene expression. In this system, Tet-controllable pGFAP.tTA and pTRE2.Flag.HMOX1 constructs were used to create the GFAP.HMOX1 transgenic (TG) mice. The pTRE2.Flag.HMOX1 construct contains a fusion gene of Flag (F) (30 bp; derived from pcDNA3.1/Zeo.Flag) and the entire protein-coding sequence (866 bp) of HMOX1 (Song et al. 2006) under the minimal CMV promoter/enhancer downstream of the tetracycline-response-element 2 (TRE2) (Song et al. 2012a). To inhibit transgene expression, doxycycline is provided through the diet (200 mg/kg, sterile, BIO-SERV, Frenchtown, NJ) to breeding pairs and derived litters. The doxycycline diet was replaced with regular rodent diet between 8.5 – 19 months of age to permit transgene expression. According to the life phase equivalencies between humans and mice (Vanhooren and Libert 2012), the selected window of transgene expression reflects early stages in the natural progression of idiopathic PD (approximately 33-62 years). For all animals, body weights, fur texture and mortality were monitored as indices of general health. PCR Genotyping The TG mice utilized in all in vivo experiments were heterozygous and of either sex. Genotypes were determined by PCR amplification of genomic tail DNA. Crude extracts containing genomic DNA from tail biopsy specimens were recovered using the REDExtract-N-AmpTM Tissue PCR kit (Sigma). The tTA coding sequence (1.009 kb) and the Flag + HMOX1 gene segment (989 bp) were amplified with respective primer pairs as previously described (Song et al. 2012a). Primers for glyceraldehyde 3-phosphate dehydrogenase (GAPDH) amplifying a shorter fragment of 385 bp were used as an internal control (Preisig-Muller et al. 1999). Postnatal day 1 (P1) neonates used to isolate primary astrocytes and neurons were offspring of homozygous TG breeders. Genotypes of parental animals were determined via purification of tail genomic DNA using a modified protease-digestion protocol (Gains et al. 2006, Wang and Storm 2006, Zangala 2007), followed by reverse transcriptase quantitative PCR (RT-

75 qPCR) with SensiFASTTM SYBR® Low ROX reagent (FroggaBio Inc., Toronto, ON) according to manufacturer instructions. The forward and reverse primer sequences used to detect genomic DNA were designed with Primer Express Software Version 3.0 (Applied Biosystems by Life Technologies) based on Gene Bank sequences. The tTA and TRE2 alleles were amplified in a single reaction containing the following primers: tTA-forward, 5’-ACAGCGCATTAGAGCTGCTTAAT-3’; tTA-reverse, 5’-GGCGAGTTTACGGGTTGTTAAA-3’; TRE2-forward, 5’- TGTACGGTGGGAGGCCTATATAA-3’; and TRE2-reverse, 5’-GCGTCTCCAGGCGATCTG-3’. b-actin was set up as an internal control with the primers as: b-actin-forward, 5’- GTGGGCCGCTCTAGGCACCAA-3’ and b-actin-reverse, 5’-CTCTTTGATGTCACGCACGATTTC-3’. Pharmacological Treatment Beginning at 13.5 months of age, GFAP.HMOX1 mice with late-activation of the HMOX1 transgene (at 8.5 months of age) and age-matched wild-type (WT) littermates were randomized to receive either the iron chelator, deferiprone (ApoPharma, Toronto ON) 1 mg/ml in drinking water or water vehicle only (control) daily (Hadziahmetovic et al. 2011) for 22 weeks. All animals underwent testing for behavioural endpoints following treatment. Behavioural Tests GFAP.HMOX1 mice and their WT littermates at 19 months of age were transferred to the Neurophenotyping Centre at the Douglas Mental Health University Institute for behavioural analyses. The animals were tested for non-spatial memory (olfaction) (Wong and Brown 2007); motor coordination and balance, including the rotarod test (Li et al. 2010), balance beam test (Luong et al. 2011) and inverted grids test (Brooks and Dunnett 2009); locomotor activity (Pinna et al. 2006) and anxiety (Thatcher-Britton paradigm) (Rochford et al. 1997). Surgical Procedures (i) For standard perfusions, mouse brains were fixed by transcardial perfusion as previously described (Fenton et al. 1998) with minor modifications. The animals were deeply anaesthetized with rodent cocktail containing ketamine, xylazine, acepromazine and saline followed by perfusion with 200 ml ice-cold saline and 250 ml of cold 4% paraformaldehyde in 0.1M phosphate buffered saline (PBS) (pH 7.4) for light microscopic analysis, or cold 2.5% glutaraldehyde in 0.1 M sodium cacodylate buffer (pH 7.5) containing 0.1% CaCl2 for transmission electron microscopy

76 (TEM). The brains were removed and immersed in the same fixatives for 24 hours at 4°C. For RNA and protein expression assays, mouse brains were frozen in dry ice immediately after transcardial perfusion with 200 ml ice-cold PBS and stored at -80ºC. (ii) For high performance liquid chromatography (HPLC) assays, animals were decapitated and brains were removed and frozen in 2-methylbutane at −40°C and stored at −80°C until use (Laplante et al. 2004). (iii) For primary culture of astrocytes and neurons, P1 neonates were decapitated and cells were isolated by mechanoenzymatic dissociation of cerebral tissue (see below). HPLC-EC Measurement of Brain Neurotransmitters Brains were sliced into 400–500 µm serial sections using a cryostat and selected brain regions (striatum, STM; substantial nigra, SN) were dissected using 0.5-2.0 mm micropunches. Tissues were homogenized in 0.25 M perchloric acid, centrifuged at 4ºC (10000 rpm, 15 min) and supernatants collected. HPLC with electrochemical detection (HPLC-EC) was used to measure concentrations of the monoamines, DA, norepinephrine (NE), epinephrine (E) and 5- hydroxytryptamine (5-HT); the monoamine metabolites, 3, 4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA) and 5-hydroxyindoleacetic acid (5-HIAA); and the neurotransmitter amino acids glutamate (GLU), gamma-amino butyric acid (GABA) and aspartate (ASP); as previously described (Gratton et al. 1989, Song et al. 2012a). Cell Culture P1 GFAP.HMOX1 and WT mice were used to generate primary astroglial and neuronal cultures. Approximately 20 min prior to dissection, mouse pups were separated from the mother. Mice were decapitated and astroglia or neurons were isolated by mechanoenzymatic dissociation of cerebral tissue as previously described (Cisse and Schipper 1995, Jones et al. 2012, Vaya et al. 2007). Astroglial cells were grown in Kaighn’s Modification of Ham’s F-12 Medium and high glucose Dulbecco’s Modified Eagle Medium (DMEM; 50:50, v/v), supplemented with 5% heat- inactivated horse serum, 5% heat-inactivated fetal bovine serum and penicillin-streptomycin (50 U/ml and 50 mg/ml, respectively). Cells were seeded in T-75 flasks at a density of 1.2 x 106 cells/ml and incubated at 37°C in humidified 95% air-5% CO2 for 6 h, after which they were vigorously shaken 18-20 times. Detached oligodendroglia and microglia were aspirated and fresh medium was added to the astroglial monolayers. The media were replaced on in vitro day 3 and

77 6 by which time more than 98% of the cells comprising the monolayer were determined to be astrocytes by GFAP immunolabeling (Chopra et al. 1995). After washing twice with PBS, astrocytes were harvested using Trizol (Life Technologies Inc., Burlington, ON) and stored at - 80°C in Trizol reagent until further use. For astroglial/neuronal co-cultures, neuronal cells were isolated from GFAP.HMOX1 and WT and mouse pups as described above. Neurons were seeded at a density of 1.0 x 106 cells/ml in 6-well plates pre-coated with Poly-L-Lysine (Sigma-Aldrich) and grown in Neurocell Modified medium, supplemented with 2% B-27 Supplement, 1% GlutaMAX-I and penicillin-streptomycin (50 U/ml and 50 mg/ml, respectively). After 48 hours, 3- day old astroglia were seeded in Transwell Permeable Supports 24 mm Inserts (Costar) (VWR International, Mont-Royal, QC) and introduced into wells containing the neurons (Fig. 1). Astroglial/neuronal co-cultures were maintained for 5-14 days with replacement of half the media every 3 days. Penicillin-streptomycin (50 U/mL and 50 mg/mL, respectively) was introduced on in vitro day 2, and cytosine β-D-arabinofuranoside (Ara-C; Sigma-Aldrich; 3 μM final concentration) on day 3, to the neuronal cultures. For RT-qPCR, cells were harvested under the aforementioned conditions and stored in Trizol reagent at -80°C until further use. For Western blotting, whole cell lysates were collected with ice-cold RIPA buffer (150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 50 mM Tris-HCl pH 8.0, 40 mM NaF, and protease inhibitors) and incubated on ice for 10 min. Adherent cells were detached using a rubber scraper, followed by incubation for 30 min at 4°C with constant agitation. The cell suspension was centrifuged at 13000 rpm for 20 min at 4°C and the supernatant was stored at -80°C until further use. Cell culture media and antibiotics were purchased from Wisent Inc. (St-Bruno, QC), and serum and supplements from Gibco (Life Technologies). mRNA Expression Analysis Total RNA extraction and cDNA synthesis - Total RNA from each dissected brain region or culture was extracted in Trizol according to the manufacturer instructions. 2.5 µg of total RNA was subjected to RT-qPCR using RevertAid first strand cDNA synthesis kit with oligo (dT)18 primer (Thermo Fisher Scientific Inc., Waltham, MA), and the resulting cDNA was amplified by PCR (Song et al. 2009).

78 mRNA RT-qPCR - The Applied Biosystems 7500 Fast Real-Time PCR System (Applied Biosystems by Life Technologies) was employed to quantify mRNA with SensiFASTTM SYBR® Low ROX reagent according to manufacturer instructions. 20 ng of cDNA was quantified for each reaction (10 µl final volume) via RT-qPCR. As shown in Table 1, the forward and reverse primer sequences used to detect mRNA were provided by OriGene Technologies (Rockville, MD) and designed to span an exon-intron boundary (Hibbeler et al. 2008), designed with Primer Express Software Version 3.0 (Applied Biosystems by Life Technologies), and validated by reference to published studies as in the case of a-synuclein (SNCA) and b-actin (Mak et al. 2009). Melting curves were verified for each reaction to screen for genomic DNA contamination or errors in primer design (primer dimer formation) (Nolan et al. 2006). mRNA expression fold changes between groups were calculated using the delta-delta Ct method relative to controls following normalization with levels of β-Actin mRNA (Livak and Schmittgen 2001). Histochemistry/Immunohistochemistry/Immunofluorescence Coronal brain sections (6µm) were deparaffinized and rehydrated in a series of graded alcohol solutions followed by de-ionized water. To assess iron distribution in brain tissue, sections were stained with Perls’ solution (Xian-hui et al. 2015). Perls-positive inclusions were quantified per unit area under light microscopy and photographed at a magnification of 400´. For immunostaining, sections were incubated with either polyclonal antibodies recognizing HO-1 (1:100; Enzo Life Sciences), TH (1:100; InvitrogenTM), MnSOD (1:200; InvitrogenTM), GFAP (1:100; Sigma-Aldrich), ubiquitin (1:500; InvitrogenTM), or monoclonal antibodies targeting Flag M2 (1:100; Sigma-Aldrich) and a-synuclein (1:250; BD BioScience), followed by goat anti-rabbit or donkey anti-mouse Cy3- or FITC-labeled IgG (1:50-100; Jackson ImmunoResearch) for immunofluorescence (IF); or goat anti-rabbit IgG peroxidase-linked (1:50-100; Cedarlane Laboratories) for immunohistochemistry (IHC). The IF sections were analyzed using a Carl Zeiss LSM 5 Pascal laser-scanning confocal imaging microscope. Ultrastructural Analyses Fixed mouse brains were sub-dissected into STM, hippocampus (HC), SN/ventral tegmental area (VTA) and prefrontal cortex (PFC) using a dissecting microscope, and processed for transmission electron microscopy as previously described (Zukor et al. 2009).

79 Western Blot Analysis Whole cell lysates were isolated from primary cell co-cultures following the protocol described above. The DC Protein Assay kit (Bio-Rad) was used to measure protein concentrations prior to Western blot analysis. Protein samples were boiled for 5 min in the presence of 4X SDS Loading Dye (0.2 M Tris-HCl pH 6.8, 0.2% SDS, 40% glycerol, 0.05 M EDTA pH 8.0, 4% beta- mercaptoethanol) before electrophoresis on 10% SDS-PAGE and transferred to a polyvinylidene difluoride (PVDF) membrane with 0.2 μm pore size (Bio-Rad). Anti-protein mouse, rat or rabbit monoclonal or polyclonal antibodies (TH, Millipore Bioscience Research Reagents; DAT, Abcam; α-synuclein, BD Transduction Laboratories; Caspase-3, R&D Systems; LC3B, Cell Signaling) were used at 1:1000 and anti-mouse, anti-rat or anti-rabbit IgG HRP (Promega) at 1:2000 were used to blot membranes. As an internal control, anti-actin clone C4 (MediMabs) at 1:2000 and anti- mouse IgG HRP (GE Healthcare) at 1:2000 were used to re-blot mildly stripped membranes. Amersham ECL Western 39 Blotting Detection Reagent was used for development and visualization of the protein bands (GE Healthcare Life Sciences). Quantification by densitometry and statistics were performed on 3-5 separate cultures per experimental group. Statistics All data are expressed as means ± standard error of the mean (SEM). Statistical significance between control and experimental values was determined using Student’s t test (paired, 2-tailed, 95% confidence interval) or one-way ANOVA followed by Newman–Keuls post hoc multiple- comparison test. For the rotarod test, two-way ANOVA was used to analyze serial trials considering two factors (genotype and trial). Statistical significance was set at p < 0.05. 10.4. Chapter 1 Results General health of GFAP.HMOX18.5-19m mice The TG and WT mice of either sex did not differ with respect to fur texture, body weight or mortality. Astroglial HMOX1 expression in aging GFAP.HMOX1 mice Astrocytes in all brain regions surveyed, including the SN and STM, of GFAP.HMOX18.5-19m mice exhibited anti-Flag immunoreactivity which was not observed in WT littermates (Fig. 2). Using dual immunolabeling and confocal microscopy, HMOX1 expression was documented in

80 astrocytes, ependymocytes and tanycytes, but not in neurons, microglia, oligodendroglia, cerebrovascular cells and other non-neural tissues, as previously described (Song et al. 2012a). Behaviour Glial expression of the HMOX1 transgene between 8.5-19 months of age resulted in poor rotarod performance relative to WT values (p<0.05; Fig. 3). A trend towards impaired motor coordination in mice expressing the transgene for an identical duration (10.5 months) but spanning the period from 1.5-12 months of age did not achieve statistical significance. Hyperkinesia was not observed in the TG mice in contradistinction to the hyperlocomotor behaviour documented in the mice expressing the HMOX1 transgene throughout development until 48 weeks of age (“schizophrenia model”) (Song et al. 2012a). The GFAP.HMOX18.5-19m mice exhibited intense asymmetric circling behaviour or stereotypy in an open field. Olfactory discrimination and anxiety testing revealed no abnormalities in TG mice compared to WT controls. Brain neurotransmitters In light of the observed behavioural abnormalities (above), we ascertained brain neurotransmitter concentrations with emphasis on the dopaminergic system (Table 2). Relative to WT controls, the TG mice exhibited a significant decrease in the levels of dopamine (DA) in STM (p<0.001), and a decline in striatal DA metabolites (DOPAC, HVA) which did not achieve statistical significance (p>0.05). Concentrations of serotonin (5-HT) and its metabolite, 5-HIAA remained unchanged in the TG brains relative to control values (p>0.05). GABA concentrations in the TG SN were markedly elevated compared to WT preparations (p<0.001). Albeit of uncertain clinical significance, augmented brain GABA levels have previously been reported in early-stage human and experimental parkinsonism (Emir et al. 2012, Gwiazda et al. 2002, Kish et al. 1986, Ondo and Hunter 2003, Oz et al. 2006). Reelin is a glycoprotein elaborated by subpopulations of GABAergic neurons which promotes neuronal migration/lamination during development, and synaptic plasticity important for learning and memory in the mature brain (Beffert et al. 2005, Herz and Chen 2006). GAD67 is also produced by GABA neurons wherein it acts downstream of reelin to regulate GABA synthesis (Guidotti et al. 2000). Reelin and GAD67 expression is reduced in several neurodevelopmental disorders (Guidotti et al. 2000, Nouel et al. 2012, Song et al. 2012a) and augmented in PD and other neurodegenerative states (Botella-Lopez et al. 2006,

81 Soghomonian and Laprade 1997). Expression levels of reelin and GAD67 mRNA were significantly increased in the GFAP.HMOX18.5-19m SN and STM (p<0.05-0.001) as well as in primary TG astrocyte/neuron co-cultures (p<0.05-0.01) relative to control values (Fig. 4). The induction of reelin and GAD67 may be mechanistically linked to the elevated nigral GABA concentrations documented in the GFAP.HMOX1 mice at 19 months of age (vide supra). Levels of NE, E, GLU and ASP in the nigrostriatum of the TG and WT mice were similar (p>0.05 for each comparison). Neuropathology Astroglial damage and dopaminergic neuronal toxicity were ascertained in TG and WT brains in situ, and in co-cultures of neurons with either TG or WT astrocytes. Dopaminergic neurons – Relative to WT preparations, TH immunoreactivity was significantly decreased in the GFAP.HMOX18.5-19m SN (p<0.05; Fig. 5A), and both TH and DAT mRNA expression levels were significantly decreased in the TG STM in situ (p<0.05-0.001; Fig. 5B). TH-positive cells in the TG, but not the WT, SN exhibited perikaryal distension and cytoplasmic vacuolation indicative of neuronal damage (Fig. 5A). TH and DAT mRNA expression was diminished in neurons co-cultured with TG astrocytes relative to expression levels obtained in neurons co-cultured with WT astroglia (p<0.05-0.01 for each comparison; Fig. 5C). TH and DAT protein levels were significantly decreased 5.1-fold and 8.7-fold, respectively, in neurons co- cultured with TG astrocytes relative to expression levels obtained in neurons co-cultured with WT astroglia (p £ 0.05; Fig. 5D, E). No differences were observed in TH and DAT protein levels between TG-derived and WT neurons grown in the absence of astrocytes, underscoring the dependence of the nigrostriatal DA deficit on ongoing exposure to the HO-1 overexpressing astroglia (Fig. 5D, E). mRNA expression levels of LMX1b and its downstream Pitx3 and Nurr1 transcription factors, which play vital roles in the development and maintenance of dopaminergic circuitry (Li et al. 2009), were significantly reduced in the TG STM relative to WT controls (p<0.05- 0.001; Fig. 5B). There was a significant reduction in LMX1b and Pitx3 mRNA levels (p<0.01-0.001), and a trend towards suppression of Nurr1 expression which did not reach statistical significance, in neurons co-cultured with TG astroglia compared to WT preparations (p>0.05; Fig. 5C). Synucleinopathy – Enhanced α-synuclein expression or reduced α-synuclein degradation is thought to mediate proteotoxicity and contribute to Lewy body formation in PD brain (Rott et

82 al. 2014). Both a-synuclein and ubiquitin mRNA were significantly upregulated in the TG STM and SN compared to WT controls (p<0.05-0.001; Fig. 6A), and this was confirmed in co-cultured TG astrocytes (α-synuclein and ubiquitin) and neurons (α-synuclein) (p<0.05-0.001, Fig. 6B). Commensurate with these findings, negative regulators of a-synuclein acting either upstream, viz. CtsB and CtsD, or downstream, viz. Notch1, were downregulated in the TG STM and SN compared to WT preparations (p<0.01-0.001; Fig. 6C). IF-confocal microscopy confirmed increased expression of a-synuclein (SN) and ubiquitin (SN, STM) protein in the TG mice which localized to and around TH-positive perikarya (Fig. 6E, F); Western blot confirmed a 1.6-fold increase in a-synuclein protein expression in isolated neurons co-cultured with TG astrocytes (p<0.01; Fig. 6D). Oxidative stress – The mRNA of MnSOD, a mitochondrial antioxidant enzyme and marker of oxidative stress that has previously been shown to accumulate in cultured astrocytes under HO-1 provocation (Frankel et al. 2000), was significantly increased in the TG STM and SN relative to WT control values (p<0.05-0.001; Fig. 7A). Enhanced expression of MnSOD in the TG nigrostriatum co-localized with HO-1 (Fig. 7C), GFAP and TH (data not shown), indicating that both neuronal (dopaminergic) and non-neuronal cell populations were subjected to pro-oxidant stressors in the affected tissues. In vivo upregulation of Sirt1 and PGC1-a mRNAs (p<0.05-0.001) and a trend towards downregulation of PARP1 mRNA (Fig. 7A) may represent protective responses to increased levels of ambient reactive oxygen species (ROS) accruing from glial HMOX1 overproduction (Alcendor et al. 2007, Chen et al. 2011). Similar mRNA expression profiles were obtained in co-cultures of primary astrocytes and neurons harvested from the brains of the GFAP.HMOX1 mice (Fig. 7B), further attesting to the important role of glia-derived ROS in the ensuing neuropathology. Iron deposition – Numbers of Perls-positive inclusions per unit area of the TG STM were increased relative to WT values (p<0.05; Fig. 8A). However, administration of the iron chelator, deferiprone, improved rotarod performance in the TG mice, as documented by duration on the rod before falling and rolling speed, compared to the vehicle-treated TG group (p<0.05; Fig. 8B). A trend towards longer travel distances on the rod in deferiprone-treated vs. vehicle-treated TG mice did not reach statistical significance (p>0.05; Fig. 8B). The improvement in rotarod

83 performance in the deferiprone-exposed TG mice substantially diminished differences in locomotor activity between the TG and WT animals (Fig. 8B). Deferiprone treatment did not significantly affect rotarod performance in WT mice (p>0.05 vs. vehicle-treated controls). Autophagy and mitochondrial biogenesis – The mRNAs of BECN1, p62 and Hdac6, genes participating in autophagy, were significantly upregulated in the TG STM and SN (p<0.05-0.001), and Lamp2 mRNA in STM only (p<0.001), compared to WT controls (Fig. 9A). These autophagy- related genes were also significantly upregulated at the mRNA level in both neurons and TG astrocytes grown together relative to WT co-cultures (p<0.05-0.001; Fig. 9B). The ratio of LC3B- II/LC3B-I, an autophagosome marker in its active membrane-bound and inactive cytosolic forms, respectively, was increased 3-fold in primary neurons co-cultured with TG astrocytes (p<0.05 vs. WT cells) but not in co-cultured TG astrocytes themselves (p>0.05 vs WT cells; Fig. 9C). We interrogated more specifically genes involved in mitophagy (mitochondrial macroautophagy), including Parkin, PTEN, PINK1 and DJ-1. Parkin, PTEN and PINK1 mRNAs were significantly upregulated in the TG SN (P< 0.05-0.001), but remained unchanged in TG STM (p>0.05), compared to WT controls (Fig. 9D). DJ-1 mRNA was unchanged in TG SN (p>0.05) and significantly downregulated (p<0.001) in TG STM compared to WT preparations (Fig. 9D). Similarly, in the co-culture experiments, Parkin, PTEN, and PINK1 mRNAs were significantly upregulated in both neurons and TG astrocytes (P<0.05-0.001), whereas neuronal DJ-1 mRNA was significantly suppressed vs. WT controls (P<0.05; Fig. 9E). Mitochondrial biogenesis, involving the Mfn1, Mfn2 and OPA-1 genes for fusion and Drp1 for fission, is reportedly dysregulated in PD brain (Celardo et al. 2014). Mfn1, Mfn2 and OPA-1 mRNAs were upregulated (p<0.05-0.001), and Drp1 significantly downregulated (p<0.001), in the basal ganglia of GFAP.HMOX18.5-19m mice (Fig. 9F), underscoring a profound imbalance in neural mitochondrial biogenesis. In vitro co-culture experiments suggested further that mitochondrial biogenesis in our model is more severely impacted in the HMOX1-expressing astrocytes than in the affected neuronal compartment (Fig. 9G). Commensurate with the molecular data, subcortical astrocytes in the GFAP.HMOX18.5-19m mice exhibited distended mitochondria with reduced and disorganized cristae, fragmented

84 membranes and osmiophilic cytoplasmic inclusions (Fig. 9H), ultrastructual features indicative of autophagosome formation and mitophagy (Gomes and Scorrano 2013, Klionsky et al. 2016). Apoptosis and neural cell stress – Several genes involved in the apoptotic pathway were analyzed, including p53, p21, PUMA, Bak, Bax and Bcl2. Most of the apoptotic genes surveyed were significantly upregulated at the mRNA level in both the TG STM and SN compared to WT values (p<0.05-0.001; Fig. 10A). In co-cultures of primary astrocytes and neurons derived from the brains of the GFAP.HMOX1 mice, mRNA levels of these pro-apoptotic genes were significantly increased in both cell compartments relative to WT co-cultures (p<0.05-0.001; Fig. 10B). Active caspase-3, an effector of programmed cell death, was increased 4.5-fold in neurons co-cultured with TG astrocytes compared to WT preparations (p<0.05; Fig. 10C). Several HMOX1-related changes in gene expression were largely restricted to the astrocytic compartment. Although levels of GFAP mRNA remained stable (possibly a ‘false- negative’ finding related to the GFAP.HMOX1 construct), S100B mRNA concentrations, which encodes a calcium-binding protein elaborated during reactive gliosis, were significantly elevated in the TG SN and STM and in cultured TG astroglia in comparison to respective WT controls (p<0.05-0.01; data not shown). 10.5. Chapter 1 Discussion The GFAP.HMOX18.5-19m mouse Selective overexpression of human HO-1 in astrocytes of GFAP.HMOX1 TG between 8.5 and 19 months of age resulted in a behavioural, neuropathological and molecular biological profile consistent with parkinsonism. The neurophenotype is characterized by locomotor incoordination and stereotypy; decreased nigrostriatal DA and attendant downregulation of TH, DAT, LMX1b, Nurr1 and Pitx3 mRNA and/or protein in affected basal ganglia; early synucleinopathy as evidenced by induction of α-synuclein and ubiquitin mRNA, down-modulation of α-synuclein- regulating genes (CtsB, CtsD, Notch1) and increased α-synuclein protein levels in DA neurons of the SN; central oxidative stress; pathological brain iron deposition and alleviation of neurological deficits by deferiprone treatment (iron chelation); aberrant mitochondrial function, autophagy and fission/fusion (biogenesis); gliosis; and GABAergic system alterations consisting of augmented nigral GABA concentrations and levels of reelin and GAD67 mRNA. All of the

85 aforementioned changes have been documented in idiopathic PD and/or established animal models of the disease (Kalia and Lang 2015, Schipper and Song 2015). Of note, this phenotype was not observed in mice expressing the HMOX1 transgene for an identical duration between 1.5 and 12 months of age (data not shown), underscoring the importance of brain aging for symptom manifestation in both human and experimental parkinsonism (Kalia and Lang 2015, Soderstrom et al. 2009). Dopaminergic neurotransmission and locomotion The reduced concentrations of striatal DA are likely responsible for the impaired rotarod performance (motor incoordination) and stereotypy (circling behaviour) observed in the GFAP.HMOX18.5-19m mice, as has been amply documented in other animal models of experimental parkinsonism (Blesa and Przedborski 2014, Soderstrom et al. 2009). The spontaneity and unidirectionality of the circling behaviour in our TG mice may further reflect hemispheric asymmetries in dopaminergic tone within the basal ganglia akin to the stereotypy seen in rodents following unilateral intra-nigral injection of 6-hydroxydopamine (Loscher et al. 1996, Soderstrom et al. 2009). The hypodopaminergia characterizing the GFAP.HMOX18.5-19m mice is readily explained by the decreased expression of TH and DAT mRNA and protein in the affected nigrostriatum (Salvatore et al. 2016). That no differences in TH and DAT mRNA levels could be discerned between TG-derived and WT neurons grown in isolation underscores the dependence of the nigrostriatal DA deficit on ongoing exposure to the HO-1 overexpressing astroglia. The observed suppression of brain cell Nurr1, Pitx3 and LMX1b, transcription factors required for DA synthesis/regulation and the terminal differentiation/maintenance of dopaminergic neurons, may account for the downregulation of TH and DAT in the GFAP.HMOX18.5-19m mice. Glial HO-1 and the pathogenesis of PD The neurodystrophic changes, aberrant DA and GABA levels and behavioural abnormalities documented in the GFAP.HMOX18.5-19m mice indicate unequivocally that patterns of neuronal dysfunction commensurate with parkinsonism may be evoked by a primary insult to the astroglial compartment. Indeed, many of the robust alterations in gene expression impacting dopaminergic and GABAergic neurotransmission, a-synuclein metabolism, mitochondrial biogenesis,

86 autophagy, cytoprotection and apoptosis observed in the GFAP.HMOX18.5-19m mouse nigrostriatum in situ were recapitulated in primary neurons co-cultured with HMOX1-transgenic astroglia (current study). That neuraxis-wide overexpression of HO-1 and attendant iron sequestration in mature astrocytes culminates specifically in an extrapyramidal disorder may be related to the fact that (i) the basal ganglia are naturally predisposed to the accumulation of iron in the course of normal development and aging and (ii) genetically diverse cases of ‘neurodegeneration with brain iron accumulation’ almost invariably feature involuntary movements and incoordination (extrapyramidal signs) at some point in their natural history and degenerative changes in the basal ganglia on neuroimaging and histopathology (Schipper 2011). A panoply of consensus sequences within the HMOX1 promoter renders the gene sensitive to upregulation by pesticides (e.g. paraquat, maneb, rotenone), organic solvents, pro-inflammatory cytokines, transition metals, mitochondria-derived ROS and other stressors implicated in the development of PD (Kalia and Lang 2015, Schipper and Song 2015, Soderstrom et al. 2009). The GFAP.HMOX18.5-19m mouse teaches that upregulation of HO-1 in brain astrocytes, as has been documented in the basal ganglia of PD subjects (Schipper et al. 1998), may be a critical link in the etiopathogenesis of PD by transducing deleterious environmental and endogenous influences into patterns of dopaminergic cell dysfunction and degeneration. Non-transferrin iron, pathologically sequestered in astrocytes of the senescent and degenerating CNS as a result of HO-1 hyperactivity (Song et al. 2012b, Zukor et al. 2009) (current study), behaves as a pseudoperoxidase that facilitates the non-enzymatic bioactivation of DA and other catechol- containing compounds to neurotoxic semiquinone radicals (Schipper et al. 1991), and MPTP to the dopaminergic toxin, MPP+ (Di Monte et al. 1995). The redox-active iron is particularly inimical to the mitochondrial compartment where it fosters profound membrane damage, loss of cristae, organellar swelling and mitophagy (Song et al. 2012b, Zukor et al. 2009). Mitochondrial integrity in the basal ganglia of GFAP.HMOX18.5-19m mice may be further compromised by the overproduction of a-synuclein (current study) which interacts with the outer membrane receptor, TOM20 to block protein import into the organelle (Di Maio et al. 2016). Altered redox homeostasis in the basal ganglia of GFAP.HMOX18.5-19m mice, as evidenced by induction of Mnsod in both astrocytes and dopaminergic neurons, may be responsible for upregulation and post-

87 translational modification of a-synuclein in these animals (Hwang 2013, Song et al. 2012a). Our observations are consistent with the elevated levels of α-synuclein mRNA and protein documented in the basal ganglia of PD subjects (Baba et al. 1998, Grundemann et al. 2008). The apparent enhancement of both perikaryal and neuropil α-synuclein immunofluorescence in the GFAP.HMOX18.5-19m mouse brain may lend support to the recent ‘prion hypothesis’ of α-synuclein propagation (Chu and Kordower 2015, Lewis et al. 2014, Luk et al. 2012), while the abundance of tetrameric α-synuclein detected by Western blot of primary neurons co-cultured with TG (relative to WT) astrocytes is of uncertain biological significance (Giraldez-Perez et al. 2014). In line with our observations, Rostami and colleagues (Rostami et al., 2016) recently reported that (i) astrocytes derived from human embryonic stem cells incorporate exogenous monomeric or oligomeric α-synuclein, (ii) oligomeric α-synuclein is incompletely degraded by, and impairs mitochondrial function in, these cells, and (iii) α-synuclein aggregates may be transferred between astrocytes in a prion-like fashion. α-Synuclein may not be the sole gene product compromising mitochondrial integrity in the GFAP.HMOX18.5-19m mice. In an earlier study using cultured rat astrocytes, all of three microRNA (miRNA) species augmented by HMOX1 transfection (miR-140, -17 and -16), and four of six down-modulated miRNAs (miR-206, -181a, -138, -29c), deregulate target genes known or predicted to impact mitochondrial structure and/or function (Lin et al. 2015). The downregulation of DJ-1 observed in the GFAP.HMOX18.5-19m mouse basal ganglia (current study) may also contribute to the accumulation of dystrophic mitochondria in our model in so far as: (i) mutations in PARK7, which codes for human DJ-1, cause an autosomal recessive form of familial PD with documented mitochondrial deficits (Moon and Paek 2015, Ryan et al. 2015); (ii) DJ-1 knockout mice exhibit parkinsonism and altered nigrostriatal dopaminergic transmission (Harvey et al. 2008, Lopert and Patel 2014); (iii) oxidized, inactive DJ-1 protein is excessively deposited and is associated with bioenergy failure in the brains of persons with sporadic PD and Alzheimer disease (Ariga et al. 2013, Bandopadhyay et al. 2004, Choi et al. 2006); and (iv) DJ-1 knockdown in astrocytes de-regulates mitochondrial complex I activity and impedes glia-mediated neuroprotection against oxidative stress (Ariga et al. 2013, Lev et al. 2006, Moon and Paek 2015). Conceivably, the induction of Parkin, Pten and Pink1 in the SN of GFAP.HMOX18.5-19m mice, genes

88 which also give rise to familial PD when mutated (Harvey et al. 2008, Sung et al. 2016), represents an adaptive response aimed at disposing of mitochondrial carcasses (macroautophagy) in the affected tissues (Poole et al. 2008, Thomas et al. 2011, Vives-Bauza et al. 2010, Yang et al. 2006). The release of DA from degenerating nigrostriatal neurons and proinflammatory cytokines (TNF- α, IL-1β) from activated microglia may further induce HMOX1 in indigent astrocytes, completing a self-reinforcing loop of pathological cellular interactions that perpetuate oxidative neural injury and mitochondrial insufficiency long after exposure to initiating stimuli may have dissipated. The upregulation of Sirt1, PGC1-a and S100B mRNAs, and downmodulation of PARP1 mRNA, noted in the basal ganglia of the GFAP.HMOX18.5-19m mice (current study) are likely components of a concerted neuroprotective response to the ingravescent oxidative damage (Donmez et al. 2012, Hu et al. 1997, Iuvone et al. 2007, Martire et al. 2015, Sathe et al. 2012). HO-1 and PD: Therapeutic considerations The data presented here further implicate astroglial HO-1 as a pivotal transducer of noxious stimuli, a potent driver of relevant cytopathology and a potential therapeutic target in PD and other chronic human CNS conditions (Fig. 11). Metalloporphyrin inhibitors of heme oxygenase activity have been employed in the management of neonatal hyperbilirubinemia (jaundice) and certain adult liver conditions (Drummond and Kappas 2004, Kappas et al. 1993) and could be adapted for use in idiopathic PD. Small, azole-based inhibitors, such as OB-28, may confer additional advantages given their specificity for HO-1 relative to HO-2, blood-brain barrier permeability and favorable toxicity profile in pre-clinical studies (Alaoui-Jamali et al. 2009, Gupta et al. 2014). Alternatively, in light of their successful deployment in neurons (Kumar et al. 2007) and hepatocytes (Rozema et al. 2007), siRNA delivery systems could be exploited to achieve selective HO-1 knock-down within the astrocytic compartment (Syapin 2008). Clinical trials may be warranted to ascertain whether containment of the glial HO-1 response to provocative stimuli at strategic points of the life cycle will prevent or ameliorate PD and related CNS disorders. Acknowledgments This work was supported by Canadian Institutes of Health Research Grant MOP-68887 (H.M.S.), the Mary Katz Claman Foundation (H.M.S.) and ApoPharma Inc. (H.M.S.). W.S. is a Mary Katz

89 Claman Foundation senior scientist. The authors thank Ms. Jessica Hier and Ms. Elka Schwartz for their assistance with RT-qPCR experiments. Conflicts of Interest The authors have no conflicts of interest to report. Author contributions W.S. and H.M.S. designed the research; W.S., M.C., H.Z., A.L., C.G., performed the experiments; W.S., H.M.S., M.C., H.Z., and A.L. analyzed the data; W.S., M.C. and H.M.S. wrote the paper.

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100 10.7. Chapter 1 Tables and Figures Table 1. Primer sequences for mRNA expression by RT-qPCR.

Primer Accession No.1 Forward (5’-3’) Reverse (5’-3’) Actb (β-actin)2 NM_007393 AGGGAAATCGTGCGTGAC CGCTCATTGCCGATAGTG Bak1 NM_007523 GGAATGCCTACGAACTCTTCACC CAAACCACGCTGGTAGACGTAC Bax NM_007527 AGGATGCGTCCACCAAGAAGCT TCCGTGTCCACGTCAGCAATCA Bcl22 NM_009741 GGGATGCCTTTGTGGAACTATATG CAGCCAGGAGAAATCAAACAGA Bdnf NM_007540 GGCTGACACTTTTGAGCACGTC CTCCAAAGGCACTTGACTGCTG Becn12 NM_019584 GGACAAGCTCAAGAAAACCAATG TGTCCGCTGTGCCAGATGT Ctsb NM_007798 AGTCAACGTGGAGGTGTCTGCT GTAGACTCCACCTGAAACCAGG Ctsd NM_009983 TAAGACCACGGAGCCAGTGTCA CCACAGGTTAGAGGAGCCAGTA Dat2 NM_010020 GGTGCTGATTGCCTTCTCCAGT GACAACGAAGCCAGAGGAGAAG Dj1 (Park7) NM_020569 ACGATGTGGTGGTTCTTCCAGG CTGCACAGATGGCAGCTATGAG Drp12 NM_152816 GCGAACCTTAGAATCTGTGGACC CAGGCACAAATAAAGCAGGACGG Fis1 NM_025562 GCTGGTTCTGTGTCCAAGAGCA GACATAGTCCCGCTGTTCCTCT Fundc1 NM_028058 AGACACCACTGGTGGAATCGAG CCTTCTGGAATAAAAATCCTGCAC Gad1 (GAD67) NM_008077 CGCTTGGCTTTGGAACCGACAA GAATGCTCCGTAAACAGTCGTGC Gfap NM_010277 CACCTACAGGAAATTGCTGGAGG CCACGATGTTCCTCTTGAGGTG Hdac6 NM_010413 TCGCTGTCTCATCCTACCTGCT GTCAAAGTTGGCACCTTCACGG Igf1r NM_ 010513 CGGGATCTCATCAGCTTCACAG TCCTTGTTCGGAGGCAGGTCTA Lamp22 NM_010685 TGTGCCTCTCTCCGGTTAAAG CGGCTCCTAGGAACAGAAAGATC Ldha NM_010699 ACGCAGACAAGGAGCAGTGGAA ATGCTCTCAGCCAAGTCTGCCA Lmx1b2 NM_010725 GAAGGAGAAAGACCTGCTCAGC TCCACTGCCTTTACTCTGGCTG Mfn1 NM_024200 CCAGGTACAGATGTCACCACAG TTGGAGAGCCGCTCATTCACCT Mfn2 NM_133201 GTGGAATACGCCAGTGAGAAGC CACCTTGCTGGCACAGATGAGC Nix (Bnip3l) NM_009761 GCATGAGGAAGAGTGGAGCCAT AAGGTGTGCTCAGTCGTTTTCCA Nlgn2 NM_198862 CGATGTCATGCTCAGCGCAGTA CCACACTACCTCTTCAAAGCGG Notch1 NM_008714 GCTGCCTCTTTGATGGCTTCGA CACATTCGGCACTGTTACAGCC Nrxn1 NM_177284 ACCGTGCCTTAGCAATCCTTGC GTCGTAGCTCAAAACCGTTGCC Nurr12 NM_013613 CCGCCGAAATCGTTGTCAGTAC TTCGGCTTCGAGGGTAAACGAC Med12 (OPA-1) NM_ 021521 GCTCCTAGAAGACCTGATTCGC AGGATTCGGCAAGTAAGCCTGG p21 NM_007669 TCGCTGTCTTGCACTCTGGTGT CCAATCTGCGCTTGGAGTGATAG p533 NM_011640 AACCGCCGACCTATCCTTAC CTTCTGTACGGCGGTCTCTC p62 NM_053074 GAGGAGCGTGAGAAGACCTACAA ATGCGCTTGAGCTGAGCAT Park2 NM_016694 CCAGAGGAAAGTCACCTGCGAA GTTCGAGCAGTGAGTCGCAATC Parp12 NM_007415 CCACGCACAACGCCTATG CCCCCTCGCGCTCTATCT Pax6 NM_013627 CTGAGGAACCAGAGAAGACAGG CATGGAACCTGATGTGAAGGAGG Ppargc1a (PGC- NM_008904 GAATCAAGCCACTACAGACACCG CATCCCTCTTGAGCCTTTCGTG 1a) Pink1 NM_026880 CGACAACATCCTTGTGGAGTGG CATTGCCACCACGCTACACT Pitx32 NM_008852 CTTCCAGAGGAATCGCTACCCT CTGCGAAGCCACCTTTGCACAG Pten NM_008960 TGAGTTCCCTCAGCCATTGCCT GAGGTTTCCTCTGGTCCTGGTA Bbc3 (PUMA) NM_133234 ACCGCTCCACCTGCCGTCCGTCAC ACGGGCGACTCTAAGTGCTGC Reln (reeler) NM_011261 GCCACGCCACAATGGAA CGACCTCCACATGGTCCA Rims3 NM_182929 GGTGCCAAGATGGTAGCTATCG TCTCTGTGCTCCGTCGGATGTT S100b NM_009115 AGAGGGTGACAAGCACAAGCTG GAACTCCTGGAAGTCACACTCC Sirt12 NM_019812 CAGTGTCATGGTTCCTTTGC CACCGAGGAACTACCTGAT Snca (alphaSYN) NM_001042451 CACTGGCTTTGTCAAGAAGGACC CATAAGCCTCACTGCCAGGATC Sod22 (MnSOD) NM_013671 TAACGCGCAGATCATGCAGCTG AGGCTGAAGAGCGACCTGAGTT Th2 NM_009377 TGCACACAGTACATCCGTCATGC GCAAATGTGCGGTCAGCCAACA Uba52 NM_019883 GATATTCGCGGGCAAACAGCTG GTACTTCTGGGCAAGCTGACGA Vdac1 NM_011694 AGTGACCCAGAGCAACTTCGCA CAGGCGAGATTGACAGCAGTCT Vdac2 NM_011695 TCGGCAAAGCTGCCAGAGACAT GTCTCCAAGGTCCCGCTAACTT Vglut1 NM_182993 TGGCTGTGTCATCTTCGTGAGG TTGCCAGCCGACTCCGTTCTAA Vglut2 NM_080853 CCTATGCTGGAGCAGTCATTGC GGCTCTCATAAGACACCAGAAGC Vglut3 NM_182959 GAGTGGCTATCTCCTTCCTGGT TGGCATAGCGTGGAGCAATGTC 1Accession number for NCBI reference sequence; 2Sequences designed with Primer Express Software Version 3.0 (Applied Biosystems by Life Technologies) based on GeneBank sequences; 3Sequence from Lee et al. (Lee et al. 2007). The remaining sequences were obtained from OriGene Technologies (Rockville, MD).

101 Table 2. Neurochemistry of aged WT and GFAP.HMOX1 mice. Following behavioural testing, HPLC-EC assays were performed on STM and SN of GFAP.HMOX1 and WT mice of either sex at 19 months of age. Concentrations of monoamines (DA, NE, E, and 5-HT), monoamine metabolites (DOPAC, HVA), and 5-HIAA, ASP, GLU and GABA were analyzed by ANOVA. n=5 for TG mice and n=4 for WT littermates. ***p<0.001 relative to WT preparations.

Brain regions (WT/TG) Brain regions (WT/TG) NTs NTs STM SN STM SN 594.62 ± 47.40 3.11 ± 0.40 5.50 ± 0.56 4.73 ± 1.17 DA 467.48 ± 30.22 *** 5.92 ± 0.80 NE 5.50 ± 0.57 7.62 ± 1.02

174.44 ± 28.23 2.86 ± 0.69 0.24 ± 0.19 0.47 ± 0.28 DOPAC 126.64 ± 16.20 5.35 ± 0.73 E 4.17 ± 3.98 0.47 ± 0.23 50.68 ± 2.36 1.72 ± 0.93 14.37 ± 4.43 2.49 ± 0.71 HVA 40.47 ± 4.52 3.19 ± 2.46 HIAA 14.18 ± 1.59 6.63 ± 2.38 0.30 ± 0.72 0.93 ± 0.21 16.63 ± 2.13 2.05 ± 1.42 DOPAC 0.27 ± 0.03 1.03 ± 0.31 5-HT 16.92 ± 0.71 4.38 ± 1.43 /DA 316.37 ± 67.45 85.78 ± 37.94 150.99 ± 17.27 43.85 ± 14.96 GLU 274.94 ± 51.66 173.81 ± 69.64 ASP 143.78 ± 21.99 160.37 ± 94.02 1229.84 ± 177.90 384.82 ± 148.99 GABA 1087.08 ± 191.70 2005.24 ± 142.68 *** - -

102

Figure 1. Primary astrocyte and neuronal co-cultures. WT, wild-type; TG, GFAP.HMOX1+/+ transgenic; WtN, wild-type neurons; WtA, wild-type astrocytes; TgA, transgenic astrocytes; TgN, transgenic mouse neurons. See text for experimental details.

103

Figure 2. HMOX1 transgene expression. Astrocytes in STM, SN, and area adjacent to the third ventricle (PV) of a 19 month old male GFAP.HMOX1 mouse exhibit anti-Flag immunoreactivity (black; bottom panels), which is not observed in a WT littermate (top panels). Eosin counterstain. Magnification bars =1000x for all panels.

104

Figure 3. Effects of glial HMOX1 on rotarod performance. Glial expression of the HMOX1 transgene between 8.5-19 months of age impairs rotarod performance (right column in panels A, B and C). A trend towards motor incoordination in mice expressing the transgene for an identical duration (10.5 months), but spanning the period from 1.5-12 months of age, did not achieve statistical significance (central panels). Animals of either sex were employed in all tests.

105

Figure 4. Reelin and GAD67 mRNA in aging GFAP.HMOX1 mice. Gene expression profiles for whole brain samples (A) and co-cultured cells (B). n=5 per group, *p<0.05, **p<0.01, ***p<0.001 relative to WT control preparations.

106

Figure 5. Effects of glial HMOX1 on the dopaminergic system (mRNA, protein). A. TH immunoreactivity in WT (left panel) and TG (right panel) SN. Magnification bars = 100x (insets) and 1000x (panels). Insets depict depletion of dopaminergic neurons in the TG SN relative to WT preparations. Numbers of TH-positive cells in SN (middle small panel), n=5 brains per group. TH- positive cells in the TG SN exhibit perikaryal distension and cytoplasmic vacuolation (arrows). B,

107 C. Gene expression profiles for whole brain samples (B) and co-cultured cells (C). n=5 per group, *p<0.05, **p<0.01, ***p<0.001 relative to WT control preparations. D, E. Western blots for TH (60 kDa, D) and DAT (69 kDa, E) in neurons (underline denotes cell type assayed) co-cultured with WT (WtN/WtA) or TG (TgN/TgA) astrocytes. Neurons isolated from WT and TG brains, but cultured in the absence of WT or TG astrocytes, served as additional controls.

108

Figure 6. Synucleinopathy in GFAP.HMOX1 mice. Gene expression profiles for a-synuclein, ubiquitin, and a-synuclein regulating genes in whole brain homogenates (A, C) and co-cultured cells (B). n=5 per group, *p<0.05, **p<0.01, ***p<0.001 relative to WT control preparations. D. Western blot of a-synuclein expression in neurons (underline indicates cell type assayed) co- cultured with WT (WtN/WtA) or TG (TgN/TgA) astrocytes. Multimeric a-synuclein is overexpressed in neurons co-cultured with GFAP.HMOX1 astrocytes compared to WT preparations (top label). The expected molecular weight of monomeric a-synuclein is 14 kDa (bottom label). E. Confocal images of intra- and extraperikaryal a-synuclein IF (green) in TG

109 (bottom panels) and WT (top panels) SN and STM. Yellow fluorescence denotes co-localization of a-synuclein (green) and TH (red), while blue fluorescence represents nuclei (DAPI). Inset shows intracellular TH IF only (red) in WT SN (control for a-synuclein). F. Confocal imaging of ubiquitin (green) and TH (red) IF in the GFAP.HMOX18.5-19m SN and STM (bottom panels) compared with corresponding WT SN and STM (top panels). Yellow fluorescence denotes co-localization of ubiquitin (green) and TH (red), while blue fluorescence represents nuclei (DAPI).

110

Figure 7. Oxidative stress in GFAP.HMOX1 mice. A, B. Gene expression profiles for oxidative stress markers in brain homogenates (A) and co-cultured cells (B). n=5 per group, *p<0.05, **p<0.01, ***p<0.001 relative to WT control preparations. C. MnSOD protein IF (green), a key marker of mitochondrial oxidative stress, in neurons (bottom panels) of the TG SN at 19 months of age relative to WT samples (top panels). Large, perinuclear inclusions consistent with pathological mitochondria are noted in TG neurons after co-staining for MnSOD and HO-1 (yellow). Magnification bars =10 µm for all panels.

111 A

Figure 8. Brain iron deposition and effects of iron chelator deferiprone (DFP) on rotarod performance. A. Perls-positive inclusions (arrows) in WT and TG STM. Magnification bars = 25 µm for left panel. n=4 brains for each group. B. Effects of DFP treatment on time spent on rotarod before falling (p<0.05, left panels), rolling speed (p<0.05, middle panels) and distance travelled (p>0.05, right panels) in GFAP.HMOX18.5-19m mice relative to vehicle-treated TG controls. Top panels indicate impaired rotarod performance in vehicle-treated GFAP.HMOX18.5-19m mice relative to vehicle-treated WT controls. Animals of either sex were employed in all tests.

112

Figure 9. Mitochondrial autophagy and biogenesis. Gene expression profiles for autophagic machinery in brain homogenates (A) and co-cultured cells (B). LC3BII/I ratios were determined by Western blot and densitometry (C). Expression profiles for mitophagic genes in brain homogenates (D) and co-cultured cells (E). Expression profiles for genes subserving

113 mitochondrial biogenesis in brain homogenates (F) and co-cultured cells (G). For quantitative analysis, n=5 per group, *p<0.05, **p<0.01, ***p<0.001 relative to WT control preparations. H. Astrocytes in the STM of 19-month WT brains (i) exhibit normal mitochondrial profiles (white arrows) and few or no pathological inclusions. Astrocytes in the 19-month GFAP.HMOX18.5-19m STM (ii, iii, iv) contain distended mitochondria with reduced and disorganized cristae and fragmented membranes (black arrows) and osmiophilic cytoplasmic inclusions (asterisks). Magnification bars = 2 µm in top panels (i, ii), and 500 nm in bottom panels (iii, iv).

114

Figure 10. Mitochondria-dependent apoptosis. Gene expression profiles for apoptotic machinery in brain homogenates (A) and co-cultured cells (B). Western blot for cleaved caspase- 3 (Casp-3) was performed in neurons (underline indicates cell type assayed) co-cultured with WT (WtN/WtA) or TG (TgN/TgA) astrocytes (C). Molecular weight of cleaved Casp-3 is 17 kDa.

115 Heme Pro-toxin bioactivation

Fe2+ HO-1 CO OS Mitochondrial iron ATP

Biliverdin Bilirubin Macroautophagy ASTROCYTE GSH Glutamate uptake

TH DAT Late Life Stressors Pitx3 OS Excitotoxicity Nurr1

Aging LMX1B Genetic risk factors -synuclein Environmental risk factors Neuroinflammation

Neuronal degeneration DA NEURON DA DA Mito. fission/fusion Mitophagy Apoptosis

Motor incoordination Stereotypy Figure 11 Figure 11. Putative “transducer” role of astroglial HO-1 in the etiopathogenesis of PD. See Discussion for details. CO, carbon monoxide; DA, dopamine; DAT, dopamine transporter; Fe2+, ferrous iron; GSH, glutathione; HO-1, heme oxygenase-1; LMX1b, LIM homeobox transcription factor 1-beta; mito., mitochondrial; Nurr1, nuclear receptor related-1 protein; OS, oxidative stress; Pitx3, pituitary homeobox 3; TH, tyrosine hydroxylase; Δ, change; ↓, decreased; ↑, increased.

116 11. Transition 1: Expanding Parkinsonian Behavioural Profiles in GFAP.HMOX18.5-19m Mice That early-life HMOX1 overexpression in mice resulted in a neurodevelopmental phenotype reminiscent of human schizophrenia was discovered serendipitously and published previously (Song et al. 2012a). With the characterization of the GFAP.HMOX18.5-19m mouse model of Parkinson disease (PD) (see Chapter 1) and the previous characterization of the GFAP.HMOX10- 12m mouse model of schizophrenia (Song et al. 2012a), we wanted to expand behavioural profiles and directly compare and contrast the two conditions. The GFAP.HMOX1 mouse raises the intriguing possibility that identical sets of stressors and convergent downstream mechanisms elicit either early-onset developmental (e.g. schizophrenia) or later-life degenerative (e.g. PD) brain disorders. In this case, this depends on whether the glial HO-1 response is evoked prior to or following the maturation of dopaminergic and other salient neural circuitry, lending to what we coined ‘the great dopamine paradox’ (see Chapter 2 and Section 19.10). In parkinsonian GFAP.HMOX18.5-19m mice, the previous study employed the following behavioural tests: olfactory discrimination learning task, rotarod test, balance beam test, inverted grid test and the Thatcher-Britton novelty-conflict (open field) paradigm. The following study assessed parkinsonian behaviours using three additional tests: gait test, pole test and buried pellet test.

117 12. Chapter 2: Strategic Timing of Glial HMOX1 Expression Results in Either Schizophrenia-Like or Parkinsonian Behaviour in Mice

Published in Antioxidant and Redox Signaling (2019).

Author List: Ayda Tavitian1,2*, Marisa Cressatti1,2*, Wei Song1, Ariana Z. Turk2, Carmela Galindez1, Adam Smart1,2, Adrienne Liberman1, Hyman M. Schipper1,2 *These authors contributed equally to this study. Figures 7, 8 and 9 represent data included in the current Ph.D. thesis, while Figures 1, 2, 3, 4, 5 and 6 represent data included in A.T.’s (co-first author) traditional monograph style Ph.D. thesis. Figure 10 was created jointly by M.C. and A.T..

1Lady Davis Institute for Medical Research, Jewish General Hospital 2Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada, H3T 1E2

Corresponding Author: Dr. Hyman Schipper, Lady Davis Institute for Medical Research, Jewish General Hospital, 3755 Cote Ste. Catherine Road, Montreal, Quebec H3T 1E2, Canada. E-mail: [email protected]; Phone: 514-340-8222 ext. 25588; Fax: 514-340-7502

Short Title: Glial HMOX1, Dopamine and Behaviour

118 12.1. Chapter 2 Abstract Aims: In this original research communication, we assess the impact of shifting the window of glial HMOX1 overexpression in mice from early-to-mid-life to mid-to-late-life, resulting in two disparate conditions modeling schizophrenia (SCZ) and Parkinson disease (PD). Mesolimbic hyperdopaminergia is a widely accepted feature of SCZ, while nigrostriatal hypodopaminergia is the sine qua non of idiopathic PD. Although the advent of parkinsonian features in SCZ patients following treatment with anti-dopaminergic agents is intuitive, subtle features of parkinsonism commonly observed in young, drug-naïve schizophrenics is not. Similarly, emergent psychosis in PD subjects receiving levodopa replacement is not unusual, whereas spontaneous hallucinosis in non-medicated persons with idiopathic PD is enigmatic. Investigations using GFAP.HMOX1 mice may shed light on these clinical paradoxes. Results: Astroglial HO-1 overexpression in mice throughout embryogenesis until 6 or 12 months of age resulted in hyperdopaminergia, hyperkinesia/stereotypy ameliorated with clozapine, deficient prepulse inhibition of the acoustic startle response, reduced preference for social novelty, impaired nest-building, and cognitive dysfunction reminiscent of SCZ. On the other hand, astroglial HO-1 overexpression between 8.5 and 19 months of age yielded a PD-like behavioural phenotype with hypodopaminergia, altered gait, locomotor incoordination, and reduced olfaction. Innovation: We conjecture that region-specific disparities in the susceptibility of dopaminergic and other circuitry to the trophic and degenerative influences of glial HMOX1 induction may permit the concomitant expression of mixed SCZ and PD traits within affected individuals. Conclusion: Elucidation of these converging mechanisms may (i) help better understand disease pathogenesis and (ii) identify HO-1 as a potential therapeutic target in neurodevelopmental and neurodegenerative disorders.

Keywords: Astrocyte, behaviour, dopamine, heme oxygenase-1, Parkinson disease, schizophrenia.

119 12.2. Chapter 2 Introduction Human neurodevelopmental and neurodegenerative disorders differ with respect to risk factors, demographics, neurological and behavioural symptoms, neuroimaging, cytopathology, and neurochemistry. Iron deposition, oxidative stress, mitochondrial dysfunction, and macroautophagy form a tetrad of neuropathological features common to various neurodevelopmental and neurodegenerative disorders (Schipper 2004a, Schipper et al. 2019). We have previously shown that these core characteristics may comprise a single ‘lesion’ devolving from the sustained or repeated upregulation of HMOX1, the gene coding for heme oxygenase-1 (HO-1), in astrocytes (ibid.) (Schipper et al. 2019). We showed that the advent of this gliopathy renders nearby neuronal constituents prone to oxidative injury (Frankel and Schipper 1999, Song et al. 2007) and that pharmacological suppression of brain HO-1 activity ameliorates several behavioural and neuropathological abnormalities in vitro and in vivo (Gupta et al. 2014). To further ascertain the potential role(s) of astroglial HO-1 in human neuropathology, we engineered novel GFAP.HMOX1 transgenic (TG) mice that selectively express HMOX1 in astrocytes under temporal control of dietary doxycycline (Song et al. 2017a, Song et al. 2012a). Astrocytic expression of the HMOX1 transgene, detected by immunohistochemistry, is present throughout the brain in these mice (Song et al. 2017a, Song et al. 2012a), and total HO-1 protein levels (assayed by ELISA and Western blot) are significantly elevated in various brain regions (Song et al. 2017b, Song et al. 2012a). Expression of the transgene was also observed in ependymocytes and ependymal tanycytes, but not in oligodendroglia, microglia, neurons, cerebrovascular cells, or non-nervous tissue (Song et al. 2017a, Song et al. 2012a). The advent of novel GFAP.HMOX1 TG mice in our laboratory has allowed us to delineate the role(s) of glial HO-1 at strategic time points in the lifespan, with early-to-midlife overexpression of HMOX1 resulting in a schizophrenia-like phenotype (Song et al. 2012a) and mid-to-late-life overexpression of HMOX1 yielding a parkinsonian phenotype (Song et al. 2017a). SCZ is a hyperdopaminergic neurodevelopmental condition characterized by aberrant cognition, emotion, and behaviour that affects approximately 1% of the world population. The neuropathology of SCZ includes cerebral ventriculomegaly, alterations in regional volumetrics

120 and cytoarchitectonics, and dysregulation of genes implicated in neuronal proliferation, migration, and differentiation (Bakhshi and Chance 2015). A wide spectrum of genetic and perinatal risk factors, such as maternal psychotrauma and gestational exposure to toxins and infections, may funnel along limited neurodevelopmental trajectories to elicit SCZ and animal models of the disorder (Brown 2011). In 2004, Prabakaran and co-workers reported HMOX1 induction in the prefrontal cortex of SCZ patients that correlated with mitochondrial dysfunction and altered redox homeostasis in this brain region (Prabakaran et al. 2004). Hypomethylation of the HMOX1 promoter was subsequently documented in a genome-wide methylation study of peripheral blood DNA procured from SCZ subjects which may facilitate HO-1 overexpression in this disease (Rukova et al. 2014). Stressors germane to the etiopathogenesis of SCZ, such as pro-inflammatory cytokines (IL-1b, TNF-a), ischemia/anoxia, and dopamine, induce Hmox1 in mammalian astroglia (Mehindate et al. 2001, Schipper 2004b, Schipper et al. 1999). The putative role of HO-1 in SCZ is further supported by numerous reports of hyperbilirubinemia and increased urinary bilirubin metabolites in patients with SCZ and acute psychotic disorder (Bach et al. 2010, Miyaoka et al. 2000, Miyaoka et al. 2005, Müller et al. 1991, Yasukawa et al. 2007). In a recent study, HMOX1 overexpression in peripheral blood was determined with high cross validation accuracy to be a robust predictor of responsiveness to antipsychotic medications in SCZ patients (Sainz et al. 2018). Furthermore, lymphoblastoid cell lines (LCL) derived from SCZ patients exhibit significantly higher levels of HMOX1 induction than LCLs from healthy controls, at both baseline and in response to dopamine stimulation (Duan et al. 2018, Ifhar et al. 2019). Increased brain HO-1 mRNA and/or protein levels have been reported in several animal models used for SCZ research, including Schnurri-2 knock-out mice (Takao et al. 2013), phencyclidine- treated rats (Rajdev et al. 1998), MK-801-exposed mice (Zhao et al. 2018), and polyI:C-exposed rats (Ifhar et al. 2019). In GFAP.HMOX10-12m mice, engineered to overexpress HMOX1 in astrocytes during embryogenesis until 12 months of age, many of the pathological features characteristic of SCZ described above were recapitulated (Song et al. 2017b, Song et al. 2012a, Song et al. 2012b, Tavitian et al. 2019).

121 In contradistinction to SCZ, idiopathic PD is a hypodopaminergic movement disorder of unclear etiology that afflicts 1-2% of persons over 65 years of age. Cardinal signs of this disease include limb and axial rigidity, bradykinesia, rest tremor, and postural instability. Progressive loss of dopaminergic neurons in the substantia nigra (SN) pars compacta and the accumulation of fibrillary neuronal inclusions containing a-synuclein, ubiquitin, and tau (Lewy bodies) are hallmark pathological features of the illness (Lang 2011). As alluded to above, augmented brain iron sequestration, oxidative stress, mitochondrial damage, and macroautophagy are ‘core’ neuropathological features common to PD (Schipper et al. 2019). Lewy bodies within the PD SN are prominently decorated with HO-1 (Castellani et al. 1996, Schipper et al. 1998). Furthermore, HO-1 immunoreactivity is significantly augmented in GFAP- positive astrocytes of the PD SN relative to age-matched controls (Schipper et al. 1998). Proinflammatory cytokines, endogenous or environmental neurotoxins, and dopamine-derived reactive oxygen species are candidate inducers of HMOX1 in astrocytes of the PD SN (Mehindate et al. 2001, Schipper 1999). The local uptick in glial HO-1 activity may, in turn, accelerate iron deposition and mitochondrial complex I deficits documented in PD-affected neural tissues (Beal 1996, Schipper 2001). A recent study disclosed a fairly robust association between rs2071746 (A/T), a single nucleotide polymorphism that enhances HMOX1 promoter activity, and clinical PD (Ayuso et al. 2014). HO-1 protein is also reportedly elevated in the serum (Mateo et al. 2010) as well as saliva (Song et al. 2018) of PD subjects compared to age-matched, healthy controls. Commonly observed behaviours in animal models of PD include reduced locomotion (hypokinesia), poor performance on the pole test and rotarod (incoordination), decreased stride length (‘marche-a-petit-pas’), and rigidity (Le et al. 2014). Hmox1 induction has similarly been observed in the brains of MPTP- and rotenone-treated mice, frequently invoked models of experimental parkinsonism (Chen et al. 2009, Innamorato et al. 2010, Pan et al. 2016). The upregulation of HO-1 may contribute to disease pathogenesis in these animal models because numerous neurochemical and pathological features of PD are recapitulated in GFAP.HMOX18.5- 19m mice overexpressing the human HO-1 transgene between 8.5 to 19 months of age (Song et al. 2017a).

122 Parkinsonism secondary to hypodopaminergia is commonly noted and anticipated in SCZ patients following treatment with neuroleptic agents that interfere with central dopaminergic transmission (Bergouignan and Regnier 1954, Steck 1954). More enigmatic is the over- representation of parkinsonian signs (e.g. bradykinesia, rigidity, tremor) in a significant proportion of young, drug-naïve schizophrenics at first psychotic episode relative to control populations (Caligiuri et al. 1993). Along similar lines, while psychosis emerging in PD subjects in the course of L-dopa replacement is understandable, spontaneous hallucinosis (a pro- dopaminergic symptom responsive to neuroleptics) occurring in non-medicated persons with idiopathic PD and dementia with Lewy bodies (Ffytche et al. 2017, Snow and Arnold 1996), classical hypodopaminergic states, is difficult to reconcile. In this study, behavioural assays germane to SCZ and PD were performed on GFAP.HMOX10-12m and GFAP.HMOX18.5-19m mice to further test the hypothesis that strategic timing of glial HMOX1 overexpression is a major determinant of divergent disease states associated with pathological dopaminergic transmission. Our results underscore an unprecedented convergence of molecular and cellular mechanisms downstream of glial HMOX1 induction that may explain many of the paradoxical and overlapping behavioural manifestations of SCZ and PD. 12.3. Chapter 2 Materials and Methods Animal Husbandry All experimental protocols pertaining to the use of mice in this study (Protocol Number: 2001- 2739) were approved by the Animal Care Committee of McGill University, in accordance with the guidelines of the Canadian Council on Animal Care. All mice were bred and cared for in the Animal Care Facility at the Lady Davis Institute for Medical Research (Jewish General Hospital). Mice, housed 2-5 per cage, were kept at a room temperature of 21 ± 1°C with a 12h light/dark schedule and ad libitum access to food and water. Generation of GFAP.HMOX1 transgenic mice The transgene cascade in all GFAP.HMOX1 mice (Friend virus B background) leads to activation of the human HO-1 coding sequence through the upstream promoter drive of glial fibrillary acidic protein (GFAP) and the valve-controller of tetracycline (Tet)-Off system activator (tTA) (Song et

123 al. 2017a, Song et al. 2012a). This design permits selective targeting of HMOX1 gene expression to astrocytes and temporal control of transgene expression via doxycycline. GFAP.HMOX10-12m mice remained off doxycycline diets during embryogenesis and throughout their life, and received only regular rodent diet (2918 Teklad, Envigo, Madison, WI, USA). For GFAP.HMOX18.5-19m mice, doxycycline was provided through the diet (200 mg/kg, sterile, Bio-Serv, Frenchtown, NJ, USA) to breeding pairs and litters in order to prevent transgene expression. Between 8.5 and 19 months of age, the doxycycline diet was replaced with regular rodent diet allowing HMOX1 gene expression (Song et al. 2017a). Indices of general health, fur texture, body weight, and survival rates were monitored. No significant differences in these indices nor levels of HO-1 expression were noted between males and females therefore mice used for all experiments were of either sex, unless otherwise stated. Behaviour All behavioural tests were performed blinded at the Animal Facilities of either the Lady Davis Institute for Medical Research or the Douglas Research Centre Neurophenotyping Platform during the 12 h light cycle, unless otherwise stated. Open field test – The open field arena consisted of a Plexiglas box equipped with a system of infrared beams allowing for automated recording of horizontal movement, vertical movement, and stereotyped behaviour through the Versamax computer program (Accuscan Instruments, Columbus, OH, USA). Mice were individually placed in the open field and allowed a habituation period of 60 minutes after which the locomotor activity of the animal was measured and recorded for 30 minutes. The Ratios of TG to WT values were derived by re-analysis of a locomotor data set previously reported (Song et al. 2012a). PPI of the acoustic startle response – PPI was assessed in an automated seven-unit SR-LAB Startle Response System (San Diego Instruments Inc., San Diego, CA, USA). Each unit contains a cylindrical Plexiglas enclosure (diameter: 8 cm, length: 16 cm) mounted on a Plexiglas base inside a sound-attenuating chamber with adequate light and ventilation. Background noise (70 dB) and prepulse and pulse acoustic stimuli are provided by a speaker in the ceiling of the chamber. The whole-body acoustic startle response of the animal is transduced by a piezoelectric strain meter attached to the base. Stabilimeter readings are rectified, digitized on a 4095 scale, and recorded

124 by a computer. Startle magnitude was assessed with the presentation of a 120 dB, 30 msec stimulus. To assess PPI, a 30 msec prepulse stimulus preceded this startle stimulus. Prepulse intensities were 3, 6, 9, 12, and 15 dB above the background noise of 70 dB. Mice were placed into the Plexiglas enclosures and after a 5-minute acclimatization period, they were exposed to a total of 37 randomly-generated trials with an average inter-trial interval of 15 seconds. The first two trials were startle trials with no prepulse presented. Over the next 35 trials, animals received 10 more startle trials and 5 trials at each of the 5 prepulse intensities. No more than 2 trials of the same type occurred in succession. Percent PPI was calculated as: (startle magnitude on pulse alone – startle magnitude on prepulse-pulse / startle magnitude on pulse alone) x 100. Clozapine administration – Mice received an intraperitoneal injection of either clozapine (item number 12059, Cayman Chemical Company, Ann Arbor, MI, USA) dissolved in a vehicle solution of 3.4 ml saline with 0.6 ml lactic acid or the vehicle solution only. The clozapine dosage used was 1 mg/kg of body weight. Thirty minutes after injection of clozapine or vehicle, locomotor activity in the open field and PPI were assessed as described above. Male mice were used in this experiment because male, but not female, GFAP.HMOX1 mice exhibited PPI deficits in our original study (Song et al. 2012a). Three-chamber social interaction test – Social interaction was assessed in a transparent Plexiglas apparatus comprising three chambers (22 cm by 18 cm, each). Each of the left and right chambers contained a wire mesh cage with a diameter of 9 cm. A trial consisted of three 10- minute phases. In phase 1 (habituation phase), the test mouse was allowed to freely explore all three chambers for 10 minutes with both mesh cages empty. In phase 2 (social vs no object preference), a novel target mouse (unfamiliar to the test mouse) was placed in one of the mesh cages and the test mouse was allowed to freely explore all three chambers for 10 minutes (Fig. 2A, top panel). Placement of the novel mouse was counterbalanced across test animals. In phase 3 (novel vs familiar mouse preference) a second novel mouse was placed into the empty mesh cage. The original target mouse was left in its current position and was considered to be the “familiar mouse” in this phase. Phase 3 testing also consisted of a 10-minute exploration period as in the previous 2 phases (Fig. 2B, top panel).

125 Trials were conducted during the dark phase of a reverse light/dark cycle and were videotaped under red light (100W bulb) with an infrared camera positioned directly above the apparatus. Video analysis of each trial was performed with TopScan 2.0 (Clever Systems Inc, Reston, VA, USA). Entries into and cumulative time spent in each of the 3 chambers by the test mouse were automatically measured in each phase. Only male mice were used in this experiment. Nest building – Nest building was assessed as described by Deacon (Deacon 2006). Mice were placed in individual cages with corn cob bedding (irradiated 1/4", Teklad, Envigo, Madison, WI, USA), but no environmental enrichment material, approximately one hour before the dark phase. A cotton Nestlet (Ancare, Bellmore, NY, USA) was provided in each cage (weighed to 3.0 g/cage). Ad libitum access to food and water was also provided. The following morning, nests were photographed with a digital camera (Sony Cybershot, 12.1 megapixels, Tokyo, Japan). Nests were scored by a single investigator blinded to genotype and sex. A nest rating scale of 1-5 was used, with near-perfect nests assigned a score of 5 and nesting material nearly untouched assigned a score of 1 (Deacon 2006). Spontaneous alternation in the Y-maze – The testing apparatus consisted of a Y-shaped maze with three white opaque Plexiglas arms, designated as A, B, or C and spaced 120 degrees apart. Each arm measured 35 cm in length, 5 cm in width and 10 cm in height. Mice were individually placed in the center of the Y-maze and allowed to freely explore all 3 arms of the maze for 5 minutes (Fig. 4, top panel). There were no intra-maze cues and all arms of the maze received equal lighting. The total number and sequence of arm entries were recorded by a single experimenter blinded to mouse genotype. An arm entry was recorded when all 4 paws were inside the arm. After 5 minutes the mouse was returned to its cage. Spontaneous alternations were determined as the number of triads (consecutive entries in 3 different arms). Percent alternation was calculated as: (number of spontaneous alternations / chances to alternate) x 100 = (number of spontaneous alternations / total arm entries – 2) x 100. Bar-mouthing – Mice were transferred into individual cages 24 hours before testing. Cages contained corn cob bedding (irradiated 1/4", Teklad, Envigo, Madison, WI, USA), a cotton Nestlet (2"x2", Ancare, Bellmore, NY, USA), 20 g gray shredded paper bedding/nesting material

126 rolled into a ball (Tek-Fresh, Envigo, Madison, WI, USA), and ad libitum access to food and water. Cage conditions were identical for all mice. On day of testing, mice were brought into the sound- attenuated testing room in their home cages and were allowed to acclimatize to the room for 1 hour. After acclimatization, cage activity was recorded with an overhead video-camera for a 2- hour interval. Twelve cages were filmed simultaneously. Filming of the whole group occurred over 4 days, always at the same time of day. Bar-mouthing behaviour was assessed in the 00:05:00-01:05:00 segment of the recording. The number and duration of cage bar mouthing by each mouse within a 1-hour interval were quantified by a single experimenter blinded to genotype and sex. A mouse was considered to be engaged in bar-mouthing activity when it held a cage bar in its diastema and made sham-biting movements or wiped its open mouth along the bar. Gait analysis – Footprint test was adapted from Carter et al. and Glynn et al. (Carter et al. 1999, Glynn et al. 2005). Mice were given time to explore a Plexiglas runway 120 cm long, 12 cm wide, and 18 cm high (Fig. 7A) for 10 minutes prior to testing. The hind paws were coated in nontoxic paint. Mice were allowed to walk down the length of the runway as their hind footprints were tracked. A fresh sheet of white paper was placed on the floor for each run. Stride length was calculated as the average distance of forward movement between each stride (left side with left side; right side with right side) for at least 10 steps. Hind base width was calculated by measuring the average distance between left and right hind footprints. This was determined by measuring the perpendicular distance of a given step to a line connecting its opposite preceding and proceeding steps. Measurements are depicted in Figure 7B. The percentage of scuffled footprints (unclear, uneven, or messy footprint pattern) for each mouse was also calculated (see arrows in Fig. 7C). Rotarod – Rotarod test was performed as previously described (Li et al. 2010). Mice were placed on a rotarod (model 755, IITC Life Science Inc.) and the rod was accelerated from 5 to 45 rpm over 5 min. The speed, time and distance spent on the rod was recorded. If the mouse held onto the rod and rotated completely around at least two times, this was counted as a fall from the rod. Each mouse was tested 3 times (15-30 min inter-trial interval). The current data set

127 represents a re-analysis (average of 3 time trials) of rotarod data previously reported (Song et al. 2017a). Pole test – Pole test was adapted from Matsuura et al. (Matsuura et al. 1997). Mice were positioned near the top of the pole, measuring 50 cm high and 9 mm in diameter, facing upward. Their ability and the time it takes to turn 180º (T-turn) and climb down the pole was recorded (see Fig. 8D). The average of three trials was reported. A novel, binary (0 or 1) scoring system was created to assess motor impairments not reflected by time recorded. Categories surveyed included sliding (1 point), greater than 3 pauses (1 point), lack of tail grip (1 point), poor T-turn (1 point) and direction reversal from downward to upward (1 point). Points were calculated for each mouse tested, with greater point scores denoting worse locomotion. Average scores were calculated for WT and TG mice. Buried pellet test – The buried pellet test was adapted from (Lehmkuhl et al. 2014). One week prior to testing, mice were given 1-2 pieces of the pellets to be used during the test (piece of sweetened cereal) for three consecutive days to avoid neophobic nature of mice (Lehmkuhl et al. 2014). At least 1 hour prior to testing, mice were restricted from food and placed in a novel cage with 3 cm high of clean corn cob bedding (irradiated 1/4", Teklad, Envigo, Madison, WI, USA). At testing, mice were briefly removed from the cage as a pellet was buried in the bedding, and then returned to their testing cage. The time for mice to uncover the pellet was recorded. If the pellet was not uncovered within 5 minutes, the trial was ended and a time of 300 s was noted. For the vision-based surface pellet trial (control), the same procedure was followed except that the pellet was placed on top of the bedding rather than being buried within it (see black circle in Fig. 9A). Statistical analysis All data are expressed as means ± standard error of the mean (SEM). Statistical significance between control and experimental values was determined using Student’s t test (unpaired, 2- tailed, 95% confidence interval), one-way ANOVA followed by Newman–Keuls post hoc multiple- comparison test, or two-way ANOVA with Bonferroni correction. To calculate the standard error

!" of ratios, the error propagation method was utilized with the following formula: = |"|

128 !$ !& #( )% + ( )% ; where Q = a/b and 'Q is the standard error of Q. Statistical significance was set $ & at p < 0.05. 12.4. Chapter 2 Results The GFAP.HMOX10-12m mouse model of SCZ GFAP.HMOX10-12m TG mice showed increased locomotor activity and stereotypy in the open field test compared to wild-type (WT) control mice (Fig. 1A-F). Acute intraperitoneal administration of the atypical antipsychotic clozapine (1mg/kg) significantly decreased the hyperlocomotor behaviour and stereotypy in TG mice (Fig. 1G-L) without affecting WT locomotion (data not shown). A trend towards improvement of prepulse inhibition of the acoustic startle response (PPI) in TG mice by clozapine administration (1mg/kg, i.p.) did not reach statistical significance (p = 0.06) (Fig. 2). GFAP.HMOX10-12m TG mice did not differ from their WT counterparts in their preference for the novel target mouse vs the empty cage (sociability) in phase 2 of the three-chamber social interaction test (Fig. 3A). Phase 3 testing in the three-chamber paradigm revealed decreased social novelty preference in TG mice, evidenced by a significantly higher amount of time spent with the familiar mouse than with the novel stranger mouse (p < 0.05 relative to WT controls) (Fig. 3B). Relative to WT controls, GFAP.HMOX10-12m TG mice exhibited a highly significant impairment in nest building (p = 2.47 x 10-7 for males, p = 1.08 x 10-5 for females) (Fig. 4A, B). WT mice built near-perfect, fluffed, round nests with a crater-like wall confined to one quadrant of the cage (Fig. 4A). This grade of nest building efficiency was not attained by any TG mouse (Fig. 4A, B). The spontaneous alternation task in the Y-maze revealed impaired short-term spatial working memory in GFAP.HMOX10-12m TG mice relative to WT counterparts (p < 0.05) (Fig. 5). Male GFAP.HMOX10-12m TG mice showed a significant increase in bar-mouthing bouts (p = 0.01) and duration (p = 0.03) compared to WT mice (Fig. 6). A similar increase was not observed in female GFAP.HMOX10-12m TG mice (p = 0.23 and p = 0.17 for bouts and duration, respectively) (Fig. 6). Bar-mouthing is a stereotypy developed by animals in captivity and is posited to reflect a desire to escape (Nevison et al. 1999).

129 The GFAP.HMOX18.5-19m mouse model of PD In contradistinction to the SCZ-like behavioural features accruing from early-life expression of glial HMOX1, induction of the transgene in GFAP.HMOX1 mice between 8.5 to 19 months of age engenders a neurophenotype consistent with parkinsonism. GFAP.HMOX18.5-19m mice at 19 months of age exhibited altered gait patterns, with greater percentage of scuffled footprints (p = 0.02) (Fig. 7B, C) and decreased hind base length and width (p < 0.01 and 0.02, respectively) (Fig. 7D, E). These findings are consistent with the shuffling gait (‘marche-a-petit-pas’) observed in human parkinsonism (Kalia and Lang 2015). GFAP.HMOX18.5-19m mice at 19 months of age also displayed locomotor incoordination, as documented in the rotarod and pole tests (Fig. 8). GFAP.HMOX18.5-19m mice at 19 months of age performed significantly worse than age-matched WT controls in terms of speed (p < 0.001), time (p < 0.001) and distance (p = 0.01) spent on the rotarod (Fig. 8A-C). Though no significant differences were found between WT and GFAP.HMOX18.5-19m mice in terms of time to orient downwards on the pole (p = 0.38) or time to descend the pole (p = 0.49) (Fig. 8D, E), a novel scoring system revealed significant locomotor deficits in the GFAP.HMOX18.5-19m mice (Fig. 8F). Factors taken into consideration included sliding, more than 3 pauses, no tail grip, poor T-turn (180° turn), and direction reversal, with a higher score representing a worse performance. The average score for WT and GFAP.HMOX18.5-19m mice was 1.45 and 2.77, respectively (p = 0.02) (Fig. 8G). In addition to locomotor testing, we analyzed olfactory behaviour inasmuch as anosmia (loss of sense of smell) is a common, often pre-motor, symptom of PD (Kalia and Lang 2015). In the buried pellet test, 19-month old GFAP.HMOX18.5-19m mice took significantly more time to sniff and retrieve a buried cereal pellet compared to age-matched WT controls (p = 0.02) (Fig. 9). WT and GFAP.HMOX18.5-19m mice did not differ significantly in the visual-based surface pellet retrieval test (control; p = 0.60) confirming impaired olfaction in the GFAP.HMOX18.5-19m mice. 12.5. Chapter 2 Discussion Further to our previous documentation of molecular, morphological, and behavioural features relevant to SCZ and PD in GFAP.HMOX10-12m and GFAP.HMOX18.5-19m TG mice, respectively (Song

130 et al. 2017a, Song et al. 2012a), we subjected these two mouse models to a battery of additional behavioural tests germane to these disorders. GFAP.HMOX10-12m TG mice exhibit hyperkinesia, elevated stereotypy in the open field, increased cage bar-mouthing, impaired nest building, reduced preference for social novelty, and impaired short-term spatial working memory. These behaviours relate to the positive, negative and cognitive symptom domains described in human SCZ (Powell and Miyakawa 2006). The hyperlocomotor behaviour and augmented stereotypy in these mice are ameliorated by treatment with the atypical antipsychotic clozapine, conferring predictive validity to our model. We have previously reported deficient PPI in male GFAP.HMOX10-12m TG mice (Song et al. 2017b, Song et al. 2012a). Administration of clozapine at a dose of 1mg/kg in the present study engendered a trend towards improvement of PPI in GFAP.HMOX10-12m mice which fell short of statistical significance. The hyperkinesia, stereotypy, and possibly other neurobehavioural abnormalities documented in GFAP.HMOX10-12m mice are likely due to the associated elevations in basal ganglia dopamine and serotonin concentrations we previously reported in these mice (Song et al. 2012a). This is in contrast to the nigrostriatal hypodopaminergia observed in GFAP.HMOX18.5-19m mice (Song et al. 2017a) and associated with gait, locomotor, and olfactory behavioural deficits relevant to human PD. Contrary to the opposing dopaminergic and behavioural profiles in these two models, the ‘core’ neuropathological tetrad resulting from sustained or repeated upregulation of HMOX1 in astrocytes described above, viz. increased unregulated brain iron deposition, elevated oxidative stress, mitochondrial membrane damage, and macroautophagy, is common to both GFAP.HMOX10-12m and GFAP.HMOX18.5-19m mice (Cressatti et al. 2019, Song et al. 2017a, Song et al. 2012a, Song et al. 2012b). These observations, as well as the amelioration of HO-1-dependent locomotor deficits after treatment with the iron chelator, deferiprone, (Song et al. 2017a) suggest augmented canonical activity of HO-1 in the brains of GFAP.HMOX1 mice. Within the cellular stress response system and as part of the protective vitagene network, HO-1 acts as a sensor of cellular oxidative stress and a modulator of redox homeostasis (Calabrese et al. 2010). However, the activity of HO-1 is Janus-faced and can promote either

131 protection or toxicity in stressed cells (Schipper et al. 2019). The local redox microenvironment, the strength and duration of HO-1 upregulation, and the cell types it is expressed in determine which effect prevails (reviewed in [Schipper et al. 2019]). In central nervous system (CNS) disorders, induction of HO-1 may be neuroprotective in an acute setting as in the case of cerebral hemorrhage (Chen-Roetling et al. 2017, Chen-Roetling et al. 2015), but neurotoxic when chronically overexpressed (Schipper et al. 2019). The impact of chronic glial HO-1 overexpression in our GFAP.HMOX10-12m and GFAP.HMOX18.5-19m mice is predominantly neurodystrophic. To the extent that GFAP.HMOX1 mice simulate bonafide pathways of human disease, data compiled from both models raise the intriguing notion that comparable sets of stressors and convergent downstream mechanisms elicit either early-onset neurodevelopmental conditions (e.g. SCZ) or later-life neurodegenerative disorders (e.g. PD), contingent on whether the glial HO- 1 reaction is evoked before or after maturation of salient dopaminergic or other circuitry (Fig. 10). The shared transduction pathway and overlapping (core) neuropathological features common to both GFAP.HMOX1 mouse models may help resolve some of the vexing clinical paradoxes between SCZ and PD outlined above. The GFAP.HMOX1 mouse teaches that a parallel cascade of cytopathological changes precipitated by astroglial HMOX1 induction has opposite effects on dopaminergic transmission depending on the temporal window of expression. Although ‘net’ hyperdopaminergia and hypodopaminergia accrue, respectively, from glial HMOX1 induction in the maturing and adult brain (commensurate with the ages of onset of SCZ and PD), regional differences in the susceptibility of dopaminergic circuitry to the trophic and degenerative influences of glial HO-1 hyperactivity may allow the simultaneous expression of mixed SCZ and PD traits within affected individuals. This conjecture is supported by a panoply of clinical, genetic, and neuropathological observations in humans and experimental animals: (i) There is frequently simultaneous occurrence of positive (subcortical-frontal hyperdopaminergic) and negative (hypodopaminergic ‘hypofrontality’) symptoms in persons with SCZ (Winograd-Gurvich et al. 2006). (ii) In PD, hyposmia (diminished sense of smell) may be associated with augmented numbers of dopaminergic neurons in the olfactory bulb (Huisman et al. 2004). (iii) Lewy body pathology characteristic of hypodopaminergic conditions is over-represented in patients with late-onset

132 SCZ (Nagao et al. 2014); (iv) Re-emergence of childhood stuttering, a pro-dopaminergic state (Wu et al. 1997), may complicate early PD (Shahed and Jankovic 2001). (v) Axo-dendritic collapse, synaptic vesicle coalescence, mitophagy, and gliodystrophies, i.e. ultrastructural markers of neurodegeneration, occur in the SCZ-affected brain parenchyma (Kolomeets and Uranova 2010). (vi) There may be marked hemispheric disparities in dopamine concentrations and dopamine receptor densities in PD and SCZ (Mehler-Wex et al. 2006). (vii) Dopamine pathways in PD and SCZ are susceptible to the trophic and dystrophic influences of environmental stimuli (Tomas et al. 2015). (viii) There is evidence for concurrent trophic and degenerative processes in the brains of immature and aging GFAP.HMOX1 mice (Song et al. 2017a, Song et al. 2012a). (ix) Hypertrophic dopaminergic collaterals have been demonstrated in the striatum of animals with experimental parkinsonism (Arkadir et al. 2014). (x) Pathological circling behaviour (stereotypy), reflecting asymmetric basal ganglia dopamine levels, has been documented in human SCZ (Bracha 1987), idiopathic PD (Bracha et al. 1987), the GFAP.HMOX10-12m mouse model of SCZ (Song et al. 2012a), and the GFAP.HMOX18.5-19m mouse model of parkinsonism (Song et al. 2017a). (xi) Spontaneous conversion from early-life hyperdopaminergia with excessive exploratory behaviour to late-life hypodopaminergia and reduced exploratory behaviour has been reported in the LRRK G2019S knock-in mouse model of familial PD (Sossi et al. 2010, Volta et al. 2017). Heterogeneity in the involvement of central dopaminergic circuitry in disease states may be the rule rather than the exception as even single symptoms linked to aberrant dopamine transmission, such as hallucinosis, may correlate with highly disparate neuroanatomical signatures in subjects with distinct neurodevelopmental and neurodegenerative disorders (Rollins et al. 2019). These counterintuitive clinical observations raise the possibility that, within a given individual, the nigrostriatal dopaminergic pathways subserving locomotion and the mesolimbic/mesocortical dopamine circuitry mediating psychosis may be differentially impacted by disease (PD or SCZ) to simultaneously curtail and enhance dopaminergic neurotransmission in a region-specific manner. Our findings suggest that perinatal stressors activating the glial HO-1 cascade before the maturation of nigrostriatal and mesolimbic pathways promote “hypertrophy” of dopaminergic circuitry (mediated by induction of Nurr1, Pitx3, etc.), alongside relatively minor degenerative

133 changes, culminating as a ‘net’ neurodevelopmental hyperkinesia in early adulthood. Contrariwise, stressors acting upon established (‘hard-wired’) dopaminergic projections later in life yield phenotypes that are exclusively degenerative in nature. Innovation Our ability to model major aspects of SCZ and idiopathic PD in young and aging GFAP.HMOX1 mice suggest that these disorders may represent discrete, maturation-dependent neurophenotypes along a single etiopathogenetic continuum. This evidence helps resolve the ‘great dopamine paradox’ inasmuch as regional differences in the vulnerability of dopaminergic circuitry to the trophic and degenerative effects downstream of glial HMOX1 induction may favor the concomitant expression of mixed SCZ and PD traits within affected individuals. Suppression of the glial HO-1 response to stressors at strategic time points may prevent or arrest the progression of dopamine-dependent neuropsychiatric and neurodegenerative conditions. Acknowledgements The authors thank Daniel Gabbay and Caroline Anton for assistance with data collection, Goldy Mansourian for assistance with behavioural testing, Jean Marcotte and Isabelle Dubé for filming of cage activity, the laboratory of Dr. Andrea LeBlanc for providing the Y-maze apparatus, Sara Marier and Eva S. Nkurunziza for assistance with mouse genotyping and Lamin Juwara for advice on statistical analyses. Author Disclosure Statement H.M.S. is an officer of HemOx Biotechnologies (Montreal). A.T., M.C., W.S., A.S., A.Z.T., A.L., and C.G. have no competing financial interests to declare. Funding Information This work was supported by the Canadian Institutes of Health Research (Grant MOP-68887; awarded to H.M.S.) and the Fonds de la recherche en santé du Québec joint with Parkinson Canada (Grant No. 257822; awarded to M.C.).

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139 Snow RE, Arnold SE. 1996. Psychosis in Neurodegenerative Disease. Semin Clin Neuropsychiatry 1:282-293. Song L, Song W, Schipper HM. 2007. Astroglia overexpressing heme oxygenase-1 predispose co- cultured PC12 cells to oxidative injury. J Neurosci Res 85:2186-2195. Song W, Cressatti M, Zukor H, Liberman A, Galindez C, Schipper HM. 2017a. Parkinsonian features in aging GFAP.HMOX1 transgenic mice overexpressing human HO-1 in the astroglial compartment. Neurobiol Aging 58:163-179. Song W, Kothari V, Velly AM, Cressatti M, Liberman A, Gornitsky M, Schipper HM. 2018. Evaluation of salivary heme oxygenase-1 as a potential biomarker of early Parkinson's disease. Mov Disord 33(4):583-591. Song W, Tavitian A, Cressatti M, Galindez C, Liberman A, Schipper HM. 2017b. Cysteine-rich whey protein isolate (Immunocal(R)) ameliorates deficits in the GFAP.HMOX1 mouse model of schizophrenia. Free Radic Biol Med 110:162-175. Song W, Zukor H, Lin SH, Hascalovici J, Liberman A, Tavitian A, Mui J, Vali H, Tong XK, Bhardwaj SK, Srivastava LK, Hamel E, Schipper HM. 2012a. Schizophrenia-like features in transgenic mice overexpressing human HO-1 in the astrocytic compartment. J Neurosci 32:10841-10853. Song W, Zukor H, Lin SH, Liberman A, Tavitian A, Mui J, Vali H, Fillebeen C, Pantopoulos K, Wu TD, Guerquin-Kern JL, Schipper, HM. 2012b. Unregulated brain iron deposition in transgenic mice over-expressing HMOX1 in the astrocytic compartment. J Neurochem 123:325-336. Sossi V, de la Fuente-Fernandez R, Nandhagopal R, Schulzer M, McKenzie J, Ruth TJ, Aasly JO, Farrer MJ, Wszolek ZK, Stoessl JA. 2010. Dopamine turnover increases in asymptomatic LRRK2 mutations carriers. Mov Disord 25:2717-2723. Steck H. 1954. [Extrapyramidal and diencephalic syndrome in the course of largactil and serpasil treatments]. Ann Med Psychol (Paris) 112:737-744. Takao K, Kobayashi K, Hagihara H, Ohira K, Shoji H, Hattori S, Koshimizu H, Umemori J, Toyama K, Nakamura HK, Kuroiwa M, Maeda J, Atsuzawa K, Esaki K, Yamaguchi S, Furuya S, Takagi T, Walton NM, Hayashi N, Suzuki H, Higuchi M, Usuda N, Suhara T, Nishi A, Matsumoto M, Ishii S, Miyakawa T. 2013. Deficiency of Schnurri-2, an MHC Enhancer Binding Protein, Induces Mild Chronic

140 Inflammation in the Brain and Confers Molecular, Neuronal, and Behavioral Phenotypes Related to Schizophrenia. Neuropsychopharmacology 38:1409-1425. Tavitian A, Song W, Schipper HM. 2019. Dentate Gyrus Immaturity in Schizophrenia. Neuroscientist:1073858418824072. Tomas D, Prijanto AH, Burrows EL, Hannan AJ, Horne MK, Aumann TD. 2015. Environmental modulations of the number of midbrain dopamine neurons in adult mice. J Vis Exp:52329. Volta M, Beccano-Kelly DA, Paschall SA, Cataldi S, MacIsaac SE, Kuhlmann N, Kadgien CA, Tatarnikov I, Fox J, Khinda J, Mitchell E, Bergeron S, Melrose H, Farrer MJ, Milnerwood AJ. 2017. Initial elevations in glutamate and dopamine neurotransmission decline with age, as does exploratory behavior, in LRRK2 G2019S knock-in mice. Elife 6. Winograd-Gurvich C, Fitzgerald PB, Georgiou-Karistianis N, Bradshaw JL, White OB. 2006. Negative symptoms: A review of schizophrenia, melancholic depression and Parkinson's disease. Brain Res Bull 70:312-321. Wu JC, Maguire G, Riley G, Lee A, Keator D, Tang C, Fallon J, Najafi A. 1997. Increased dopamine activity associated with stuttering. Neuroreport 8:767-770. Yasukawa R, Miyaoka T, Yasuda H, Hayashida M, Inagaki T, Horiguch J. 2007. Increased urinary excretion of biopyrrins, oxidative metabolites of bilirubin, in patients with schizophrenia. Psychiatry Res 153:203-207. Zhao J, Liu X, Huo C, Zhao T, Ye H. 2018. Abnormalities in Prefrontal Cortical Gene Expression Profiles Relevant to Schizophrenia in MK-801-Exposed C57BL/6 Mice. Neuroscience 390:60-78.

141 12.7. Chapter 2 Figures

Figure 1

Figure 1. Increased open field locomotor activity and stereotypy in GFAP.HMOX10-12m TG mice (A-F) and their attenuation by 1 mg/kg, i.p., clozapine (G-L). (A) Movement bouts (ratio of TG to WT). (B) Horizontal activity counts (ratio of TG to WT). (C) Total distance traveled (ratio of TG to WT). (D) Stereotypy counts (ratio of TG to WT). (E) Stereotypy bouts (ratio of TG to WT). (F) Time spent in stereotypical behaviour (ratio of TG to WT). (G) Movement bouts. (H) Time spent moving (second). (I) Total distance travelled (cm). (J) Stereotypy counts. (K) Stereotypy counts. (L) Time spent in stereotypical behaviour (second). N = 9-13. *, p < 0.05; ***, p < 0.001. Error bars indicate SEM. Cl, clozapine; GFAP, glial fibrillary acidic protein; SEM, standard error of the mean; TG, transgenic; V, vehicle; WT, wild-type.

142 Figure 2

Figure 2. No significant effect of clozapine (1 mg/kg, i.p.) on PPI in GFAP.HMOX10-12m TG mice. Percent PPI of the acoustic startle response in GFAP.HMOX10-12m TG mice treated with either vehicle or clozapine. N = 10-11. Error bars indicate SEM. Cl, clozapine; V, vehicle; PP, prepulse intensity above background (dB); PPI, prepulse inhibition of the acoustic startle response.

143 Figure 3

Figure 3. Social behaviour of GFAP.HMOX10-12m TG mice in the three-chamber social interaction test. (A) Sociability. Top panel: schematic of testing apparatus. Bottom panel: time spent in chamber with an empty cage or a novel mouse. (B) Preference for social novelty. Top panel: schematic of testing apparatus. Bottom panel: time spent in chamber with novel mouse or familiar mouse. N = 12. *, p < 0.05; **, p < 0.01. Error bars indicate SEM. E, empty cage; F, familiar mouse; N, novel mouse.

144 Figure 4

Figure 4. Impaired nest building in GFAP.HMOX10-12m TG mice. (A) Typical nests built by WT (a) and TG mice (b-e) with nest scores of 5 (a), 4 (b), 3 (c), 2 (d) and 1.5 (e). (B) Nest scores of WT and TG mice. N = 20 WT (12M, 8F), 23 TG (12M, 11F). M, male; F, female.

145 Figure 5

Figure 5. Short-term spatial working memory is impaired in GFAP.HMOX10-12m TG mice. Top panel: schematic of testing apparatus. Bottom panel: percent alternation in the Y-maze spontaneous alternation task. N = 19 WT (9M, 10F), 23 TG (12M, 11F). *p<0.05. Error bars indicate SEM. M, male; F, female.

146 Figure6

Figure 6. Bar-mouthing behaviour of GFAP.HMOX10-12m TG mice. (A) Mouse engaged in bar- mouthing. (B) Bar-mouthing bouts in 1 hour. (C) Total time spent in bar-mouthing behaviour in 1 hour. N = 19 WT (9M, 10F), 23 TG (12M, 11F). *, p < 0.05. Error bars indicate SEM. M, male; F, female.

147 Figure7

Figure 7. Abnormal gait of parkinsonian GFAP.HMOX18.5-19m (TG) mice compared to WT. (A) Plexiglas runway schematic with dimensions. (B) Measurements for calculations of hind stride length and base width. (C) Visual representation of wild-type (WT) and TG hind footprints along runway. (D) Calculated percent scuffled (irregular; see arrows in C) footprints across entire runway. (E) The stride length from one ipsilateral hind paw to the next was measured and averaged. (F) The width between two hind paws was measured and averaged. N = 10 and 13 for WT and TG, respectively. *, p < 0.05; **, p < 0.01. Error bars indicate SEM.

148 Figure 8

Figure 8. Impaired locomotion of parkinsonian GFAP.HMOX18.5-19m (TG) mice compared to WT analyzed by pole test. Average of three trials on rotarod test plotted in terms of speed (A), time (B) and distance (C) spent on rod. (D) Pole test schematic (pole = 50 cm high). (E) Mice were placed on pole facing upward, with the time to turn 180° and orient downwards measured. (F) Time for mouse to descend the entire length of the pole was measured. (G) Performance of pole test was assessed using a novel binary system (see text for details), with a higher score representing a worse performance. (H) Average score for each category for WT and TG mice. N = 10 and 13 for WT and TG, respectively. *, p < 0.05; **, p < 0.01; ***, p < 0.001. Error bars indicate SEM.

149 Figure 9

Figure 9. Altered olfaction in parkinsonian GFAP.HMOX18.5-19m (TG) mice compared to wild-type (WT). (A) Olfactory test schematic, with food pellet (black circle) being either buried below 3 cm of bedding or placed atop surface of bedding (control). (B) Time measured to retrieve either buried or surface pellet. N = 10 and 13 for WT and TG, respectively. *, p < 0.05. Error bars indicate SEM.

150

Figure 10. ‘Transducer’ role of glial HMOX1 in SCZ and PD. Activation of the astroglial HO-1 cascade by perinatal stressors prior to the maturation of central dopaminergic pathways promotes net ‘hypertrophy’ of these circuits culminating as a neurodevelopmental hyperkinesia and psychosis (e.g. SCZ) in early adulthood (top). Stressor-mediated induction of glial HMOX1 later in life circumvents the developmental anomalies and engenders a neurophenotype which is predominantly degenerative in nature and characterized by subcortical hypodopaminergia and parkinsonism (bottom). See text for details. Thin black arrows denote pathways supported by

151 the literature. Thick grey arrows indicate increased or decreased levels or expression. Δ, change; ?, mechanism unknown; CNS, central nervous system; CO, carbon monoxide; DA, dopamine; DAT, dopamine transporter; Fe2, ferrous iron; GABA, gamma-aminobutyric acid; GSH, glutathione; HO- 1, heme oxygenase-1; NVC, neurovascular coupling; OS, oxidative stress; PD, Parkinson’s disease; S129-P, Serine 129 phosphorylated (pathological); SCZ, schizophrenia; TH, tyrosine hydroxylase. (Modified from (Song W. et al. 2017a, Song W. et al. 2017b, Song W. et al. 2012a), with permission).

152 13. Transition 2: Elucidating Altered MicroRNA Profiles in the GFAP.HMOX18.5-19m Mouse Model of Parkinson Disease Chapters 1 and 2 present evidence in support of the GFAP.HMOX18.5-19m mouse as a robust model system of human Parkinson disease (PD). Next, we aimed to elucidate alterations in microRNA (miRNA) profiles in these newly-characterized parkinsonian mice. Extensive literature exists outlining miRNAs changes in many neurodegenerative conditions, including PD (see Section 8.3). The study described in Chapter 3 builds upon previous work that we conducted looking at miRNA profiles in HMOX1-transfected primary rat astrocytes (Lin et al. 2015). In this 2015 study, we identified three significantly upregulated miRNAs and six significantly downregulated miRNAs (Lin et al. 2015). Moreover, the effects of HMOX1 induction on these glial miRNA profiles were abrogated by a competitive heme oxygenase (HO) inhibitor, an iron chelator and a carbon monoxide (CO) antagonist. These results directly implicate HO-1 as well as products of the HO-1- catalyzed heme degradation pathway, iron and CO, as contributors to the dysregulation of these aberrant miRNA profiles (Lin et al. 2015). While the 2015 study was conducted in vitro, Chapter 3 surveys miRNA expression alterations in intact GFAP.HMOX18.5-19m mice. The miRNAs identified in the 2015 study were linked to oxidative stress, whereas the next chapter links altered miRNAs to PD, most notably α- synuclein-targeting miR-153 and miR-223, in brain and beyond.

153 14. Chapter 3: Glial HMOX1 Expression Promotes Central and Peripheral α-Synuclein Dysregulation and Pathogenicity in Parkinsonian Mice

Published in GLIA (2019).

Author List: Marisa Cressatti1,2, Wei Song1, Ariana Z. Turk1,3, Laurianne R. Garabed1,3, Joshua A. Benchaya1,3, Carmela Galindez1, Adrienne Liberman1, and Hyman M. Schipper1,2,3

1Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec H3T 1E2, Canada 2Department of Neurology & Neurosurgery, McGill University Montreal, Quebec H3G 1Y6, Canada 3Faculty of Medicine, McGill University Montreal, Quebec H3G 1Y6, Canada

Correspondence should be addressed to: Hyman Schipper, Lady Davis Institute, Jewish General Hospital, 3999 Cote Sainte-Catherine Road, Montreal, Quebec H3T 1E2, Canada. E-mail: [email protected]. Phone: 514-340-8222 ext. 25588. Fax: 514-340-7502.

Running Title: HO-1, a-synuclein, and parkinsonian mice

154 14.1. Chapter 3 Abstract a-Synuclein is a key player in the pathogenesis of Parkinson disease (PD). Expression of human heme oxygenase-1 (HO-1) in astrocytes of GFAP.HMOX1 transgenic (TG) mice between 8.5 and 19 months of age results in a parkinsonian phenotype characterized by neural oxidative stress, nigrostriatal hypodopaminergia associated with locomotor incoordination, and overproduction of a-synuclein. We identified two microRNAs (miR-), miR-153 and miR-223, that negatively regulate a-synuclein in the basal ganglia of male and female GFAP.HMOX1 mice. Serum concentrations of both miRNAs progressively declined in the wild-type (WT) and GFAP.HMOX1 mice between 11 and 19 months of age. Moreover, at each time point surveyed, circulating levels of miR-153 were significantly lower in the TG animals compared to WT controls, while a- synuclein protein concentrations were elevated in erythrocytes of the GFAP.HMOX1 mice at 19 months of age relative to WT values. Primary WT neurons co-cultured with GFAP.HMOX1 astrocytes exhibited enhanced protein oxidation, mitophagy and apoptosis, aberrant expression of genes regulating the dopaminergic phenotype, and an imbalance in gene expression profiles governing mitochondrial fission and fusion. Many, but not all, of these neuronal abnormalities were abrogated by small interfering RNA (siRNA) knockdown of a-synuclein, implicating a- synuclein as a potent, albeit partial, mediator of HO-1’s neurodystrophic effects in these parkinsonian mice. Overexpression of HO-1 in stressed astroglia has previously been documented in the substantia nigra of idiopathic PD and may promote a-synuclein production and toxicity by down-modulating miR-153 and/or miR-223 both within the CNS and in peripheral tissues.

Keywords: Astrocytes, dopamine, heme oxygenase-1, microRNA, Parkinson disease, oxidative stress, a-synuclein.

Main Points: • MicroRNA (miR-) 153 and miR-223 regulate a-synuclein in the brains and potentially peripheral tissues of WT and parkinsonian GFAP.HMOX1 mice. • The miR-153/miR-223/heme oxygenase-1/a-synuclein pathway may be a salient therapeutic target in PD.

155 14.2. Chapter 3 Introduction Idiopathic Parkinson disease (PD) afflicts 1-2% of the population over 65 years of age (de Lau and Breteler 2006, Shulman et al. 2011). The disease features progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta and striatum and formation of fibrillar inclusions (Lewy bodies and Lewy neurites) in this cell population (Braak et al. 2004, Hornykiewicz 1988). Lewy bodies and neurites contain a-synuclein, a 14-kDa protein normally localized to presynaptic terminals and the nuclear envelope which participates in soluble N- ethylmaleimide sensitive factor receptor (SNARE)-mediated exocytosis and synaptic vesicle transport (Fusco et al. 2016, Marques and Outeiro 2012). In PD brain, a-synuclein may adversely affect mitochondrial function and thereby contribute to the vulnerability of nigrostriatal dopaminergic neurons (Deas et al. 2016, Devi et al. 2008, Nakamura et al. 2008, Shavali et al. 2008, Subramaniam et al. 2014, Zhang et al. 2008). a-Synuclein protein is also detectable in cerebrospinal fluid (CSF) and in peripheral tissues and biofluids including red blood cells (RBCs), plasma, serum, and saliva (Malek et al. 2014). In PD and other synucleinopathies, soluble a- synuclein protein assembles into filamentous, b-sheet-rich conformations prone to aggregation. There is considerable evidence implicating oxidative reactions in a-synuclein aggregation (Deas et al. 2016, Goedert 2001) and hyper-phosphorylation of the protein in the formation of hallmark Lewy pathology (Anderson et al. 2006). Heme oxygenase-1 (HO-1) is a 32 kDa enzyme which degrades heme to biliverdin (which is subsequently converted to bilirubin by biliverdin reductase), carbon monoxide (CO), and free ferrous iron. The Hmox1 promoter contains numerous response elements which render the gene exquisitely sensitive to induction by a number of endogenous and exogenous stressors implicated in the pathogenesis of PD, including dopamine, MPTP-like xenobiotics, IL-1b, TNF-a, hydrogen peroxide, and heavy metals (Schipper and Song 2015). Although biliverdin and bilirubin have antioxidant properties, prolonged or repeated release of CO and free ferrous iron promote cellular injury by stimulating the production of reactive oxygen species (ROS) within mitochondrial and other cellular compartments (Schipper 2004, Schipper and Song 2015). Net amplification of neural oxidative stress was demonstrated by our laboratory in HMOX1- transfected rat astroglia and in conditional GFAP.HMOX1 mice engineered to selectively

156 overexpress human HO-1 in astrocytes (Schipper and Song 2015, Song et al. 2017). In the latter, expression of glial HMOX1 between 8.5 and 19 months of age elicits robust behavioural (motor incoordination), neurochemical (nigrostriatal hypodopaminergia, a-synuclein induction), and neuropathological (dopaminergic neuron degeneration, basal ganglia iron deposition, oxidative mitochondrial damage, mitophagy) features of parkinsonism (Song et al. 2017). In the PD substantia nigra, the proportion of glial fibrillary acidic protein (GFAP)-positive astrocytes that expresses immunoreactive HO-1 protein is increased almost 4-fold relative to normal control values, and HO-1 prominently decorates Lewy bodies within the diseased dopaminergic neurons (Schipper et al. 1998). Data from aging GFAP.HMOX1 mice (vide supra) indicate that glial HMOX1 induction stimulates a-synuclein synthesis by the dopaminergic neuronal compartment. However, the molecular mechanisms downstream of glial HO-1 hyperexpression that promote a-synuclein production and potential toxicity in GFAP.HMOX1 mice. Abundant evidence suggests that dysregulated microRNA (miR-) expression plays a pivotal role in developmental brain disorders, normal aging, and various neurodegenerative conditions, including PD (Basak et al. 2016, Kim et al. 2007, Lukiw 2007, Martinez 2017). We previously observed that HMOX1 transfection of primary rat astroglia impacts the expression profiles of specific miRNAs implicated in mitochondrial oxidative stress, fission-fusion, and macroautophagy (mitophagy) (Lin et al. 2015). Here, we ascertained (i) the roles of key miRNA candidates (miR- 153, miR-223) in the regulation of a-synuclein in GFAP.HMOX1 mice, (ii) whether exclusive overexpression of HO-1 in astrocytes impacts a-synuclein regulation in peripheral tissues, and (iii) the extent to which a-synuclein mediates the neurodystrophic effects of HO-1 in this model. Our findings identify astroglial HO-1 as a driver of central and peripheral synucleinopathies and a rational target for disease-modifying therapy in idiopathic PD. 14.3. Chapter 3 Materials and Methods 14.3.1. Animal husbandry The Animal Care Committee of McGill University, in accordance with the guidelines of the Canadian Council on Animal Care, has approved all experimental protocols pertaining to the use of mice in this study (Protocol Number: 2001-2739). All mice were bred and cared for in the Animal Care Facilities at the Lady Davis Institute for Medical Research. Mice were housed 2-5 per

157 cage and kept at a room temperature of 21 ± 1°C with a 12h light/dark schedule and ad libitum access to food and water. For GFAP.HMOX1 mice, the transgene cascade leads to activation of the human HO-1 coding sequence through the upstream promoter drive of GFAP and the valve- controller of tetracycline (Tet)-Off system activator (tTA) (Song et al. 2017). This design permits selective targeting of HMOX1 gene expression to the astrocytic compartment and temporal control of transgene expression via doxycycline. Doxycycline was provided through the diet (200 mg/kg, sterile, Bio-Serv, Frenchtown, NJ) to breeding pairs and litters in order to prevent transgene expression. Between 8.5 and 19 months of age, the doxycycline diet was replaced with regular rodent diet to induce HMOX1 gene expression (Song et al. 2017). Indices of general health, fur texture, body weight, and survival rates were monitored. No significant differences in these indices nor levels of HO-1 expression were noted between males and females therefore mice used for all experiments were of either sex. 14.3.2. PCR genotyping Crude extracts containing genomic DNA from tail biopsy specimens were recovered using the REDExtract-N-Amp Tissue PCR kit (Sigma-Aldrich) as previously described (Song et al. 2017, Song et al. 2012a). The primers used to amplify the glyceraldehyde 3-phosphate dehydrogenase (GAPDH) segment (385 bp fragment) were used as an internal control (Preisig-Muller et al. 1999). Postnatal day 1 (P1) neonates used to isolate primary astrocytes and neurons were offspring of homozygous wild-type (WT) or TG breeders. Genotypes of parental animals were determined via purification of tail genomic DNA using a modified protease-digestion protocol, followed by reverse transcriptase quantitative PCR (RT-qPCR) with SensiFAST SYBR Low ROX reagent (FroggaBio Inc) as previously described (Song et al. 2017). 14.3.3. Blood collection One hundred µL of whole venous blood was obtained from mice at 11, 14 and 17 months by lateral saphenous vein puncture, as previously described (Hem et al. 1998). For 19-month-old mice, blood was procured via cardiac puncture immediately prior to transcardial perfusion (see Section 14.3.4). Samples obtained without EDTA were left at room temperature for 1 hour to coagulate, followed by centrifugation at 10,000 x g for 5 min, and collection of supernatant (serum). All samples collected with EDTA were stored at -80°C until further processing. RBCs were

158 isolated from EDTA samples using Ficoll-Paque according to GE Healthcare’s manufacturer instructions, followed by centrifugation at 400 x g for 40 min. See Sections 14.3.8 and 14.3.11 for further processing of serum and RBC samples, respectively. 14.3.4. Surgical procedures Mouse brains were fixed by transcardial perfusion at 19 months of age, as previously described (Fenton et al. 1998, Song et al. 2017). For light microscopy, animals were perfused with 200 mL ice-cold saline and 250 mL cold 4% paraformaldehyde in 0.1 M phosphate buffered saline (PBS; pH 7.4). For RNA and protein assays, mouse brains were removed and frozen on dry ice immediately after perfusion with 200 mL ice-cold PBS and stored at -80°C until further processing. For primary cultures of astrocytes and neurons, P1 GFAP.HMOX1 TG and WT neonates were decapitated and cells were isolated from whole brain (except cerebellum) by mechanoenzymatic dissociation of cerebral tissue (see Section 14.3.5). 14.3.5. Primary cell isolation and co-culture P1 GFAP.HMOX1 TG and WT mouse pups were used to generate primary astrocyte and neuron cultures. Twenty minutes prior to dissection, mouse pups were separated from the mother. Mice were decapitated and astroglia or neurons were isolated by mechanoenzymatic dissociation (Chopra et al. 1997, Jones et al. 2012, Song et al. 2017, Vaya et al. 2007). Cells were grown in Kaighn’s Modification of Ham’s F-12 medium and high glucose DMEM (50:50 v/v) supplemented with 5% heat-inactivated horse serum, 5% heat-inactivated fetal bovine serum, and penicillin- streptomycin (50 U/ml and 50 mg/ml, respectively). Cells were seeded alone or in co-culture in either T-75 mm2 or T-25 mm2 flasks, 6-well plates, or Transwell Permeable Supports 24 mm Inserts (VWR) at a density of 1.0-1.2 x 106 cells/mL and incubated at 37°C in humidified 95% air-

5% CO2. Astroglial cultures were incubated initially for 6 h, after which they were vigorously shaken 18-20 times followed by replacement with fresh medium to remove adherent oligodendroglia and microglia from the astrocytic monolayers. The cultures were maintained under the above-mentioned conditions for 5-16 days at which time more than 90% of the cells comprising the monolayer were astrocytes or neurons (Chopra et al. 1997). On day 3, cytosine β- D-arabinofuranoside (Ara-C) (Sigma) was added to a final concentration of 3 μM to the neuronal cultures in order to prevent glial overgrowth. For co-cultures, astrocytes were seeded in

159 Transwell permeable membrane inserts (Costar) and suspended above the neurons which were grown in 6-well plates coated with poly-D-lysine, as previously described (Song et al. 2017). 14.3.6. Neuronal cell line culture BE(2)-M17 human neuroblastoma cells were used for miRNA mimic and inhibitor transfections. Cells were grown in T-25 mm2 flask for 2-4 days (reaching 80-90% confluency), followed by seeding into a 24-well plate at a density of 0.5 x 106 cells/ml. Cells were grown in Ham’s F12 and Earl’s MEM (50:50 v/v) supplemented with 10% heat-inactivated fetal bovine serum, 1% non- essential amino acids, 1% glutamine, and penicillin-streptomycin (50 U/ml and 50 mg/ml, respectively). 14.3.7. Cell transfection The HiPerFect Transfection Reagent kit (QIAGEN) was used to transfect M17 and primary cells according to the manufacturer’s instructions. MiRNA mimics and inhibitors for hsa-miR-153, hsa- miR-223, and small interfering RNA (siRNA) against a-synuclein were obtained from QIAGEN. AllStars Negative Control and miScript Inhibitor Negative Control siRNAs (chemically synthesized, single-stranded, modified RNA with no homology to any known mammalian gene) were used as negative controls in all mimic and inhibitor experiments, respectively (QIAGEN). Cells were incubated in standard medium under standard growth conditions (see Sections 14.3.5 and 14.3.6) until transfection. Prior to transfection, 3 μL HiPerFect Reagent was combined with 10 nM siRNA/mimic, mixed by vortexing, and incubated at room temperature for 10 min to allow the formation of transfection complexes. Complexes were added drop-wise onto the cells and grown in standard medium with low serum and without antibiotics for 6-18 h. The same protocol, with the exception of the incubation period, was used for treatment of primary GFAP.HMOX1 astrocytes and co-cultures with a-synuclein siRNA. All primary astrocytes and co-cultures were grown for a total of 18-48 h post transfection. All samples were harvested accordingly for further analysis via RT-qPCR, Western blot, or protein carbonylation assay. 14.3.8. Total RNA extraction, polyadenylation and cDNA synthesis Total RNA from each dissected brain region (substantia nigra and striatum), cell culture, or serum sample was extracted in Trizol according to the manufacturer’s instructions (Invitrogen). MiRNA polyadenylation was performed followed by cDNA synthesis using 2.5 μg of polyadenylated total

160 RNA with Mir-XTM miRNA First-Strand Synthesis Kit (Clonetech). For mRNA RT-qPCRs, first strand cDNA synthesis was performed using 2.0 μg of total RNA with the Transcriptor First-Strand cDNA

Synthesis Kit (Roche Diagnostics) and anchored-oligo-dT18 or random hexamer primer, with the resulting cDNA amplified by PCR (Song et al. 2009). 14.3.9. Reverse transcriptase quantitative PCR The Applied Biosystems 7500 Fast Real-Time PCR System (Life Technologies) was used to quantify miRNA and mRNA with SensiFast SYBR Lo-ROX kit (FroggaBio) according to the manufacturer’s instructions. Twenty-five ng of cDNA were quantified using the RT-qPCR Kit (Invitrogen). The forward and reverse primer sequences used to detect miRNA and mRNA were either designed with Primer Express Software, version 3.0 (Life Technologies), or obtained from AlphaDNA (Table 1). As an internal reference, RNU44 or snoRNA-202 miRNA and β-actin mRNA were probed (Table 1). Expression fold changes between groups were calculated using the delta delta cycle threshold (2-ΔΔCt) method relative to controls following normalization with levels of either RNU44 or snoRNA-202 miRNA or β-actin mRNA (Livak and Schmittgen 2001). For each miRNA and mRNA target, 5 WT and 5 TG mice were analyzed in vivo, and 3-5 litters each of WT and TG mice were analyzed in vitro. 14.3.10. Immunofluorescence Coronal brain sections (6 µm) were deparaffinized and rehydrated in a series of graded alcohol solutions followed by deionized water. Sections were incubated with polyclonal tyrosine hydroxylase (TH) antibody (1:100; Invitrogen) and monoclonal a-synuclein antibody (1:250; BD BioScience) or polyclonal phospho S129 a-synuclein antibody (1:50; Abcam), followed by goat anti-rabbit or horse anti-mouse Cys3- or FITC-labeled IgG (1:50-100; Jackson ImmunoResearch). DAPI was used to label nuclei (1:1000; Thermo Fisher). Sections were analyzed using a Carl Zeiss LSM 5 Pascal laser-scanning confocal imaging microscope, and images were analyzed using Velocity computer software. 14.3.11. Western blot M17 or primary cells were lysed with ice-cold RIPA buffer (150 nM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 50 mM Tris-HCl pH 8.0, 40 mM NaF, and protease inhibitors) and incubated on ice for 10 min. Adherent cells were detached and collected, followed by an incubation period of 30

161 min at 4°C with constant agitation. The cell suspension was centrifuged at 18894 x g (13,000 rpm) for 20 min at 4°C and the subsequent supernatant was stored at -80°C until further use. RBCs were lysed with a 1:10 water dilution (Barbour et al. 2008). The DC Protein Assay kit (Bio-Rad) was used to measure protein concentrations prior to Western blot analysis. Protein samples were boiled for 5 min in the presence of 4X SDS Loading Dye (0.2 M Tris-HCl pH 6.8, 0.2% SDS, 40% glycerol, 0.05 M EDTA pH 8.0, 0.04 μg/mL beta-mercaptoethanol) before electrophoresis on 10% SDS-PAGE and transferred to a polyvinylidene difluoride (PVDF) membrane with 0.2 μm pore size (Bio-Rad). Anti-a-synuclein mouse monoclonal antibody (BD Biosciences, Clone No. 42) at 1:1000 dilution and anti-mouse IgG HRP (Jackson ImmunoResearch) at 1:2000 were used to blot membranes. As an internal control, anti-actin monoclonal antibody (MediMabs, Clone No. C4) at 1:2000 was used to re-blot mildly stripped membranes. Clarity™ Western ECL Blotting Substrate was used for development and protein expression visualization (Bio-Rad). 14.3.12. Protein carbonylation assay Whole cell lysates were isolated from brain tissue with ice-cold RIPA buffer, as described above (see Section 14.3.11). Protein carbonyl content was assayed in brain tissue according to the manufacturer’s instructions (Abcam) using BSA as standards. First, 100 µl of sample containing 0.25 mg protein was treated with 10 µl Streptozocin (Sigma) and incubated at room temperature for 15 min, followed by centrifugation at 18894 x g (13,000 rpm) for 5 min. Pellets were discarded and 100 µl of 2,4-dinitrophenylhydrazine (DNPH) (Sigma) was added to supernatant, vortexed, and incubated at room temperature for 10 min. Thirty µl of 100% trichloroacetic acid (TCA) (American Chemicals Ltd.) was added to each sample, vortexed, and placed on ice for 5 min, followed by centrifugation at 18894 x g (13,000 rpm) for 2 min. Pellets were washed twice with ice cold acetone, sonicated in a bath for 1 min, incubated at -20°C for 5 min, and centrifuged at 18894 x g (13,000 rpm) for 2 min. Pellets were dissolved in 200 µL of 6 M guanidine hydrochloride (Sigma) solution, sonicated briefly and incubated at 60°C for 30 min to allow re-solubilization. Samples were transferred in duplicate to a 96-well plate and optical density was measured at 375 nm with a spectrophotometer (Bio-Rad). The carbonyl content was determined as C = [(OD 375 nm)/6.364) ´ (100)] nmol/well and expressed as nmol carbonyl per mg protein.

162 14.3.13. Experimental design and statistical analyses All experiments were designed to assess the effect in TG GFAP.HMOX1 mice and compared to WT mice (all Friend leukemia virus B [FVB] background) undergoing identical treatment and conditions. All data are expressed as means ± standard error of the mean (SEM). Student’s t-test was applied for all comparisons between two groups. For comparisons between three or more groups, either two-way analysis of variance (ANOVA) with Tukey’s post-hoc test (one dependent variable) or two-way multivariate ANOVA (MANOVA; two or more dependent variables) was used. For all analyses, the two-tailed alpha significance level was 5% (p < 0.05). 14.4. Chapter 3 Results 14.4.1. Effects of HO-1 on a-synuclein expression We previously showed that mid-to-late life overexpression of HMOX1 in GFAP.HMOX1 mice results in elevated levels of a-synuclein mRNA and protein in vivo and in primary astrocyte/neuron co-cultures (Song et al. 2017). Both a-synuclein and the pathological form of the protein, serine 129 phosphorylated-a-synuclein, were increased in TH-positive dopaminergic neurons and surrounding neuropil of the GFAP.HMOX1 SN compared to WT controls (Fig. 1A). Furthermore, dopamine exposure (1 or 25 µM) resulted in substantial increases in both HO-1 and a-synuclein protein levels in primary WT astrocytes, supporting the presence of a physiological HO-1-synuclein pathway (data not shown). 14.4.2. Oxidative stress in GFAP.HMOX1 mice Mitochondria-derived oxidative stress and a-synuclein aggregation may participate in a mutually-reinforcing positive feedback loop (Blesa et al. 2015). Protein carbonylation, an index of oxidative stress, was significantly enhanced in the GFAP.HMOX1 striatum compared to age- matched, WT controls (p < 0.0001) (Fig. 1B). This finding complements the previously observed elevations of manganese superoxide dismutase (MnSOD) mRNA and protein, markers of mitochondrial oxidative stress, in GFAP.HMOX1 mice (Song et al. 2017). 14.4.3. MiRNA expression profiles in GFAP.HMOX1 mice Based on a previous study employing miRNA microchip analyses of HMOX1- and sham- transfected rat astroglia (Lin et al. 2015), in conjunction with computer algorithms (TargetScan.org) identifying putative mRNA targets, 24 miRNAs were selected for validation by

163 RT-qPCR in substantia nigra and striatum of GFAP.HMOX1 mice and in primary astrocyte and neuron co-cultures (Fig. 2A). Our study focused on select miRNAs targeting genes that contribute to hallmark features of PD viz. a-synuclein aggregation (inclusion formation) (Fig. 2B, C) and degeneration of DA neurons (Fig. 2D, E). Two of three miRNAs targeting a-synuclein (miR-153 and miR-223) were previously identified as critical in other CNS diseases and therefore studied in greater depth. A third miRNA, miR-7, previously verified in human, mouse, and zebrafish and found to be especially enriched in the brain (Bak et al. 2008, Wienholds et al. 2005), was not included for further analysis here as it was not found to be significantly altered in GFAP.HMOX1 mice. In the earlier microchip assay (Lin et al. 2015), miR-153 expression trended downwards in HMOX1-transfected rat astroglia, whereas miR-223 showed no significant change. However, current validation via RT-qPCR confirmed downregulation of both miR-153 and miR-223 in our GFAP.HMOX1 mouse model (Fig. 2B, C; see Section 14.4.4). 14.4.4. miRNA regulation of a-synuclein MiR-153 and miR-223 were selected for analysis based on their putative a-synuclein target and the pivotal role of this protein in the formation of Lewy bodies. MiR-153 was significantly downregulated in the substantia nigra (p = 0.05) and striatum (p = 0.04), while miR-223 was significantly downregulated in the SN (p = 0.05) brain region of the GFAP.HMOX1 mice compared to age-matched, WT controls (Fig. 2B). Similarly, miR-153 and miR-223 were significantly down- modulated by glial HMOX1 in both astrocytes (p < 0.0001 for both miRNAs) and neurons (p = 0.023 and p < 0.0001, respectively) in our co-culture paradigm (Fig. 2C). The downregulation of these miRNAs in vivo and in vitro correlated with upregulation of a-synuclein in the intact basal ganglia in vivo (Fig. 1A), consistent with earlier in vitro findings (Song et al. 2017). As miR-153 has been well-documented to regulate a-synuclein (Doxakis 2010, Ji et al. 2017, Kim et al. 2013) and miR-223, to our knowledge, has never been previously studied as a potential regulator of a-synuclein, these two miRNAs were subjected to further analysis. M17 human neuroblastoma cells were selected for this phase of the study on account of their substantial endogenous levels of a-synuclein (Newman et al. 2013). First, the cells were transfected for 12 h with either a miR-153 or miR-223 mimic which effected significant augmentation of their respective expression levels relative to negative control siRNA

164 preparations (p < 0.0001) (Fig. 3A). Post-transfection, a-synuclein mRNA was significantly downregulated relative to the negative siRNA controls (p = 0.0006 and p = 0.02, respectively) (Fig. 3B). Decreased a-synuclein monomeric (p < 0.0001 for both miR-153 and miR-223 mimics) and oligomeric (p = 0.05 for miR-153 mimic only) protein expression was also observed by Western blot (Fig. 3C, D). In the ‘reverse’ experiment, M17 cells were transfected for 12 h with either a miR-153 or miR-223 inhibitor (siRNA), resulting in significant suppression of their expression levels compared to negative control siRNA preparations (p < 0.0001) (Fig. 3E). Post-transfection, levels of a-synuclein mRNA (p = 0.05 for miR-153, p = 0.04 for miR-223) (Fig. 3F) and monomeric (not significant) and oligomeric (p = 0.005 for miR-153 inhibitor only) protein (Fig. 3G, H) exhibited increases relative to the negative controls. For the M17 cells, data at 12 h post- transfection are presented because at this time point responses to treatment were optimal (plateaued), most consistent (least variability) relative to the other time points surveyed (see Section 14.3.7), and normally distributed. Next, we ascertained the magnitude of miR-153 and miR-223 expression longitudinally in the serum of WT and GFAP.HMOX1 mice (n = 7-13 per group) at 11, 14, 17, and 19 months of age. The concentrations of both miRNAs decreased over time regardless of genotype (Fig. 4A, B). Levels of miR-153 were significantly lower in TG serum compared to WT values at each time point (p = 0.001) (Fig. 4A). Moreover, 19 month-old TG mice displayed significantly increased levels of a-synuclein protein in RBCs, both in its monomeric (2.0-fold increase, p = 0.002) and oligomeric (1.5-fold increase, p = 0.004) forms, compared to WT preparations (Fig. 4C, D). The latter observations correspond with, and may hint at a mechanism responsible for, increases in a- synuclein protein concentrations reported in RBCs of PD patients (Matsumoto et al. 2017, Nakai et al. 2007, Vicente Miranda et al. 2017). In contrast to miR-153, the decline in serum miR-223 with age did not differ significantly between the TG and WT animals (p = 0.2) (Fig. 4B), suggesting that the relative contribution of miR-223 to peripheral a-synuclein dysregulation in this model is minimal. 14.4.5. miRNA regulation and the dopaminergic system As in the case of a-synuclein (Section 14.4.4), the expression profiles of cellular miRNAs targeting vital components of the dopaminergic system were found to be altered under the influence of

165 glial HMOX1. Pitx3, a transcription factor involved in dopaminergic neuron generation and maintenance, and the dopamine transporter, DAT, are putative targets of miR-133b. Nurr1, another transcription factor involved in dopaminergic neuron elaboration and survival, is a putative target of miR-145 (TargetScan) (de Mena et al. 2010, Kim et al. 2007, Xie et al. 2017). Both MiR-133b and miR-145 were significantly upregulated in the TG striatum compared to WT striatum (p = 0.004 and p = 0.05, respectively) and trended towards enhanced expression in the TG SN (Fig 2D). The latter changes correlated inversely with decreased expression of Pitx3, DAT, and Nurr1 mRNA in the TG striatum compared to WT striatum (Song et al. 2017). In complementary experiments, the expression of miR-133b and miR-145 was significantly increased in both cellular compartments of the TG astrocyte (p = 0.01 and p = 0.04, respectively) and neuron (p = 0.01 and p = 0.05, respectively) co-cultures compared to WT controls (Fig. 2E), and correlated inversely with decreased DA system gene expression profiles observed in vitro (Song et al. 2017). 14.4.6. Downstream effects of a-synuclein knockdown (i) Oxidative stress: In vitro and in vivo experiments indicate that increased neural oxidative stress may promote a-synuclein aggregation (Blesa et al. 2015, Paxinou et al. 2001). In turn, a-synuclein has been shown to directly contribute to ambient levels of oxidative stress (Hsu et al. 2000). In further support of this notion, siRNA knockdown of a-synuclein (Fig. 5A) effectively diminished protein carbonylation in primary TG astrocytes to WT levels (p < 0.0001; Fig. 5B). Twenty-four hour-transfection of primary co-cultures with siRNA against a-synuclein also engendered downregulation of MnSOD mRNA levels in neurons co-cultured with TG astrocytes (black bar) relative to negative control preparations (grey bar; p = 0.01) (Fig. 5C). For the primary astrocytes and astrocyte/neuron co-cultures, data at 24 h post-transfection are presented because at this time point responses to treatment were optimal (plateaued), most consistent (least variability) relative to the other time points surveyed (see Section 14.3.7), and normally distributed. Transfection with siRNA against a-synuclein also reduced MnSOD mRNA in neurons co-cultured with WT astrocytes (checkered bar) compared to negative control preparations (white bar; p = 0.0002) (Fig. 5C), suggesting that a-synuclein stimulates mitochondria-derived oxidative stress even under basal (WT) conditions. Consistent with previous observations (Song

166 et al. 2017), MnSOD mRNA expression levels were significantly elevated in negative control neurons co-cultured with TG astrocytes (grey bar) compared to negative control neurons co- cultured with WT astrocytes (white bar; p = 0.03) (Fig. 5C). (ii) The dopaminergic system: Transfection of primary co-cultures with siRNA against a- synuclein restored expression levels of genes involved in dopaminergic neuron generation/maintenance and dopamine metabolism, implicating a-synuclein as a mediator of dopaminergic system dysregulation under HMOX1 stress. After transfection with siRNA against a-synuclein, DAT and Pitx3 mRNA expression levels in neurons co-cultured with TG astrocytes (black bars) were restored to levels observed in negative control (white bars) or transfected (checkered bars) neurons co-cultured with WT astrocytes, while TH and Nurr1 mRNA expression levels in neurons co-cultured with TG astrocytes (black bars) were significantly increased relative to negative control preparations (grey bars; p = 0.03 and p = 0.02, respectively) (Fig. 6). Nurr1, Pitx3, and TH expression levels were significantly downregulated in negative control neurons co- cultured with TG astrocytes (grey bars) compared to negative control neurons co-cultured with WT astrocytes (white bars; p = 0.02, p = 0.05, p = 0.05, and p = 0.02, respectively) (Fig. 6), akin to previous observations (Song et al. 2017). (iii) Mitophagy: Primary co-cultures transfected with siRNA against a-synuclein impacted DJ-1 (PARK7) expression but had no significant effects on Parkin (PARK2) and PINK1 (PARK6). Parkin and PINK1 play important roles in mitophagy whereas DJ-1, a protein with chaperone-like activity, modulates a-synuclein aggregation via direct interaction (Zondler et al. 2014). Consistent with previous observations (Song et al. 2017), PINK1 mRNA expression was upregulated (p = 0.003), while DJ-1 mRNA significantly declined (p = 0.003), in negative control neurons co- cultured with TG astrocytes (grey bars) relative to neurons co-cultured with WT astrocytes (white bars) (Fig. 7A). After transfection with siRNA against a-synuclein, DJ-1 mRNA expression in neurons co-cultured with TG astrocytes (black bar) was upregulated relative to negative control preparations (white and grey bars; p < 0.001), while Parkin and PINK1 remained unchanged (Fig. 7A). (iv) Mitochondrial dynamics: Expression levels of genes involved in mitochondrial fusion and fission were considerably impacted by siRNA knockdown of a-synuclein. The imbalance

167 between fusion (Mfn1, Mfn2) and fission (DRP1) genes observed in negative control neurons co- cultured with TG astrocytes (grey bars) compared to those co-cultured with WT astrocytes (white bars) (Fig. 7B) corroborates previous observations in primary GFAP.HMOX1 co-cultures (Song et al. 2017). However, the pattern of downregulated fusion genes and upregulated fission genes seen here is more consistent with other parkinsonian animal models (Celardo et al. 2014, Henchcliffe and Beal 2008). The fact that a-synuclein overexpression induces mitochondrial fragmentation in several models (Pozo Devoto and Falzone 2017) is consistent with the enhancement of fission gene (DRP1) expression noted in the current study (p = 0.01). Anti-a- synuclein siRNA transfection of neurons co-cultured with TG astrocytes restored Mfn2 and DRP1 (Fig. 7B, black bars), and to a lesser extent Mfn1, mRNA expression. These findings strongly implicate a-synuclein as a mediator of HO-1’s dystrophic effects on mitochondrial dynamics in this paradigm. (v) Apoptosis: Primary co-cultures transfected with siRNA against a-synuclein had no significant effects on genes involved in apoptosis (p53, Bax, Bak), with the exception of Bcl2 which was significantly down-modulated only in the treated WT group (checkered bar; p = 0.01) (Fig. 7C). Similar to previous observations (Song et al. 2017), apoptotic gene expression levels (p53, Bax and Bak) were significantly upregulated in negative control neurons co-cultured with TG astrocytes (grey bars) relative to neurons co-cultured with WT astrocytes (white bars; p = 0.05, p = 0.001, and p = 0.04, respectively) (Fig. 7C). 14.5. Chapter 3 Discussion 14.5.1. The GFAP.HMOX1 mouse model of PD Selective overexpression of human HO-1 in astrocytes of GFAP.HMOX1 TG mice between 8.5 and 19 months of age results in behavioural, neuropathological, and molecular biological features consistent with parkinsonism (Song et al. 2017). The neurophenotype of these mice is characterized by: (i) glial and neuronal oxidative stress, increased tissue iron deposition, and aberrant mitochondrial function, fission/fusion and macroautophagy; (ii) locomotor incoordination and stereotypic behaviour; (iii) dystrophic and fewer dopaminergic neuronal perikarya in the SN and decreased striatal dopamine concentrations; (iv) downregulation of TH, DAT, LMX1b, Pitx3, and Nurr1 mRNA and/or protein in the affected basal ganglia; (v) early

168 synucleinopathy; and (vi) elevated GABA, GAD67, and reelin levels, as previously documented in early-stage human and experimental parkinsonism (Botella-Lopez et al. 2006, Emir et al. 2012, Oz et al. 2006). The current results further validate aging GFAP.HMOX1 mice as a parkinsonian model and yield the following novel observations: (i) Elevation of native and, notably, pathological (phospho129) forms of a-synuclein in the GFAP.HMOX1 striatum; (ii) increased protein carbonylation (oxidation) in the GFAP.HMOX1 striatum; (iii) diminished neural concentrations of a-synuclein-targeting miRNAs, miR-153 and miR-223, and confirmation of this novel a-synuclein regulatory pathway in human M17 neuroblastoma cells using molecular mimics and siRNA inhibitors of miR-153 and miR-223; (iv) progressive decline in serum miR-153 and miR-223 levels of both TG and WT mice; (v) significantly lower serum concentrations of miR- 153 at each time point surveyed and higher erythrocyte a-synuclein levels at 19 months in the GFAP.HMOX1 RBCs relative to WT values; (vi) upregulation of basal ganglia miR-133b and miR- 145 correlating with suppression of their Nurr1, Pitx3, and DAT mRNA targets in GFAP.HMOX1 mouse (Song et al. 2017) and human PD brain (Decressac et al. 2013, Kim et al. 2007); and (vii) siRNA knockdown evidence that a-synuclein contributes to brain protein carbonylation and Mnsod hyper-induction (oxidative stress), down-modulation of genes governing dopamine metabolism, and dysregulation of mitochondrial fission/fusion and mitophagy pathways in GFAP.HMOX1 mice. 14.5.2. MiRNA regulation of a-synuclein in GFAP.HMOX1 mice The upregulation of a-synuclein mRNA and protein in the brains of parkinsonian GFAP.HMOX1 mice recapitulates induction of the SNCA gene observed in the basal ganglia of human PD subjects (Baba et al. 1998, Grundemann et al. 2008). In the GFAP.HMOX1 mice, astroglial HO-1 overexpression engenders significant downregulation of both neural and circulating miR-153 and miR-223 which, in turn, de-repress the Snca gene in brain and potentially peripheral tissues (erythrocytes). Conserved binding sites for miR-153 and miR-223 were predicted to lie within the SNCA 3’UTR (partial complementarity) across species using TargetScan software, and both miRNAs are highly expressed in rodent and human brain (Farh et al. 2005, Tagliafierro et al. 2017). MiR-153 was confirmed to bind the 3’UTR of SNCA and suppress a-synuclein mRNA and protein levels (Doxakis 2010). MiR-153 and Snca mRNA exhibit highest expression levels in murine

169 midbrain (Doxakis 2010), and their dysregulation may adversely affect synaptic branching, long- term potentiation (neuroplasticity), and neurotransmission (Doxakis 2010). miR-153 has also been shown to protect dopaminergic neurons from cell death by interfering with MPP+-induced suppression of mTOR signaling (Fragkouli and Doxakis 2014), and MPP+-mediated increases in SNCA levels are regulated by miR-153 (Je and Kim 2017). A rare mutation within the miR-153 binding site in a patient with idiopathic PD has been reported (Kim et al. 2013). miR-153 is also significantly reduced in Alzheimer disease brains where it may play a role in the regulation of amyloid precursor protein expression (Liang et al. 2007, Long et al. 2012). Unlike miR-153, brain miR-223 has been largely investigated for its participation in neuronal maturation and glutamate sensitivity (Harraz et al. 2014) as well as neuroprotection via inflammatory response modulation (Harraz et al. 2014, Wang et al. 2014, Yang et al. 2015). Save for the downregulation of miR-7b in cultured GFAP.HMOX1 astrocytes, the miR-7 family, previously implicated in a-synuclein regulation (Doxakis 2010, Fragkouli and Doxakis 2014, Junn et al. 2009), remained minimally altered in GFAP.HMOX1 mouse tissues relative to WT values. In both the WT and GFAP.HMOX1 mice, we observed a progressive decline in serum miR- 153 and miR-223 concentrations between 11 and 19 months of age. These findings correlate with age-related increases in nigrostriatal and peripheral a-synuclein expression reported in humans and monkeys (Barbour et al. 2008, Chu and Kordower 2007, Daniele et al. 2018a, Daniele et al. 2018b, Matsumoto et al. 2017). MiR-153 levels were significantly lower in GFAP.HMOX1 serum than WT serum at each time point surveyed, suggesting that miR-153, more so than miR-223, may be responsible for upregulation of peripheral a-synuclein expression under pathological (parkinsonian) conditions. In support of this formulation, both monomeric and oligomeric forms of a-synuclein protein were significantly increased in RBCs of 19-month old GFAP.HMOX1 mice compared to age-matched WT mice, and as previously documented in human PD blood (Matsumoto et al. 2017, Nakai et al. 2007, Vicente Miranda et al. 2017). MiR-153 has been previously implicated in the neuroepithelial cell response to ethanol toxicity, likely accounting for the lower levels of miR-153 and higher blood cell a-synuclein mRNA concentrations observed in alcoholic subjects (Walker and Grant 2006). It remains unsettled whether the synucleinopathy in PD manifests itself concomitantly and independently in brain and periphery; whether SNCA is

170 first induced in peripheral tissues (e.g. the enteric nervous system) with centripetal, prion-like propagation of the protein to the brain stem; or whether pathological a-synuclein expression first implicates the brain with secondary dysregulation of a-synuclein signaling and homeostasis in systemic tissues. Our data may favor the latter hypothesis insofar as (i) selective overexpression of HMOX1 in astrocytes reduced serum concentrations of miR-153 and increased levels of a-synuclein in circulating erythrocytes and (ii) a tissue survey disclosed no evidence of promoter leakage and off-target transgene expression in the GFAP.HMOX1 mice (Song et al. 2012a). Neural miRNAs, native and misfolded proteins, and lipids may be stably packaged in microvesicles and conveyed to blood and other peripheral biofluids (urine, saliva, breast milk) via exosomal delivery (Alexander et al. 2015, Cai et al. 2018, Haqqani et al. 2013, Moldovan et al. 2013, Valadi et al. 2007). In the case of PD, exosomes have been shown to participate in a- synuclein aggregation, externalization, intercellular transmission, and toxicity (Cai et al. 2018, Lee et al. 2014). On the basis of our current findings, we conjecture that exosomal transport of miRNA and protein cargo across the blood-brain barrier may be in dynamic equilibrium and that primary deficiencies in exosomal physiology within the CNS may precipitate parallel changes in peripheral tissues and biofluids (Fig. 8). In support of this model, preliminary results from our laboratory suggest exosomal shuttling of miR-153, miR-223, and relevant protein targets, between brain and periphery of GFAP.HMOX1 mice (Cressatti and Schipper, unpublished). Oxidative stress was found to mediate extracellular miRNA changes in certain conditions (Matsuzaki and Ochiya 2018) and likely plays a prominent role in our model (Lin et al. 2015, Song et al. 2017). PD-specific patterns of circulating miRNAs may provide clinically-useful chemical biomarkers for diagnosis/prognosis of the disease and the monitoring of therapeutic interventions. We recently determined that elevated salivary HO-1 concentrations may hold promise as a non-invasive and relatively inexpensive biomarker of early-stage idiopathic PD (Song et al. 2018). Further investigations are warranted to ascertain whether algorithms combining salivary HO-1 levels with biofluid miR-153 and a-synuclein measurements improve the accuracy of the test for PD.

171 14.5.3. Pathogenicity of a-synuclein in GFAP.HMOX1 mice We observed that siRNA-mediated knockdown of a-synuclein in primary GFAP.HMOX1 astrocytes profoundly impacted oxidative stress levels, dopamine metabolism, genes involved in mitophagy, and mitochondrial fission/fusion in co-cultured neurons. Pathologic a-synuclein can localize to mitochondria and cause mitochondrial dysfunction, enhancing ROS generation and oxidative stress (Dias et al. 2013). The propensity for dopamine and its metabolites to facilitate toxic protofibril formation may account for the selective vulnerability of dopaminergic neurons to a-synuclein-mediated toxicity (Rochet et al. 2004). a-Synuclein knockdown did not significantly affect p53, Bax, or Bak mRNA expression in neurons co-cultured with GFAP.HMOX1 TG astrocytes, excluding engagement of apoptotic pathways as a major contributor to a- synuclein toxicity in this system, though the anti-apoptotic Bcl2 was slightly diminished in astrocytes treated with siRNA against a-synuclein. Ferroptosis is a more likely mechanism for cellular injury in our model insofar as (i) iron is pathologically deposited in human PD basal ganglia, the GFAP.HMOX1 mouse brain, and HMOX1-transfected astroglia (Song et al. 2017, Song et al. 2012b) and (ii) iron and other transition metals promote a-synuclein upregulation, b-sheet assembly, aggregation, and fibrillogenesis, thereby enhancing the toxicity of the protein in PD- affected neural tissues (el-Agnaf and Irvine 2002, Uversky et al. 2001). Interestingly, treatment of parkinsonian GFAP.HMOX1 mice with deferiprone, an iron chelator, for 22 weeks alleviated neurological deficits in TG mice compared to controls (Song et al. 2017). Glial HO-1 hyperactivity transduces an array of noxious stimuli through neurodegenerative cascades which culminate in nigrostriatal injury (Schipper and Song 2015). The results of the current study implicate a novel HO-1-miR-153/223-a-synuclein pathway in the etiopathogenesis of parkinsonism (summarized schematically in Fig. 8). If confirmed in humans, disruption of this HO-1/a-synuclein axis may be an attractive approach towards neuroprotection in PD. Of note, Ji et al. identified a link between HO-1 and miR-153 via nuclear factor erythroid 2- related factor 2 (Nrf2), which was identified as a target gene of miR-153. Inhibition of miR-153 significantly promoted the expression of Nrf2 and HO-1, protecting neurons during cerebral ischemia (Ji et al. 2017). Constructs equivalent to miR-153 or miR-223 may prove useful in attenuating a-synuclein expression and its downstream neurodegenerative sequelae in patients

172 with idiopathic PD and related synucleinopathies. Alternatively, metalloporphyrin inhibitors of HO activity may afford neuroprotection in PD upstream of a-synuclein deposition. Novel, imidazole-based inhibitors of HO activity, such as OB-28, may be particularly interesting in this regard in light of their selectivity for HO-1 (over HO-2), blood-brain barrier permeability, and favorable toxicity profile in pre-clinical studies. In one such investigation, long-term subcutaneous administration of OB-28 countered some behavioural deficits and neuropathological changes in the APPswe/PS1DE9 mouse model of Alzheimer disease with no overt untoward effects (Gupta et al. 2014). The pre-clinical findings presented here warrant consideration of an early-phase therapeutic trial targeting the HO-1/a-synuclein axis in patients with idiopathic PD. Acknowledgements This study was supported by grants from the Canadian Institutes of Health Research and Mary Katz Claman Foundation (to HMS), and the Fonds de recherche du Québec – Santé (to MC). The authors thank Lamin Juwara for help with statistical analyses and Julia Galindez, Joshua Schwartz, Bo Yang Zhao, and Ryan Schwartz for the technical assistance. Conflicts of interest HMS has served as officer of HemOx Biotechnoliges and consultant to Osta Biotechnologies, Molecular Biometrics Inc., TEVA Neurosciences, and Caprion Pharmaceuticals. HMS is an inventor on patents related to HO-1 diagnostics and therapeutics for neurodegenerative diseases and cancer [U.S. 6,210,895B1 (2001); U.S. 60/680,006 (2005); U.S. 11/542,645 and P.C.T. 1303537 (2006); U.S. P12/139,781 and P.C.T. CA2008/001134 (2008)]. MC, WS, AZT, LRG, JAB, CG, and AL have no conflicts of interest to declare.

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181 14.7. Chapter 3 Tables and Figures Table 1. Primer sequences for microRNA and mRNA probes. F, forward; R, reverse. Primer Sequence (5’ to 3’) b-actin F: agggaaatcgtgcgtgac; R: cgctcattgccgatagtg RNU44 forward F: cctggatgatgatagcaaatgc; R: gagctaattaagaccttcatgtt SNCA F: accaaacagggtgtggcagaag; R: cttgctctttggtcttctcagcc snoRNA-202 agtacttttgaacccttttcca mmu-miR-7a tggaagactagtgattttgttgt mmu-miR-7b tggaagacttgtgattttgttgt mmu-miR-16 tagcagcacgtaaatattggcg mmu-miR-17 caaagtgcttacagtgcaggtag mmu-miR-29c tagcaccatttgaaatcggtta mmu-miR-34a-5p acaaccagctaagacactgcca mmu-miR-128-3p tcacagtgaaccggtctcttt mmu-miR-128-5p cggggccgtagcactgtctga mmu-miR-133b tttggtccccttcaaccagcta mmu-miR-137-3p ttattgcttaagaatacgcgtag mmu-miR-137-5p acgggtattcttgggtggataat mmu-miR-138 agctggtgttgtgaatcaggccg mmu-miR-140* taccacagggtagaaccacgg mmu-miR-145 gtccagttttcccaggaatccct mmu-miR-153-3p ttgcatagtcacaaaagtgatc mmu-miR181a aacattcaacgctgtcggtgagt mmu-miR-200c-3p taatactgccgggtaatgatgga mmu-miR-206 tggaatgtaaggaagtgtgtgg mmu-miR-208a-3p acaagctttttgctcgtcttat mmu-miR-208b acaaaccttttgttcgtcttat mmu-miR-223 tgtcagtttgtcaaatacccca mmu-miR-325 ttgataggaggtgctcaataaa

182 Figure 1

A WT SN TG SN B

α-Synuclein

Ser129Phospho-Syn

Figure 1. a-Synuclein expression and oxidative stress in parkinsonian GFAP.HMOX1 mice. A. Confocal imaging of intra- and extraperikaryal a-synuclein (red) and serine 129-phosphorylated (S129Phospho) a-synuclein (red) immunofluorescence in dopaminergic neurons of the substantia nigra (SN). TH (green) and DAPI (blue) in 19 month-old WT and TG SN. B. Protein carbonylation (nmol carbonyl per mg protein), an indicator of oxidative stress, in 19-month old WT vs. TG striatum (STM), n = 3, *** p < 0.001.

183 Figure 2

STM 4

2 SN

0 Astrocytes

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miR-7amiR-7b miR-16miR-17 miR-153miR-223miR-145miR-325 miR-138miR-29cmiR-206 miR-140 miR-133b miR-208b miR-181a miR-34a-5p miR-137-5pmiR-137-3pmiR-128-5pmiR-128-3p miR-208a-3p miR-200c-3p

B1.5 C 1.5 WT WT * * * * TG *** *** * *** TG 1.0 1.0

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mmu-miR-145 mmu-miR-145 mmu-miR-145 mmu-miR-145 mmu-miR-133b mmu-miR-133b mmu-miR-133b mmu-miR-133b

SN STM Astrocytes Neurons

Figure 2. MiRNA profiles in 19-month old GFAP.HMOX1 mice. A. Data from striatum (STM) and substantia nigra (SN) in vivo and from primary astrocyte-neuron co-cultures are depicted by

184 heatmap. Downregulation of miR-153 and miR-223 in TG SN and STM in vivo (B) and TG primary astrocyte-neuronal co-cultures (C). Upregulation of miR-133b and miR-145 in TG STM in vivo (D) and TG primary astrocyte and neuronal co-cultures (E). All data were obtained via RT-qPCR and analyzed using the DDCt method relative to internal and endogenous controls. Heatmap generated by GraphPad Prism 8. n = 5, *, p < 0.05; **, p < 0.01; ***, p < 0.001.

185 Figure 3 A B C D 40 1.5 1.5 Neg Ctl Neg Ctl Neg Ctl Treated 30 *** *** ** ** Treated *** *** * Treated 1.0 1.0 20

0.5 0.5

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miR-153 mimic miR-223 mimic miR-153 mimic miR-223 mimic miR-153 mimicmiR-223 mimic miR-153 mimicmiR-223 mimic

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E F G H 1.5 2.5 2.0 Neg Ctl * * Neg Ctl * Neg Ctl Treated Treated *** *** 2.0 Treated 1.5 1.0 1.5 1.0

0.5 1.0 Fold Change 0.5 0.5 miRNA Fold Change SNCA Fold Change

0.0 0.0 0.0

miR-153 siRNA miR-223 siRNA miR-153 siRNA miR-223 siRNA miR-153 inhibitormiR-223 inhibitor miR-153 inhibitormiR-223 inhibitor Monomers Oligomers Figure 3. a-Synuclein regulation by miR-153 and miR-223. Transfection (12 h) of BE(2)-M17 human neuroblastoma cells with miR-153 and miR-223 mimics increases miRNA expression levels (A) and results in decreased a-synuclein mRNA (B) and protein (C) compared to negative control values. Densitometric analysis of Western blot bands depicted in (C) was performed using ImageStudio software (D). Contrariwise, transfection (12 h) of cells with miR-153 and miR-223 siRNA decreases miRNA expression levels (E) and results in increased a-synuclein mRNA (F) and protein (G) compared to negative controls. Densitometric analysis of Western blot bands depicted in (G) was performed using ImageStudio software (H). RT-qPCR was used to measure miRNA and mRNA expression levels and Western blot was used to measure a-synuclein protein, in negative control (Neg Ctl) and treated samples. RT-qPCR was analyzed using the DDCt method relative to internal and endogenous controls. n = 3-5; *, p < 0.05; **, p < 0.01; ***, p < 0.001.

186 Figure 4

A B

1.5 1.5 WT WT TG TG 1.0 p < 0.001 1.0 p = 0.1937

0.5 0.5

0.0 0.0 Relative Expression (snoRNA202 ctl) Relative Expression (snoRNA202 ctl)

11 months 14 months 17 months 19 months 11 months 14 months 17 months 19 months

C D 2.5 ** WT 2.0 TG * 1.5

1.0 Fold Change 0.5

0.0

Monomers Oligomers Figure 4. Expression patterns of miR-153 (A), miR-223 (B) and a-synuclein (C, D) in WT and GFAP.HMOX1 mouse blood. Blood serum was procured from WT and TG mice at 11, 14, 17 and 19 months of age, while RBCs were isolated from WT and TG mice at 19 months of age only. MiRNA expression levels were determined by RT-qPCR and analyzed using the DDCt method relative to internal and endogenous controls. Western blot was used to measure a-synuclein protein. For A and B, n = 7-13; for C and D, n = 7-8; ***, p < 0.001.

187 Figure 5

A B

C **

Figure 5. Effects of a-synuclein inhibition on oxidative stress in primary GFAP.HMOX1 cultures. A. Western blot was used to measure a-synuclein protein expression levels in TG and WT primary astrocyte cultures after transfection (24 h) with SNCA siRNA or negative control (Neg Ctl) siRNA. B. The protein carbonyl assay was used to measure nmol carbonyl per mg protein in WT vs. TG samples. C. MnSOD mRNA expression levels in neurons co-cultured with WT or TG astrocytes transfected (24 h) with negative control (Neg) siRNA (white and grey bars) and a-synuclein siRNA (checkered and black bars). RT-qPCR was used to measure mRNA levels and analyzed using the DDCt method relative to internal and endogenous controls. Comparisons between groups was analyzed by 2-way ANOVA. n = 3-4; *, p < 0.05; ***, p < 0.001.

188 Figure 6

Figure 6. Effects of a-synuclein inhibition on dopaminergic gene expression profiles in primary GFAP.HMOX1 co-cultures. TH, DAT, Nurr1, and Pitx3 mRNA expression levels in neurons co- cultured with WT or TG astrocytes transfected (24 h) with negative control (Neg) siRNA (white and grey bars) and a-synuclein siRNA (checkered and black bars). mRNA levels were measured by RT-qPCR and analyzed using the DDCt method relative to internal and endogenous controls. Comparisons between groups was analyzed by 2-way MANOVA. n = 3-4; *, p < 0.05; **, p < 0.01.

189 Figure 7

A B C

Figure 7. Effects of a-synuclein inhibition on mitophagy, mitochondrial fission/fusion, and apoptosis genes in primary GFAP.HMOX1 co-cultures. A. Parkin, PINK1, and DJ-1 mRNA expression levels in neurons co-cultured with WT or TG astrocytes transfected (24 h) with negative control (Neg) siRNA (white and grey bars) or a-synuclein siRNA (checkered and black bars). B. Mfn1, Mfn2, and DRP1 mRNA expression levels in neurons co-cultured with WT or TG astrocytes transfected (24 h) with negative control (Neg) siRNA (white and grey bars) or a- synuclein siRNA (checkered and black bars). C. p53, Bcl2, Bax, and Bak mRNA expression levels in neurons co-cultured with WT or TG astrocytes transfected (24 h) with negative control (Neg) siRNA (white and grey bars) or a-synuclein siRNA (checkered and black bars). RT-qPCR was used to measure mRNA levels and analyzed using the DDCt method relative to internal and endogenous controls. Comparisons between groups was analyzed by 2-way MANOVA. n = 3-4; **, p < 0.05; **, p < 0.01; ***, p < 0.001.

190 Figure 8 DA Neurons Astrocytes ↓miR-153 Aging Oxidative ↑CO Stress ↓miR-223 Genetic ↑HO-1 ↑Fe2+ Propagation Environmental (↑Biliverdin/Bilirubin) ↑⍺-Synuclein

↓miR-153 ↓miR-223 Aggregation - ↑ Oxidative stress - ↓ Nurr1, Pitx3, TH, DAT - ↓ DJ-1 ↓miR-153 ↓miR-223 - ↓ Mfn2, ↑ DRP1 ↑⍺-Syn Neurodegeneration CNS ↓miR-153 ↓miR-223 Equilibrium Periphery ↓miR-153 ↓miR-223 Serum Erythrocytes ↑⍺-Syn

↓miR-153 ↑⍺-Synuclein ↓miR-223 Bone = exosome marrow Fig. 8. A working model for a-synuclein dysregulation and pathogenicity in parkinsonian GFAP.HMOX1 mice. See text for details. CNS, central nervous system; CO, carbon monoxide; DA, dopaminergic; DAT, dopamine transporter; DJ-1, protein deglycase DJ-1; DRP1, dynamin-related protein 1; Fe2+, ferrous iron; HO-1, heme oxygenase-1; Mfn2, mitofusin-2; Nurr1, nuclear receptor related-1 protein; Pitx3, pituitary homeobox 3; a-Syn, a-synuclein; TH, tyrosine hydroxylase.

191 15. Transition 3: Peripheral MicroRNA Changes from Mice to Humans The finding of decreased microRNA (miRNA)-153 and miR-223 expression levels in GFAP.HMOX18.5-19m mouse serum (see Chapter 3), complementing changes observed in brain, is what led to this next study. Chapter 4 sought to explore whether miR-153 and miR-223 changes could similarly be observed in the periphery of humans with PD. We selected saliva as our biofluid of choice due to its ease of accessibility, acquisition and standardized processing. This was a project conducted in collaboration with Dr. Mervyn Gornitsky, Chief Emeritus and Director of Research (Department of Dentistry, Jewish General Hospital), and Dr. Ana Velly, epidemiologist and Associate Professor (Faculty of Dentistry, McGill University). We previously reported significantly increased concentrations of heme oxygenase-1 (HO-1) protein in the saliva of PD patients relative to non-neurological (healthy) controls (Song et al. 2018). The study described in Chapter 4 builds upon this previous work, looking downstream of HO-1 at salivary miR-153 and miR-223 levels. Soon after our online publication of this work in Movement Disorders (2019), our findings were prominently featured in Research Highlights of Nature Reviews Neurology (2019).

192 16. Chapter 4: Salivary MicroRNA-153 and MicroRNA-223 Levels as Potential Diagnostic Biomarkers of Idiopathic Parkinson’s Disease

Published in Movement Disorders (2019).

Author List: Marisa Cressatti1,2, MSc, Lamin Juwara1,3, MSc, Julia M. Galindez1,2, BSc, Ana M. Velly1,4,5, DDS, MSc, PhD, Eva S. Nkurunziza1, BSc, Sara Marier1,2, BSc, Olivia Canie1, BSc, Mervyn Gornistky1,4,5, DDS, FRCDC, and Hyman M. Schipper1,2¶, MD, PhD, FRCPC

1Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada 2Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada 3Department of Quantitative Life Sciences, McGill University, Montreal, QC, Canada 4Department of Dentistry, Jewish General Hospital, Montreal, QC, Canada 5Faculty of Dentistry, McGill University, Montreal, QC, Canada

Correspondence¶: Hyman M. Schipper, Lady Davis Institute for Medical Research, Jewish General Hospital, 3999 Cote Sainte-Catherine Road, Montreal, Quebec H3T 1E2, Canada. E-mail: [email protected]. Phone: 514-340-8222 ext. 25588.

193 16.1. Chapter 4 Abstract Background: Parkinson’s disease (PD) is the most common movement disorder among adults, affecting 2% of the world population above 65 years of age. No diagnostic biomarker for routine use in clinical settings currently exists. Dysregulation of microRNAs (miR-) has been implicated in various neurodegenerative conditions, including PD. Distinct miRNAs have been demonstrated to be involved in the regulation of a-synuclein, a key player in PD pathogenesis. MiR-153 and miR-223 are downregulated in brain and serum of parkinsonian GFAP.HMOX1 transgenic mice where they directly regulate a-synuclein. Objective: To ascertain whether salivary miR-153 and miR-223 are similarly down-modulated in, and may serve as diagnostic biomarkers of, idiopathic PD. Methods: Using RT-qPCR, miR-153 and miR-223 levels were evaluated in the saliva of 77 non- neurological controls and 83 PD subjects. Levels of heme oxygenase-1 and a-synuclein were measured using ELISA. Analyses were adjusted by age, sex, medication exposure, disease duration and relevant comorbidities. Results: Log-transformed expression levels of miR-153 and miR-223 were significantly decreased in the saliva of human PD subjects in comparison to non- neurological controls. MiRNA expression levels did not change as a function of disease progression (Hoehn and Yahr staging). The area under the receiver operating characteristic curve separating controls from PD subjects was 79% (confidence interval: 64-99%) for miR-153 and 74% (confidence interval: 60-93%) for miR-223. Ratios of miRNAs to oligomeric a-synuclein, total a- synuclein or heme oxygenase-1 protein did not improve accuracy of the test. Conclusion: Salivary miR-153 and miR-223 levels may serve as useful, non-invasive and relatively inexpensive diagnostic biomarkers of idiopathic PD.

Keywords: Heme oxygenase-1, microRNA, Parkinson disease, saliva, a-synuclein.

194 16.2. Chapter 4 Introduction Parkinson’s disease (PD) is the most common movement disorder and second most common neurodegenerative condition, affecting 2% of the global population over 65 years of age (Dexter and Jenner 2013). Resting tremor, rigidity and hypokinesia are the cardinal symptoms of this disorder. Autonomic dysfunction, dementia and pre-motor manifestations (olfactory deficits, constipation, rapid eye movement [REM] sleep behaviour disorder and depression) may complete the clinical picture (Fahn 2003, Lang 2011). For the past 25 years, accuracy of PD diagnosis has been estimated at 80% (Rizzo et al. 2016). Early stage PD (Hoehn and Yahr [H&Y] stage 1) is particularly prone to misdiagnosis, with studies reporting 26% and 53% accuracy in patients with less than 3 and 5 years disease duration, respectively (Adler et al. 2014). Despite advances in neuroimaging and genetics, the diagnosis of PD remains primarily clinical, only confirmed upon autopsy. Neuroimaging modalities, such as MRI, [18F]fluorodopa PET, single-photon emission computed tomography and transcranial ultrasound, have provided some utility in the diagnosis and staging of idiopathic PD (Emamzadeh and Surguchov 2018, Miller and O'Callaghan 2015), but remain expensive and labor-intensive. Blood and cerebrospinal fluid (CSF) have been extensively analyzed for protein biomarkers, dopamine metabolites and amino acids. Among the most promising: soluble, aggregated and post-translationally modified forms of a-synuclein have been tested (Emamzadeh and Surguchov 2018). a-Synuclein comprises the main protein component of hallmark Lewy bodies and is measurable in blood, CSF and saliva (Baba et al. 1998, Emamzadeh and Surguchov 2018, Marques and Outeiro 2012). Saliva has advantages over other biofluids and imaging techniques because its acquisition is non-invasive, inexpensive and requires minimal training of personnel (Roi et al. 2019, Wang et al. 2015). Most groups report reduced salivary total a-synuclein levels and higher oligomeric a-synuclein levels in PD patients compared to controls, in addition to higher oligomeric to total a-synuclein ratios (Al-Nimer et al. 2014, Devic et al. 2011, Kang et al. 2016, Vivacqua et al. 2016, Vivacqua et al. 2019). In 2018, we reported increased concentrations of salivary heme oxygenase-1 (HO-1) in early stage PD patients compared to non-neurological controls (Song et al. 2018). HO-1 catalyses the degradation of heme to biliverdin (further catabolized to bilirubin), free ferrous iron and

195 carbon monoxide. Numerous response elements in the HMOX1 promoter render it remarkably sensitive to induction by dopamine and various stressors implicated in PD etiopathogenesis (Schipper et al. 2019). HO-1 is upregulated in astrocytes of the substantia nigra and decorates peripheries of neuronal Lewy bodies in idiopathic PD (Schipper et al. 1998). Moreover, glial HO- 1 induction in primary astrocyte cultures and GFAP.HMOX1 transgenic mice promotes oxidative stress, mitochondrial injury, pathological iron deposition and mitophagy reminiscent of PD- affected human tissues (Song et al. 2017, Zukor et al. 2009). Novel GFAP.HMOX1 mice engineered by our laboratory to conditionally overexpress human HO-1 in astrocytes between 8.5 and 19 months of age and provide a direct link between HO-1 and behavioural abnormalities, neuropathology as well as biochemistry reminiscent of human PD (Song et al. 2017). At 19 months, GFAP.HMOX1 mice exhibit locomotor incoordination, hypo-dopaminergia, increased α- synuclein production in addition to the core neurodegenerative features listed above (Song et al. 2017). Serum HO-1 levels in PD patients are also elevated compared to non-PD controls (Mateo et al. 2010). While acute upregulation of HO-1 confers neuroprotection by accelerating degradation of pro-oxidant heme to radical-scavenging bile pigments, biliverdin and bilirubin (Chen-Roetling et al. 2017, Chen-Roetling et al. 2015, Dore et al. 1999), excessive heme-derived iron and carbon monoxide accruing from prolonged HO-1 overexpression in chronic conditions may exacerbate intracellular oxidative stress and substrate damage by promoting the generation of reactive oxygen species within mitochondria (Schipper et al. 2019). MicroRNAs (miR-) have emerged as key players in development, normal aging and disease, including PD (Basak et al. 2016, Lukiw 2007, Martinez 2017). MiRNAs are short, non- coding RNA species that act in post-transcriptional regulation of messenger RNA (mRNA) by binding the 3’ untranslated region (3’UTR) and blocking translation. Overexpression of human HO-1 in primary astrocytes and parkinsonian GFAP.HMOX1 mice results in altered miRNA profiles compared to controls (Cressatti et al. 2019, Lin et al. 2015). MiR-153 and miR-223 were found to regulate a-synuclein expression in brain downstream of HMOX1 induction (Cressatti et al. 2019). Other groups have similarly reported a-synuclein regulation by miR-153 (Doxakis 2010, Fragkouli and Doxakis 2014, Je and Kim 2017), although regulation of a-synuclein by miR-223 is unprecedented. Circulating levels of miR-153 and miR-223 were lower in the GFAP.HMOX1 mice

196 compared to age-matched, wild-type controls (Cressatti et al. 2019), commensurate with systemic alterations in a-synuclein gene and protein expression profiles in idiopathic PD (Gao et al. 2015, Matsumoto et al. 2017, Vivacqua et al. 2019). In the current study, we assessed salivary miR-153 and miR-223 levels as potential diagnostic biomarkers of PD relative to non-neurological controls. 16.3. Chapter 4 Materials and Methods 16.3.1. Study design and population This study was approved by the Research Ethics Committee of the Jewish General Hospital (JGH; Montreal, Canada). A total of 167 potential subjects (84 PD subjects and 83 control subjects) were enrolled between July 2014 and June 2018. Seven subjects were subsequently removed as outliers, leaving 83 subjects diagnosed with idiopathic PD (51.9%) and 77 controls (48.1%). One control subject was removed by Cook’s distance (see Section 16.3.6), and five additional controls and one PD subject were removed based on miRNA expression levels greater than two standard deviations from the means. The omitted outliers reported high blood pressure (3/7), appendectomy (1/7), major operation (1/7), diabetes (1/7) and heart disease (1/7), factors which may have impacted miRNA expression levels. All participants provided written informed consent. Subjects eligible for inclusion in the PD group were diagnosed with idiopathic PD by members of the Department of Neurology at the JGH and fulfilled UK Parkinson’s Disease Society Brain Bank diagnostic criteria. Medical charts of 74 out of 84 PD subjects (88%) were available for determination of disease duration and medication use at the time of sample procurement (see Section 16.3.2). Non-neurological controls were recruited from the Departments of Medicine, Dentistry and Ophthalmology at the JGH. Exclusion criteria for both PD and control groups included cigarette smoking within the past year, severe periodontal disease, history of oral cancer, active systemic inflammatory disease (e.g. tuberculosis, HIV, rheumatoid arthritis, etc.), current alcoholism or illicit drug abuse, recent exposure to neuroleptic medications and evidence suggesting atypical, secondary or familial parkinsonism.

197 16.3.2. Clinical and demographic data Demographics and questionnaires (designed by our research team and approved by the JGH Research Ethics Committee) were available on all subjects. The H&Y scale was used for staging of all PD subjects in this study. Patients with PD are typically treated with pro-dopaminergic and, to a lesser extent, anticholinergic medications aimed at alleviating motor symptoms of the disease. We assessed whether dopamine exposure impacted salivary miRNA concentrations by converting all pro- dopaminergic medication dosages to levodopa (L-dopa) equivalent daily dose (LEDD) using an established formula (https://www.parkinsonmeasurement.org) (Song et al. 2018). We also ascertained whether (i) L-dopa exposure alone or (ii) non-L-dopa anti-parkinsonian medications correlate with salivary miRNA levels. 16.3.3. Saliva collection and processing Whole, unstimulated saliva samples were collected at least 30 min after food or liquid ingestion, and saliva was collected by passive drooling and kept at 4°C for a maximum of 3 h until further processing. Samples with traces of blood were discarded. Before analysis, saliva was centrifuged at 7,862 x g (10,000 rpm) for 20 min at 4°C to remove food particles and reduce sample viscosity. Supernatants were stored at -80°C. Protease inhibitors were added upon first thaw. We determined that long-term storage (up to 4 years) does not significantly affect saliva composition (P=0.3; data not shown). 16.3.4. Quantification of miRNA expression levels MiR-153 and miR-223 were selected for further study based on their mRNA target, a-synuclein predicted by the TargetScan algorithm and confirmed previously (Cressatti et al. 2019). MiR-7 was also selected given its purported role in a-synuclein regulation (Doxakis 2010, Fragkouli and Doxakis 2014). Total RNA from subject saliva was extracted in Trizol reagent according to manufacturer instructions (Invitrogen). Prior to cDNA synthesis, RNA extract was subjected to spectrophotometric analysis to determine concentration and purity. MiRNA polyadenylation was performed followed by cDNA synthesis with miScript II RT kit (Qiagen). The Applied Biosystems 7500 Fast Real-Time PCR System (Life Technologies) was used to quantify miRNA with SensiFast SYBR Lo-ROX kit (FroggaBio) via reverse transcriptase quantitative real-time PCR (RT-qPCR).

198 Primer sequences used to detect miRNA levels were either designed with Primer Express Software, version 3.0 (Applied Biosystems by Life Technologies), or obtained from AlphaDNA (Supplementary Table 1). As an internal reference for normalization of all miRNA data, endogenous levels of RNU44 (small nucleolar RNA, C/D box 44; abundantly expressed in human biofluids with low variability) were probed. Expression fold changes between groups were calculated using the delta-delta cycle threshold value (2-∆∆Ct) method relative to controls, following additional normalization with RNU44 levels. 16.3.5. Enzyme-linked immunosorbent assay (ELISA) Levels of protein were assayed in whole saliva of subjects by sandwich ELISA using kits specific for oligomeric α-synuclein (MyBioSource), total α-synuclein (SensoLyte) and HO-1 (Abbexa), according to the manufacturer instructions. For oligomeric α-synuclein ELISA, intra-assay variability was ≤5.6%, inter-assay variability was ≤8.1% and sensitivity was <0.1 ng/ml. The detection range for oligomeric α-synuclein protein was 0-50 ng/ml, and original samples were diluted 1:4 with PBS and plated in duplicate. For total α-synuclein ELISA, intra-assay variability was ≤5.03% with a sensitivity of 5 pg/ml. The detection range for total α-synuclein protein was 8-500 pg/ml, and original samples were diluted 1:2.5 with standard dilution buffer and plated in duplicate. The detection range for HO-1 ELISA was 0.16-10 ng/ml with a sensitivity of 0.1 ng/ml and intra-assay and inter-assay variability of <10%. For HO-1 measurements, original samples were diluted 1:10 with standard dilution buffer prior to plating in duplicate. Regression for all respective standard curves were highly linear with an average of r2>0.92. Concentrations of oligomeric α-synuclein, total α-synuclein and HO-1 were normalized to total protein concentration, determined using BCA assay (Bio-Rad). The detection range was 0.31-20 mg/ml, with an average regression of r2=0.96. 16.3.6. Statistical analysis Student’s t-test and analysis of covariance (ANCOVA), and Pearson chi-square tests were used to compare the means of the continuous variables and distribution of the categorical variables between study groups, respectively. The distribution of miRNA expression levels in each group was highly skewed to the left, therefore expression levels were log-transformed for normal distribution. ANCOVA was used to assess the difference in mean values of salivary miRNA levels.

199 ANCOVA analysis included age, sex and relevant comorbidities. The Pearson correlation was used to assess whether covariates were associated with salivary miRNA levels. Cook’s distance was used to identify potential outliers (Cook’s distance Di>2). We utilized an unconditional Multivariable Logistic Regression (MLR) model to estimate the odds of PD (H&Y stage ≥ 1) versus controls for a unit change in relative expression level while accounting for all pertinent comorbidities. Two MLR models were independently constructed for miR-153 and miR-223, and receiver operating characteristic (ROC) curves were estimated for each model. ANCOVA was used to assess the difference in mean values of salivary miRNA levels between H&Y stages (H&Y scores: 1-3+) compared to the control group. Additionally, dose and duration of exposure to pro-dopaminergic drugs (independent variable) were evaluated to determine whether the primary analysis may have been modified by PD-specific medication use. For all analyses, the two-tailed a significance level was 5% and were performed with R statistical software (version 3.4.4). 16.4. Chapter 4 Results 16.4.1. Demographic and comorbidity distributions Table 1 shows the demographic and comorbidity distributions between study groups. Significant differences were observed between the groups for heart disease (P=0.02) and age (P=0.02). The mean age of the PD group (71.4 years old, standard error of the mean [SEM]=1.04) was significantly greater than the control group (67.3 years old, SEM=1.38). Heart disease was also more prevalent in the PD group (18.10%) compared to the control group (4.80%). All confounding variables were accounted for in the multivariable models presented herein. 16.4.2. Salivary miRNA expression RT-qPCR and analysis via the 2-∆∆Ct method revealed decreased expression levels of miR-153 and miR-223 in PD subjects compared to controls. Mean miR-153 concentrations for PD subjects was 0.55 (SEM=0.046) relative to controls (Fig. 1A), while mean miR-223 levels for PD subjects was 0.52 (SEM=0.17) relative to controls (Fig. 1B). After log-transformation of the data for normal distribution, both miR-153 and miR-223 were significantly diminished relative to control values (P=0.01 and P=0.02, respectively) (Fig. 1 C, D). Salivary log-transformed miR-153 and miR-223

200 levels remained significantly lower in PD subjects relative to controls after controlling for age, sex and comorbidities (Supplementary Table 2). Log-transformed expression levels of miR-7a and miR-7b were not significantly different in PD saliva compared to controls (P=0.1 and P=0.2, respectively) (Fig. 2A-D). 16.4.3. ROC analyses The data suggest that salivary miR-153, and to a lesser extent, miR-223 expression levels distinguish PD subjects from controls with an area under the curve (AUC) of 79% (95% confidence interval [CI]: 64.5-99.2) and 74% (95% CI: 59.6-93.0), respectively (Fig. 1E, F). At the arbitrary threshold of 0.34, miR-153 sensitivity was 81.8% and miR-153 specificity was 71.4%, while miR- 223 sensitivity was 72.7% and miR-223 specificity was 71.4% at the arbitrary threshold of 0.47, relative to controls. Combining the MLR models for miR-153 and miR-223 did not improve the goodness-of-fit assessment of the test (data not shown). As for miR-7a and miR-7b, expression levels in saliva do not distinguish PD subjects from controls, with an AUC of 59% (95% CI: 39.8-78.1) and 53% (95% CI: 33.1-72.2), respectively (Fig. 2E, F). 16.4.4. Effects of medications Among PD subjects, mean LEDD was 658.33 (SEM=34.11) mg, and as expected, LEDD increased as a function of H&Y stage (Fig. 3A). Similarly, mean L-dopa exposure was 337.9 (SEM=25.72) mg, and increased as a function of H&Y stage (Fig. 3B). Log-transformed miR-153 and miR-223 expression levels were not correlated to LEDD (P=0.78 and P=0.37, respectively) (Fig. 3C, D) or L- dopa exposure (P=0.99 and P=0.38, respectively) (Fig. 3E, F). Expression levels also did not correlate to non-L-dopa anti-parkinsonian medications (P=0.85 and P=0.88, respectively) (data not shown). 16.4.5. Progression of PD Analyses demonstrated that PD patients in H&Y stage 1 (early PD) had significantly lower log- transformed salivary miR-153 concentrations relative to controls (P<0.05) (Fig. 4A). Log- transformed salivary miR-153 levels relative to controls also displayed significant differences in disease progression with PD patients in H&Y stage 2 (P=0.006), though differences from PD patients in H&Y stage ≥3 were not significant (P=0.08) (Fig. 4A). No other significant differences

201 in log-transformed miR-153 levels were noted between groups. For log-transformed miR-223 levels, on the other hand, a significant difference was only noted between H&Y stage 2 and non- PD controls (P=0.03) (Fig. 4B). The estimated disease duration among the PD population was 2.78 years (SD=3.45), which was not significantly correlated with expression levels of miR-153 (P=0.81) or miR-223 (P=0.24) (Fig. 4C-E). 16.4.6. Ratios MiR-153 and miR-223 regulate a-synuclein, and several groups have shown increased levels of oligomeric a-synuclein and decreased levels of total a-synuclein in PD saliva (Song et al. 2018). In a randomly selected subset of the study population (22 PD subjects and 30 controls), salivary oligomeric a-synuclein was increased, though not significantly, in PD saliva compared to control preparations (P=0.41). Although the ratio of oligomeric a-synuclein/miR-153 was significantly increased among PD subjects (P<0.05), this did not improve accuracy of the test (Supplementary Fig. 1A). The ratio of oligomeric a-synuclein/miR-223 was not significantly different in the PD subjects compared to controls (P=0.28) (Supplementary Fig. 1C). On the other hand, salivary total a-synuclein was decreased, though not significantly, in a randomly-selected subset of PD saliva (16 subjects) compared to control preparations (18 subjects). Both the ratio of total a- synuclein/miR-153 and total a-synuclein/miR-223 were not significantly different between PD and control groups (P=0.23 and P=0.47, respectively) (Supplementary Fig. 1E, G), and did not improve accuracy of the test. Neither miR-153 or miR-223 was significantly correlated with oligomeric a-synuclein (P=0.35 and P=0.64, respectively) or total a-synuclein (P=0.93 and P=0.80, respectively) levels (Supplementary Fig. 1). Similarly, the ratio of oligomeric a-synuclein to total a-synuclein was not significantly correlated to either miR-153 (P=0.51) or miR-223 (P=0.74) (data not shown). HO-1 acts upstream of miR-153 and miR-223 and we have previously shown that salivary HO-1 is increased in PD subjects compared to controls (Song et al. 2018). In a randomly selected subset of the study population (32 PD subjects and 27 controls), the ratios of HO-1/miR-153 and HO-1/miR-223 were not significantly increased in PD saliva compared to healthy controls (P=0.074 and P=0.26, respectively), and did not improve accuracy of the test (Supplementary Fig. 1I, J).

202 The samples used in the randomly selected subsets were representative of the overall population in terms of distribution and all comorbidities, with the exception of sex (P=0.004) for the population subset used for total a-synuclein analysis (data not shown). 16.5. Chapter 4 Discussion Using quantitative RT-qPCR, we observed (i) the presence of miR-153, miR-223 and miR-7 family in human saliva and (ii) significantly reduced expression levels of miR-153 and miR-223 in PD saliva compared to non-neurological controls. The miRNA expression patterns observed in PD saliva were unaffected by age, sex, various comorbidities or medication exposure. While miR-7 has been linked to a-synuclein regulation (Doxakis 2010, Junn et al. 2009), we did not observe significant alterations in miR-7a or miR-7b in PD saliva relative to controls. The changes in salivary miRNAs described herein are consistent with our previous findings in brain and serum of parkinsonian GFAP.HMOX1 mice (Cressatti et al. 2019). Changes in miR-153 or miR-223 expression levels did not become more pronounced with disease progression or duration. Additionally, measurement of the ratios of key proteins acting upstream (HO-1) or downstream (oligomeric or total a-synuclein) of miR-153 or miR-223 to these miRNAs did not improve the accuracy of the test as a PD neurodiagnostic relative to ascertainment of miR-153 or miR-223 alone. Expression levels of miR-153, miR-223 and SNCA are highest in midbrain (Doxakis 2010, Farh et al. 2005, Tagliafierro et al. 2017), though they have also been detected in extracellular compartments, including blood (Matsumoto et al. 2017, Vallelunga et al. 2014, Vicente Miranda et al. 2017), CSF (Gao et al. 2015, Gui et al. 2015) and saliva (Patel et al. 2011, Vivacqua et al. 2016, Vivacqua et al. 2019), where their levels appear to fluctuate in response to disease state. Several groups, including our own, have linked miR-153 and, to a lesser extent, miR-223 to PD pathology (Cressatti et al. 2019, Doxakis 2010, Je and Kim 2017, Vallelunga et al. 2014). Alterations in miR-153 levels have been documented in PD CSF (Gui et al. 2015) and plasma (Zhang et al. 2017), while changes in miR-223 have been reported in PD serum (Vallelunga et al. 2014). Differential expression of miR-153 and miR-223 has been reported in other CNS conditions. In Alzheimer-diseased brain, suppression of miR-153 has been implicated in the dysregulation of amyloid precursor protein (Liang et al. 2007, Long et al. 2012). In multiple

203 sclerosis, miR-223 levels were noted to be increased in whole blood (Keller et al. 2009), CD4+ T cells (Hosseini et al. 2016) and brain (Guerau-de-Arellano et al. 2015) and diminished in serum (Fenoglio et al. 2013, Ridolfi et al. 2013) compared to healthy controls. To our knowledge, the current study is the first to document aberrant expression levels of miR-153 and miR-223 in the saliva of PD subjects. Conserved binding sites for miR-153 and miR-223 were predicted to lie within the 3’UTR of SNCA with partial complementarity (TargetScan software), and miR-153 was confirmed to bind the 3’UTR of SNCA and suppress a-synuclein mRNA and protein (Doxakis 2010). A rare mutation within the miR-153 binding site was also reported in a patient with idiopathic PD (Kim et al. 2013). GFAP.HMOX1 transgenic mice were engineered to overexpress the human HO-1 gene (HMOX1) in astrocytes between 8.5 and 19 months of age, recapitulating HO-1 levels observed in substantia nigra astrocytes of PD subjects (Schipper et al. 1998). Akin to changes observed in human PD saliva, miR-153 and miR-223 were decreased in the serum of GFAP.HMOX1 transgenic mice at multiple time points surveyed relative to age-matched, wild-type controls (Cressatti et al. 2019). Whether salivary miR-153 and miR-223 down-modulation in PD reflects primary changes in the CNS downstream of glial HMOX1 induction remains to be determined. Circumstantial evidence in support of the latter includes the following: (i) Circulating miR-153 and miR-223 levels are suppressed in parkinsonian GFAP.HMOX1 mice which selectively overexpress HO-1 in the astrocytes (Cressatti et al. 2019); (ii) miR-153 has been linked to HO-1 via nuclear factor erythroid 2-related factor 2 (Nrf2), which was recognized as a target gene of miR-153 (Ji et al. 2017, Zhu et al. 2019). Inhibition of miR-153 promotes the expression of Nrf2 and HO-1, protecting neurons from cerebral ischemia (Ji et al. 2017). Chronically overexpressed HO-1 may be participating in a feed-forward loop, contributing to the downregulation of miR-153 and, ultimately, a-synuclein overproduction and PD pathogenesis; (iii) Phosphorylated a-synuclein aggregates were detected in labial salivary gland biopsies of persons with idiopathic REM sleep behaviour disorder and PD patients (Iranzo et al. 2018). a-Synuclein may be delivered to the salivary gland via autonomic innervation (Bosch 2014) where it may be susceptible to dysregulation by altered miR-153 and miR-223 activity; (iv) We previously observed increased salivary HO-1 concentrations in PD

204 patients compared to healthy controls (Song et al. 2018). Native and misfolded proteins as well as miRNAs can be stably packaged in neural microvesicles and transported to peripheral biofluids (blood, urine, saliva, breast milk) via exosomal delivery (Alexander et al. 2015, Cai et al. 2018, Haqqani et al. 2013, Moldovan et al. 2013, Valadi et al. 2007). With regard to PD, exosomes have been shown to participate in a-synuclein aggregation, externalization, intercellular transmission and toxicity (Cai et al. 2018, Lee et al. 2014). Preliminary results from our laboratory suggest that in parkinsonian GFAP.HMOX1 mice, exosomal transport of miRNA and proteins across the blood- brain barrier may be in dynamic equilibrium (Cressatti and Schipper, unpublished). We conjecture that altered exosomal physiology within the CNS may be reflected by parallel changes in peripheral tissues and biofluids, though further work is required to confirm this hypothesis. Our results indicate that salivary levels of miR-153 and miR-223 distinguish PD with 79% and 74% accuracy, respectively, identifying these nucleic acids as moderately good diagnostic biomarkers of idiopathic PD. In accordance with the landmark consensus report on Alzheimer’s disease biomarkers sponsored by the Ronald and Nancy Reagan Research Institute (Alzheimer’s Association) and National Institute on Aging (1998), measurement of miR-153 and miR-223 expression levels in saliva may satisfy certain criteria for a useful biological marker. Oligomeric and total a-synuclein concentrations were not correlated to either miRNA expression levels. This discrepancy may be explained by the fact that: (i) small sample sizes of groups analyzed for of oligomeric a-synuclein and total a-synuclein may not accurately reflect the populations; (ii) regulation of a-synuclein by miR-153 and miR-223 has been confirmed in brain, but not yet in the systemic circulation. Similarly, miR-7 has been identified as a negative regulator of a- synuclein in brain, however we did not observe significant differences in either miR-7a or miR-7b in PD saliva relative to controls. Other miRNAs, potentially in concert with miR-153 and/or miR- 223, may be responsible for the regulation of a-synuclein in systemic circulation; and (iii) in contrast to proteins, the majority of miRNAs present in saliva are concentrated in exosomes, protecting them from degrading RNases (Gallo et al. 2012). There were several limitations to the current study: (i) The current sample population represented a single site and a replication cohort is lacking; (ii) In contrast to the miRNA analyses, the sample sizes for measurement of oligomeric a-synuclein, total a-synuclein and HO-1 protein

205 levels were relatively small (due to sample availability); (iii) In addition to controls, neurological controls (non-PD movement and degenerative conditions) should be analyzed to determine specificity of the test; (iv) MDS-UPDRS scores were not available to corroborate H&Y staging in the ascertainment of disease severity, but should be utilized as a more robust measure of PD staging in future studies. Validation of an easily quantifiable salivary biomarker of idiopathic PD in large-scale trials would address a major unmet clinical imperative by facilitating rapid and accurate diagnosis of this condition, assisting in patient and family counselling and possibly accelerating early implementation and surrogate monitoring of effective neuroprotective therapies as they become available. Acknowledgements We thank Drs. R. Altman, J. A. Carlton, C. A. Melmed, D. Rabinovitch and M. Sidel from the Department of Neurology, Jewish General Hospital, for their assistance with patient recruitment. The authors thank Adrienne Liberman for assistance with figures. Funding sources Canadian Institutes of Health Research (HMS), Parkinson Canada (MG and HMS) and Fonds de recherche du Québec – Santé/Parkinson Canada (MC). Conflicts of interest HMS and MG have served as officers of HemOx Biotechnologies. HMS has served as consultant to Osta Biotechnologies, Molecular Biometrics Inc., TEVA Neurosciences, and Caprion Pharmaceuticals. MC, LJ, JMG, AMV, ESN, SM and OC have no conflicts of interest to declare. Financial disclosures of all authors (for the preceding 12 months) HMS is an officer of HemOx Biotechnologies, recently received research funding from: Canadian Institutes of Health Research, Immunotec Inc., and is an inventor on a patent portfolio related to HO-1 diagnostics and therapeutics for neurodegenerative diseases and cancer. MG is an officer of HemOx Biotechnologies, and has received funding from Parkinson Canada. MC has received funding from Fonds de recherche du Québec – Santé/Parkinson Canada (joint). LJ and JMG have received funding from Mitacs. AMV, ESN, SM and OC have no financial disclosures to report.

206 Author contributions HMS and MC conceived the study. MC, JMG, ESN, SM, OC and MG contributed to organization and execution of the study. MC, LJ and AMV performed statistical analyses of the data. MC and HMS wrote the manuscript.

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213 16.7. Chapter 4 Tables and Figures Table 1. Demographic and comorbidity distribution between study groups. With the exception of age and sex, values reported represent percentage of participants who responded ‘yes’ to respective comorbidity. Ctl, non-neurological control; F, female; M, male; PD, Parkinson’s disease; SEM, standard error of the mean.

Comorbidity Ctl (n = 83) PD (n = 84) P-value

Age [Mean (SEM)] 67.31 (1.04) 71.39 (1.38) 0.02 Sex (M/F) 39/44 49/35 0.19 Smoker (%) 0 0 N/A Cancer (%) 13.30 19.30 0.40 Diabetes (%) 18.10 14.60 0.70 Liver disease (%) 4.80 3.60 1.00 Arthritis (%) 28.90 39.80 0.19 Neurological disease 0 100.00 <0.001 (%) Tuberculosis (%) 1.20 2.40 0.99 Asthma (%) 11.90 4.80 0.17 Kidney disease (%) 2.40 6.10 0.43 Hypertension (%) 43.40 45.80 0.88 Heart disease (%) 4.80 18.10 0.02 Bleeding diathesis (%) 3.60 4.80 0.99 Vitamin intake (%) 43.40 39.00 0.68

214 A C E **

AUC: 78.6%

* B D F AUC: 74.0%

Figure 1. Salivary miR-153 and miR-223 expression levels in idiopathic PD patients relative to non-neurological controls. Mean expression levels of miR-153 (A) and miR-223 (B) were determined by reverse transcriptase quantitative polymerase chain reaction and analyzed using the delta-delta cycle threshold value (2-DDCt) method relative to experimental and endogenous controls. Data were normalized via log transformation and reported for miR-153 (C) and miR-223 (D). Midline in box and whisker plots depicts the median, with upper and lower limits representing maximum and minimum values, respectively. ROC curves were estimated for miR- 153 (E) and miR-223 (F), with AUC indicated. N = 77 and 83 for non-neurological Ctl and PD groups, respectively. AUC, area under the curve; Ctl, control; miR, microRNA; PD, Parkinson’s disease; ROC, receiver operating characteristic. *, p < 0.05; **, p < 0.01.

215 A C E

AUC: 58.9%

B D F

AUC: 52.7%

Figure 2. Salivary miR-7a and miR-7b expression levels in idiopathic PD patients relative to non- neurological controls. Mean expression levels of miR-7a (A) and miR-7b (B) were determined by reverse transcriptase quantitative polymerase chain reaction and analyzed using the delta-delta cycle threshold value (2-DDCt) method relative to endogenous and experimental controls. Data were normalized via log transformation and reported for miR-7a (C) and miR-7b (D). Midline in box and whisker plots depicts the median, with upper and lower limits representing maximum and minimum values, respectively. ROC curves were estimated for miR-7a (E) and miR-7b (F), with AUC indicated. N = 63 and 77, for non-neurological Ctl and PD groups, respectively. AUC, area under the curve; Ctl, control; miR, microRNA; PD, Parkinson’s disease; ROC, receiver operating characteristic.

216 A B C

D E F

Figure 3. Correlation analysis of LEDD and levodopa exposure with miR-153 and miR-223 expression in idiopathic PD patients. Mean LEDD levels among H&Y stages of idiopathic PD patients tested (A). Correlation analysis of LEDD and miR-153 (B) or miR-223 (C) expression levels. Mean levodopa exposure levels among H&Y stages of idiopathic PD patients tested (D). Correlation analysis of levodopa exposure and miR-153 (E) or miR-223 (F) expression levels. N = 22 to 36 per group. H&Y, Hoehn and Yahr; L-dopa, levodopa; LEDD, levodopa equivalent daily dose.

217 A ** B 0.2 * 0.5 * 0.0 77 24 36 23 0.0 77 24 36 23 -0.2

-0.5 -0.4 Log Relative Expression -0.6 Log Relative Expression -1.0

Ctl Ctl H&Y 1H&Y 2 H&Y 1H&Y 2 H&Y 3+ H&Y 3+ C D E

Figure 4. MiR-153 and miR-223 expression as functions of H&Y staging and disease duration of idiopathic Parkinson’s disease patients. Mean expression levels (normalized via log- transformation) of miR-153 (A) and miR-223 (B) for each H&Y stage were determined by reverse transcriptase quantitative polymerase chain reaction and analyzed using the delta-delta cycle threshold value (2-DDCt) method relative to endogenous and experimental controls. Values shown within bars denote number of subjects for A and B. (C) Disease duration separated by H&Y staging (N = 20-35 per group) and correlation analysis with miR-153 (D) or miR-223 (E). Ctl, control; H&Y, Hoehn and Yahr; miR, microRNA. *, p < 0.05; **, p < 0.01.

218 Supplementary Table 1. Primer sequences for microRNA and mRNA probes. F, forward; R, reverse. Primer Sequence (5’ to 3’) RNU44 forward F: cctggatgatgatagcaaatgc; R: gagctaattaagaccttcatgtt mmu-miR-7a tggaagactagtgattttgttgt mmu-miR-7b tggaagacttgtgattttgttgt mmu-miR-153 ttgcatagtcacaaaagtgatc mmu-miR-223 tgtcagtttgtcaaatacccca

219 Supplementary Table 2. Unconditional Multivariate Logistic Regression models for diagnosis of PD. The odds of PD was modeled for: (1) miR-153 and (2) miR-223. Final models, selected based on Bayesian information criterion (BIC), were adjusted for age (cubic polynomial), sex, arthritis and heart disease. 95% CILower, lower 95% confidence limit of odds ratio; 95% CIHigher, upper 95% confidence limit of odds ratio.

Covariate Odds Ratio CILower CIHigher Log(miR-153) 0.46 0.29 0.72 Age 0.01 0.0006 0.36 Age2 1.06 1.01 1.11 miR-153 Age3 0.99 1.00 1.00 Sex 1.87 0.88 3.98 Arthritis 1.51 0.68 3.37 Heart disease 2.48 0.71 8.72 Log(miR-223) 0.84 0.69 1.04 Age 0.03 0.001 0.56 Age2 1.05 1.01 1.10 miR-223 Age3 0.99 1.00 1.00 Sex 1.76 0.85 3.63 Arthritis 1.52 0.70 3.31 Heart disease 2.99 0.89 10.05

220

Supplementary Figure 1. Ratio of oligomeric a-synuclein, total a-synuclein and HO-1 to miR- 153 and miR-223 expression in idiopathic PD subjects. Oligomeric a-synuclein was measured by ELISA in idiopathic PD and non-neurological control subjects. Ratios of oligomeric a- synuclein/miR-153 (A) and oligomeric a-synuclein/miR-223 (C). Correlation analysis (Pearson correlation) between oligomeric a-synuclein and miR-153 (B) and miR-223 (D). Total a-synuclein was measured by ELISA in idiopathic PD and non-neurological control subjects. Ratios of total a- synuclein/miR-153 (E) and total a-synuclein/miR-223 (G). Correlation analysis (Pearson correlation) between total a-synuclein and miR-153 (F) and miR-223 (H). HO-1 was measured by ELISA in idiopathic PD and non-neurological control subjects, with ratios of HO-1/miR-153 (I) and HO-1/miR-223 (J) depicted. MiRNA expression levels were determined by reverse transcriptase quantitative polymerase chain reaction and analyzed using the delta-delta cycle threshold value (2-DDCt) method relative to endogenous and experimental controls. All data was log-transformed for normal distribution. Values shown within bars denote number of subjects. *, p < 0.05. Ctl, non-neurological controls; PD, Parkinson’s disease.

221 17. Transition 4: Understanding the Reflection of Central Nervous System Changes in Peripheral Biofluids Findings from parkinsonian GFAP.HMOX18.5-19m mice and human Parkinson disease (PD) saliva, described in Chapters 3 and 4, raise the intriguing question as to how discrete pathological changes within the central nervous system (CNS) become reflected in the periphery. GFAP.HMOX18.5-19m mice were engineered to conditionally overexpress HMOX1 in astrocytes from mid-to-late life, resulting in behavioural, pathological and biochemical alterations reminiscent of PD (see Chapters 1 and 2). This neural heme oxygenase-1 (HO-1) overexpression (beginning at 8.5 months of age) is the primary insult that evokes a decrease in circulating microRNA (miRNA)-153 and miR-223 levels by 11 months of age, which continues to progress at least until 19 months of age (see Chapter 3). Similarly, human PD patients show enhanced astroglial HO-1 post-mortem (Schipper et al. 1998) and diminished salivary miR-153 and miR-223 expression levels as early as Hoehn and Yahr stage 1 (see Chapter 4). The mechanism by which CNS miRNA and protein alterations are recapitulated in peripheral biofluids, as supported by our model, may involve extracellular vesicles (EVs). Further, considering the fact that HMOX1 does not contain a signal peptide sequence destining the protein it encodes for the secretory system, EVs represent an attractive alternative method of secretion. In this next and final chapter, total EVs and CNS-derived EVs were isolated from five different human biofluids and assessed for HO- 1 content. Minimal literature exists concerning HO-1 and EVs, therefore our main focus was to evaluate whether this stress protein, previously implicated in PD and its downstream pathologies, is present within peripheral EV cargo of healthy human subjects. The study described in Chapter 5 was conducted in collaboration with Dr. Mervyn Gornitsky, Dr. Ana Velly and Dr. Shaun Eintracht, Chief of the Division of Medical Biochemistry (Jewish General Hospital).

222 18. Chapter 5: Characterization and Heme Oxygenase-1 Content of Extracellular Vesicles in Human Biofluids

Accepted for publication in Journal of Neurochemistry (2020).

Author List: Marisa Cressatti1,2, Julia M. Galindez1,2, Lamin Juwara1,3, Natalie Orlovetskie1,2, Ana M. Velly1,4,5, Shaun Eintracht6, Adrienne Liberman1, Mervyn Gornistky1,4,5, and Hyman M. Schipper1,2¶

1Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada 2Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada 3Quantitative Life Sciences, McGill University, Montreal, QC, Canada 4Department of Dentistry, Jewish General Hospital, Montreal, QC, Canada 5Faculty of Dentistry, McGill University, Montreal, QC, Canada 6Department of Diagnostic Medicine, Jewish General Hospital, Montreal, QC, Canada

Laboratory of Origin: Dr. Hyman Schipper Laboratory, Room F428, Lady Davis Institute for Medical Research, Jewish General Hospital, 3999 Cote Sainte-Catherine Road, Montreal, Quebec, H3T 1E2, Canada

Short Title: Heme oxygenase-1 in extracellular vesicles

223 18.1. Chapter 5 Abstract and Graphical Abstract Heme oxygenase-1 (HO-1), a highly inducible stress protein that degrades heme to biliverdin, carbon monoxide and free ferrous iron, is increased in blood and other biofluids of subjects with various systemic and neurological disorders. HO-1 does not contain an N-terminal signal peptide and the mechanism responsible for its secretion remains unknown. Extracellular vesicles (EVs) are membrane-bound inclusions that transport microRNAs, messenger RNAs, lipids and proteins among diverse cellular and extracellular compartments. The objective of the current study was to determine whether EVs in human biofluids contain HO-1, and whether the latter may be transported in EVs from brain to periphery. Total, L1 cell adhesion molecule protein (L1CAM)- enriched (neuron-derived) and glutamate aspartate transporter 1 (GLAST)-enriched (astrocyte- derived) EVs were purified from five different human biofluids (saliva [n=40], plasma [n=14], serum [n=10], urine [n=10] and cerebrospinal fluid [n=11]) using polymer precipitation and immuno-affinity-based capture methods. L1CAM-enriched, GLAST-enriched and L1CAM/GLAST- depleted (LGD) EV, along with EV-depleted (EVD), fractions were validated by nanoparticle tracking analysis, enzyme-linked immunosorbent assay (ELISA) and Western blot. HO-1 was assayed in all fractions using ELISA and Western blot. The majority of HO-1 protein was localized to LGD, L1CAM-enriched and GLAST-enriched EVs of all human biofluids surveyed after adjusting for age and sex, with little HO-1 protein detected in EVD fractions. Taken together, HO-1 protein in human biofluids is predominantly localized to EV compartments. A substantial proportion of EV HO-1 in peripheral human biofluids is derived from the central nervous system and may contribute to the systemic manifestations of various neurological conditions.

Keywords: Astrocytes, biofluids, extracellular vesicles, heme oxygenase-1, neurons.

224 Biofluid Astrocytes GLAST Saliva HO-1

Extracellular Vesicles Plasma

HO-1

GLAST

Serum HO-1

Neurons L1CAM HO-1 Urine

HO-1 CSF L1CAM = Extracellular vesicles Caption: Heme oxygenase-1 (HO-1) is a highly inducible stress protein involved in neurological disease and is detectable in numerous peripheral biofluids. HO-1 is not secreted via classical secretory pathways. The current study indicates that HO-1 is predominantly transported by extracellular vesicles (EVs) in five different human biofluids. EVs derived from astrocytes (GLAST- containing) and neurons (L1CAM-containing) isolated from these peripheral biofluids also contain HO-1. The latter may provide a ‘window’ into nervous system (patho)physiology and facilitate disease biomarker discovery.

225 18.2. Chapter 5 Introduction Heme oxygenase-1 (HO-1) is a 32 kDa stress protein that acts in concert with cytochrome P450 reductase and NADPH to catalyze the oxidative cleavage of heme into biliverdin, free ferrous iron and carbon monoxide. Biliverdin is further converted to bilirubin by the cytosolic enzyme biliverdin reductase. HO-1 plays a major role in disease, in part due to numerous response elements in the HMOX1 promoter region which render it highly inducible by a number of different stressors. This includes heme, dopamine, β-amyloid, hydrogen peroxide, helper T cell cytokines, heavy metals, ultraviolet light, hyperoxia, prostaglandins, nitric oxide, peroxynitrite, lipopolysaccharide, oxidized lipid products and various growth factors (Dennery 2000, Loboda et al. 2008, Schipper 2000, Kinobe et al. 2006). In numerous disease states, the conversion of pro- oxidant heme to the antioxidants, biliverdin and bilirubin by HO-1 and biliverdin reductase, respectively, may help restore a more favorable tissue redox status (Schipper et al. 2019). However, in some cell types and under certain conditions, heme-derived iron and carbon monoxide may amplify intracellular oxidative stress and exacerbate the disease process (Schipper et al. 2019). Whether free radical injury due to intracellular liberation of iron and carbon monoxide or the antioxidant benefits of a declining heme to bilirubin ratio predominate may depend on the chemistry of the local redox microenvironment as well as the intensity and duration of HO-1 expression (Galbraith 1999, Suttner and Dennery 1999). HO-1 protein has been evaluated widely as a potential biomarker of various disease states due to the highly inducible nature of HO-1 and its dual role, whether beneficial or detrimental, in disease pathogenesis (Schipper et al. 2019). In addition to being detected in human tissues, including liver, spleen, kidney, testes, heart, lung, placenta and brain, the presence of HO-1 has also been shown in diverse circulating biofluids (Schipper et al. 2019). It has been reported that HO-1 protein is increased in the saliva and serum of Parkinson disease subjects (Song et al. 2018, Mateo et al. 2010), serum of rheumatoid arthritis subjects (Yuan et al. 2016), serum of individuals with preeclampsia (Eide et al. 2008), plasma of coronary and peripheral artery disease and atherosclerosis subjects (Kishimoto et al. 2018a, Kishimoto et al. 2018b) and urine of early diabetic nephropathy subjects (Li et al. 2017); and decreased in the cerebrospinal fluid (CSF) and plasma of Alzheimer disease subjects (Anthony et al. 2003).

226 Despite the fact that HO-1 protein is detectable in numerous circulating biofluids, HMOX1 does not code for an amino-terminus signal peptide destining the protein to the secretory pathway. HO-1 is normally anchored in the endoplasmic reticulum by a carboxyl-terminus transmembrane segment. The mechanism subserving the egress of HO-1 from the endoplasmic reticulum to the circulation remains to be elucidated. Extracellular vesicles (EVs) have emerged as a rich source of potential biomarkers, inasmuch as these membrane-bound structures facilitate intercellular transport of DNA, RNA, proteins and lipids (Margolis and Sadovsky 2019). All cells are capable of releasing EVs, which are highly heterogeneous in size, cargo, membrane composition, biogenesis and biological function (Margolis and Sadovsky 2019). Based on the current knowledge of their biogenesis, EVs can be broadly divided into two main populations: exosomes and microvesicles (van Niel et al. 2018). Exosomes (30 – 150 nm in diameter) are intraluminal vesicles formed by the inward budding of the endosomal membrane during maturation of multivesicular endosomes, which are intermediates within the endosomal system, and secreted upon fusion of multivesicular endosomes with the cell surface (van Niel et al. 2018). Microvesicles (50 – 1000 nm in diameter), on the other hand, are generated by the outward budding and fission of the plasma membrane and the subsequent release of vesicles to the extracellular space (van Niel et al. 2018). Other subpopulations of EVs proposed include apoptotic bodies, oncosomes, ectosomes and microparticles (Thery et al. 2018). The presence of HO-1 messenger RNA (mRNA) or protein in EVs has been minimally described in the literature. El-Rifaie and colleagues reported increased HO-1 mRNA in exosomes isolated from peripheral blood mononuclear cells of psoriasis patients (El-Rifaie et al. 2018). Furthermore, exosomes released from bovine granulosa cells challenged with hydrogen peroxide in vitro resulted in significant elevation of nuclear factor erythroid 2-related factor 2 mRNA and downstream antioxidants (e.g. catalase, thioredoxin), though lower levels of HO-1 mRNA were recorded (Saeed-Zidane et al. 2017). With respect to cell-to-cell communication, EVs derived from human lung mesenchymal stem cells under inflammatory conditions were shown to increase nuclear factor kappa-light-chain-enhanced of activated B cells and HO-1 mRNA in an in vitro human model of cystic fibrosis (Zulueta et al. 2018). Finally, HO-1 protein has also been detected in numerous mass spectrometry analyses of EVs released from various cancer cell types

227 (summarized in Vesiclepedia; see [Kalra et al. 2012]), as well as in healthy human urine exosomes (Wang et al. 2012). The objectives of the current study were to determine whether EVs isolated from diverse human biofluids contain HO-1 protein, and whether HO-1 protein may be transported in EVs from the central nervous system (CNS) to periphery. To ascertain the latter, we employed EV isolation techniques enriching for EVs derived from astrocytes and neurons of the CNS (Thery et al. 2018, Goetzl et al. 2016, Mustapic et al. 2017). 18.3. Chapter 5 Materials and Methods Population This study was approved by the Research Ethics Committee of the Jewish General Hospital (JGH; Montreal, Canada) (Ethics Protocol Numbers: CODIM-MBM-09-062 and CODIM-MBM-14-170). This study was not pre-registered. A total of 85 human subjects were recruited from the JGH for this study. Subjects donating saliva were recruited between July and August 2014 from the Departments of Medicine, Dentistry and Ophthalmology. Subjects donating plasma were recruited between January 2011 and October 2017 from the JGH Alzheimer Risk Assessment Clinic (Schipper et al. 2011). Written informed consent was obtained from all subjects donating saliva or plasma. Exclusion criteria for subjects donating saliva or plasma included cigarette smoking within the past year, severe periodontal disease (saliva only), history of oral cancer (saliva only), active systemic inflammatory disease (e.g. tuberculosis, human immunodeficiency virus, rheumatoid arthritis, etc.), current alcoholism or illicit drug abuse, recent exposure to neuroleptic medications and evidence of neurological disorder or early-stage dementia (Montreal Cognitive Assessment [MoCA] score < 26, etc.) (plasma only). Subjects donating saliva and plasma were randomly selected (simple randomization) from the above-mentioned biobanks. Subjects donating serum, urine or CSF were anonymously recruited between August and November 2019 through the Department of Diagnostic Medicine. Exclusion criteria for these samples included the presence of traces of blood or other visible sample abnormalities (e.g. discoloration, atypical viscosity, etc.). The following samples were collected from the 85 subjects recruited: 40 saliva samples, 14 plasma samples, 10 serum samples, 10 urine samples and 11 CSF

228 samples. All samples were collected and all experiments (described below) were conducted between regular business hours (9:00 AM to 5:00 PM EST). Clinical and demographic data Demographics and medical history questionnaires (designed by our research team and approved by the JGH Research Ethics Committee) were available on all subjects providing saliva or plasma. Age and sex demographics were available on all subjects, with the exception of missing sex for one subject. Biofluid collection and processing Saliva was collected as whole, unstimulated saliva at least 30 min after food or liquid ingestion by passive drooling and kept at 4°C for a maximum of 3 h until further processing. Before analysis, saliva was centrifuged at 8,960 x g (10,000 rpm) for 20 min at 4°C to remove residual food particles and reduce sample viscosity. Supernatants were stored at -80°C, and protease inhibitors (Roche; Catalogue Number: 11836153001; year of purchase [YOP]: 2011-2019) were added upon first thaw. Plasma was isolated by centrifugation of fresh whole blood (containing ethylenediaminetetraacetic acid) layered with Ficoll-Paque PLUS density gradient media (GE Healthcare; Catalogue Number: GE171440-02; YOP: 2011-2017). Centrifugation was done at 200 x g for 30 min at 4°C. Protease inhibitors (Roche; Catalogue Number: 11836153001; YOP: 2011- 2019) were added prior to storing at -80°C. We previously determined that long-term storage does not significantly affect sample composition (Cressatti et al. 2019a). Serum, urine and CSF samples were collected and kept at 4°C until further processing (EV isolation), no longer than 24 hours. EV isolation and L1CAM- and GLAST-EV enrichment EVs were purified using Total Exosome Isolation Reagent (Thermo Fisher; Catalogue Number: 4484453 for saliva and CSF; Catalogue Number: 4484450 for plasma; Catalogue Number: 4478360 for serum; Catalogue Number 4484452 for urine; YOP: 2019) specific to the biofluid. See Table 1 for specific biofluid-dependent workflow. Plasma samples were subjected to an additional proteinase K (Thermo Fisher; Catalogue Number: 4484450; YOP: 2019) step prior to the addition of Total Exosome Isolation reagent.

229 For L1CAM- and GLAST-EV enrichments, modified protocols from Mustapic et al. (Mustapic et al. 2017) and Goetzl et al. (Goetzl et al. 2016) were employed. After total EV isolation (Table 1), the supernatant (EV-depleted [EVD] fraction) was collected and stored, while the EV pellets were resuspended in 500 µl deionized water. To the EV suspension, 4 µg of either mouse anti-human L1 cell adhesion molecule protein (L1CAM) biotinylated antibody (research resource identifier [RRID; see scicrunch.org]: AB_2043813; YOP: 2018-2019) or rabbit anti-human glutamate aspartate transporter 1 (GLAST) biotinylated antibody (Novus Biologicals; Catalogue Number: NB100-1869B; YOP: 2018-2019) in a total volume of 50 µl 3% bovine serum albumin (BSA) (Sigma-Aldrich; Catalogue Number: A1933; YOP: 2015), and incubated with agitation for 1 h at 4°C. Next, 15 µl Pierce Streptavidin UltraLink Resin (Thermo Fisher; Catalogue Number: 53117; YOP: 2018-2019) were added to the EV suspension and incubated with agitation for 30 min at 4°C. After adjusting the pH to approximately 7.0 with 1 M Tris-HCl pH 8.0 (BioShop; Catalogue Number: TRS003; YOP: 2017), suspensions were centrifuged at 200 x g for 10 min at 4°C. Supernatants were collected (L1CAM/GLAST-depleted [LGD] EVs) and pellets were resuspended in 200 µl 0.1 M glycine-HCl (BioShop; Catalogue Number: GLN001; YOP: 2019) pH 3.0 followed by vigorous vortex for 30 s. Suspensions were then centrifuged at 4500 x g for 10 min at 4°C to detach L1CAM-positive EVs or GLAST-positive EVs from bead-antibody complexes, respectively. The supernatants (L1CAM- or GLAST-enriched EVs) were transferred to new tubes containing 25 µl 10% BSA (Sigma-Aldrich; Catalogue Number: A1933; YOP: 2015) and 15 µl 1M Tris-HCl pH 8.0 (BioShop; Catalogue Number: TRS003; YOP: 2017). Protease inhibitors (Roche; Catalogue Number: 11836153001; YOP = 2019) were added to each fraction prior to storage at - 80°C to prevent protease degradation and ensure intact EVs upon thaw. All buffers used for EV isolation were filter-sterilized with 0.22 µm (Ultident; Catalogue Number: 229747; YOP: 2019) and 0.02 µm (Sigma-Aldrich; Catalogue Number: WHA68091002; YOP: 2019) membrane filters to avoid potential contamination. Nanoparticle tracking analysis (NTA) For the concentration and size distribution of EVs, NTA was carried out using NanoSight NS500 instrument with 532 nm laser (NanoSight Ltd.; Catalogue Number: NS500; YOP: 2011). Three recordings of 30 s at 37°C were obtained and processed using NanoSight NTA software (version

230 3.0). Plasma LGD EVs were diluted 1:500 in deionized water, while all other fractions from plasma and additional biofluids tested were undiluted. Enzyme-linked immunosorbent assay (ELISA) Levels of protein were assayed in each EV fraction of subjects by sandwich ELISA using kits specific for CD63 (System Biosciences; Catalogue Number: EXEL-ULTRA-CD63-1; YOP: 2019) and HO-1 (Abbexa; Catalogue Number: 252635; YOP: 2019), according to the manufacturer instructions. For CD63 detection using ExoELISA-ULTRA Complete Kit (System Biosciences; Catalogue Number: EXEL-ULTRA-CD63-1; YOP: 2019), intra- and inter-assay variabilities were minimal and sensitivity was ≥4 ng/ml (System Biosciences). Original samples were diluted 1:4 with coating buffer and plated in duplicate. The detection range for HO-1 using the HMOX1 ELISA Kit (Abbexa; Catalogue Number: 252635; YOP: 2019) was 0.16-10 ng/ml with a sensitivity of 0.1 ng/ml and intra-assay and inter-assay variability of <10%. For HO-1 measurements, original samples were diluted 1:4 with standard dilution buffer prior to plating in duplicate. Regression for all respective standard curves were highly linear with an average of r2>0.90. Concentrations of HO-1 were standardized to EV abundance (CD63-positive) to generate “relative HO-1” levels. Western blot EV and EVD fractions were boiled for 5 min in the presence of 2X Laemmli buffer (4% SDS, 20% glycerol, 10% 2-mercaptoethanol, 0.004% bromophenol blue and 0.125 M Tris-HCl pH 6.8) (Sigma-Aldrich; Catalogue Number: S3401; YOP: 2018) before electrophoresis on 7-10% SDS- PAGE and transferred to a polyvinylidine difluoride membrane with 0.45 μm pore size (Bio-Rad; Catalogue Number: 1620177; YOP: 2017). As positive markers of EVs, anti-CD63 rabbit polyclonal (RRID: AB_2561274; YOP: 2019) at 1:5000, anti-tumor susceptibility gene 101 protein (TSG101) rabbit polyclonal (System Biosciences; Catalogue Number: EXOAB-TSG101-1; YOP: 2019) at 1:3000, anti-apoptosis linked gene 2 product (ALG-2)-interacting protein X (Alix) rabbit polyclonal (RRID: AB_2754981; YOP: 2018) at 1:10000, anti-L1CAM mouse monoclonal (RRID: AB_448025; YOP: 2018) at 1:10000 or anti-GLAST rabbit polyclonal (Novus Biologicals; Catalogue Number: NB100-1869B; YOP: 2018-2019) at 1:1000 antibodies were used to blot membranes or re-blot mildly stripped membranes (Abcam protocol). Anti-HO-1 rabbit polyclonal antibody (RRID: AB_10618757; YOP: 2019) at 1:1000 dilution was used to blot membranes for HO-1

231 immunoreactivity. Subsequently, anti-rabbit (RRID: AB_2337913; YOP: 2015) or anti-mouse (RRID: AB_10015289; YOP: 2015) IgG horseradish peroxidase antibody at 1:8000 were used to secondarily blot membranes. Clarity™ Western ECL Blotting Substrate (Bio-Rad; Catalogue Number: 1705060; YOP: 2018) was used for development and protein expression visualization. Statistical analysis Sample size, in this exploratory study, was determined based on the minimum sample size recommendations for linear regression (n = 5-10 per covariate), as described by Harrell et al. (Harrell et al. 2015). A heuristic check for normality was performed by plotting the distribution of the data, as well as additional analysis via Shapiro-Wilk's test (p > 0.05). Normality of the error terms (linear regression) was assessed through the diagnostic Q-Q plots. Analysis of variance (ANOVA) was used to assess differences in normally distributed variables (size of EVs and EV concentration/abundance) between biofluid groups (saliva, plasma, serum, urine, CSF) or between EV groups (LGD, L1CAM-enriched and GLAST-enriched EV fractions). Mann-Whitney and Kruskal-Wallis non-parametric tests were employed for EV group comparisons (EVD, LGD, L1CAM-enriched and GLAST-enriched EV fractions) in samples whose relative HO-1 level in each group was not normally distributed or sample size was small. To compare relative HO-1 levels (dependent variable) by type of EV fraction (independent variable) in various human biofluids, we performed a series of multivariable linear regression analyses adjusted by age and sex. No outliers were removed based on analysis with Cook’s distance and standardized residuals (greater than 3). All parametric data (normally distributed) are presented as means (standard error of the mean [SEM]), while all nonparametric data (not normally distributed) are presented as medians (lower interquartile [Q1]; upper interquartile [Q3]). No specific blinding was performed in the current set of experiments due to the exploratory nature of comparisons being evaluated. For all analyses, the two-tailed α-significance level was 5% and were performed with R statistical software (version 3.4.4).

232 18.4. Chapter 5 Results Demographics Table 2 shows the group demographics for each biofluid. Out of the 85 subjects, 49 were females (57.6%), 35 were males (41.2%) and the sex of one subject was unknown (1.2%) (Table 2). The median age of all subjects tested was 48.0 years old (Q1 = 33.0; Q3 = 62.0) (Table 2). EV quantification EVs were isolated with polymer-based precipitation followed by cell-specific enrichment via immuno-affinity precipitation. NTA confirmed an average size of 361.3 nm (SEM = 24.7 nm) for saliva LGD EVs, 395.4 nm (SEM = 40.7 nm) for plasma, 292.6 nm (SEM = 49.6 nm) for serum, 310.9 nm (SEM = 49.9 nm) for urine and 356.0 nm (SEM = 48.8 nm) for CSF (Fig. 1A). The average size of isolated LGD EVs across all biofluids assayed was 343.2 nm (SEM = 4.5 nm), and average size did not significantly differ among biofluids (P = 0.50) (Fig. 1A). The average size of isolated L1CAM- enriched EVs across all biofluids assayed was 323.3 nm (SEM = 6.1 nm), and average size did significantly differ among biofluids (P = 0.01) (Supplementary Fig. 1). Finally, the average size of isolated GLAST-enriched EVs across all biofluids assayed was 314.5 nm (SEM = 3.4 nm), and average size did not significantly differ among biofluids (P = 0.25) (Supplementary Fig. 2). Concentration measured for LGD EVs by NTA was 4.07 x 109 (SEM = 2.63 x 108) particles/ml for saliva, 6.30 x 109 (SEM = 2.32 x 107) particles/ml for plasma, 9.52 x 1010 (SEM = 1.95 x 108) particles/ml for serum, 3.74 x 109 (SEM = 4.03 x 108) particles/ml for urine and 1.40 x 109 (SEM = 5.20 x 107) particles/ml for CSF (Fig. 1). For NTA concentration measurements for L1CAM-enriched and GLAST-enriched EVs, see Supplementary Figures 1 and 2, respectively. Concentrations were also confirmed by ELISA (Fig. 2-6A, B), and values were found to be within range from NTA measurements. EV abundance (concentration) varied between fractions in each of the biofluids assayed (Fig. 2-6A). Low to moderate levels of EV contamination were detected in the EVD fractions from each of the biofluids assayed: 11.5% for saliva, 8.6% for plasma, 21.4% for serum and 5.5% for urine (Fig. 2-5B). There was no apparent EV contamination in CSF EVD fractions (Fig. 6B). Western blotting was used to detect the presence of CD63, TSG101 and Alix bands (EV positive controls) (Fig. 2-6C). CD63 is a transmembrane tetraspanin protein associated to the endosome, while TSG101 and Alix are cytosolic proteins localized to EVs with lipid or

233 membrane protein-binding abilities (Thery et al. 2018, van Niel et al. 2018). Western blotting was also used to detect the presence of L1CAM and GLAST bands (enriched cell-type specific populations) (Fig. 2-6C) and demonstrate the lack of Golgi matrix protein 130 and tri-methyl- histone H3 bands (EV negative controls (Li et al. 2018)) in all EV populations (data not shown). Protein bands of EVD fractions from each of the biofluids assayed were faint or nil (Fig. 2-6C). HO-1 Quantification Levels of HO-1 protein were assayed in each EV fraction and EVD fractions by ELISA and standardized to respective EV abundance (relative HO-1); the 32 kDa and 50-70 kDa bands (see Section 5) were confirmed by Western blot. Variability in age and sex distributions were accounted for in the multivariable linear regression models presented (Table 3). The regression coefficients (β) corresponding to the type of EV represent change in relative HO-1 levels from the reference group (LGD EVs), after adjusting for age and sex (Table 3). Unless otherwise stated, HO- 1 protein was detected in all EV fractions derived from each of the biofluids surveyed (Fig. 2-6C, D). Pooled EVs from each biofluid consistently exhibited significantly greater levels of HO-1 compared to EVD fractions (Fig. 2-6E) indicating that the majority of circulating HO-1 is transported by EVs. When comparing levels of total HO-1 protein within pooled EV fractions, significant differences were also observed among biofluids (Fig. 7). Plasma HO-1 levels were significantly diminished compared to saliva (P < 0.0001), serum (P = 0.008) and CSF (P < 0.0001); CSF HO-1 concentrations were significantly greater than those of urine (P = 0.003) (Fig. 7). Overall, CSF and saliva EVs displayed the highest levels of HO-1 protein (Fig. 7). Saliva – In comparison to salivary LGD EVs, relative HO-1 protein concentrations were significantly lower in GLAST-enriched EVs (β = -2.5, confidence intervals [CI] = -3.7, -1.2; P < 0.001) (Fig. 2D). The 32 kDa band was present in LGD, L1CAM-enriched and GLAST-enriched EV fractions, while no band was detected in the EVD fraction (Fig. 2C). HO-1 protein levels were significantly higher in pooled EV fractions compared to the EVD fraction (P < 0.0001) (Fig. 2E). Plasma – In comparison to plasma LGD EVs, relative HO-1 protein levels were significantly reduced in L1CAM-enriched EVs (β = -8.1, CI = -12.9, -3.3; P = 0.002) and GLAST-enriched EVs (β = -2.5, CI = -13.1, -3.5; P = 0.001) (Fig. 3D). The 32 kDa band was present in LGD and GLAST- enriched EV fractions, though only weakly detectable in L1CAM-enriched EVs, and no band was

234 detected in the EVD fraction (Fig. 3C). A trend towards increased HO-1 protein levels was observed in pooled EV fractions compared to the EVD fraction (P = 0.07) (Fig. 3E). Serum – In comparison to serum LGD EVs, relative HO-1 protein concentrations were not significantly different among L1CAM-enriched EVs (β = -2.6, CI = -6.2, 0.9; P = 0.1) and GLAST- enriched EVs (β = -1.7, CI = -5.3, 1.8; P = 0.3) (Fig. 4D). The 32 kDa band was present in LGD, L1CAM-enriched and GLAST-enriched EV fractions, while no band was detected in the EVD fraction (Fig. 4C). HO-1 protein levels were significantly higher in pooled EV fractions compared to the EVD fraction (P < 0.0001) (Fig. 4E). Urine – In comparison to urinary LGD EVs, relative HO-1 protein levels were diminished in L1CAM-enriched EVs, though this did not achieve statistical significance (β = -14.0, CI = -28.9, 0.8; P = 0.06) (Fig. 4E). Minimal HO-1 protein was detected in L1CAM-enriched EVs from urine by ELISA (Fig. 5D) which was not consistent with Western blot analysis (Fig. 5C). The 32 kDa band was present in LGD, L1CAM-enriched and GLAST-enriched EV fractions but not in the EVD fraction (Fig. 5C). Similar to other biofluids tested, urinary HO-1 protein levels were significantly higher in pooled EV fractions compared to the EVD fraction (P = 0.03) (Fig. 5E). CSF – In comparison to CSF LGD EVs, relative HO-1 protein concentrations were not significantly different among L1CAM-enriched EVs (β = -12.3, CI = -34.3, 9.8; P = 0.3) and GLAST- enriched EVs (β = -1.7, CI = -23.7, 20.4; P = 0.9) (Fig. 6D). The 32 kDa band was present in LGD, L1CAM-enriched and GLAST-enriched EV fractions but was not detected in the EVD fraction (Fig. 6C). HO-1 protein levels were significantly elevated in pooled EV fractions relative to the EVD fraction (P < 0.0001) (Fig. 6E). 18.5. Chapter 5 Discussion EVs were isolated by two consecutive EV separation techniques, one high recovery/low specificity method (polymer precipitation) and one low recovery/high specificity method (immuno-affinity precipitation), from five human biofluids (saliva, plasma, serum, urine, CSF). The isolated EVs were characterized by NTA, ELISA and Western blot. Using these techniques, we ascertained that full-length 32 kDa HO-1 protein is present in EVs of all biofluids surveyed and that HO-1 levels are significantly higher in pooled EV fractions than in EVD preparations. We further analyzed subpopulations of EVs, specifically L1CAM-enriched EVs derived from neurons

235 and GLAST-enriched EVs derived from astrocytes of the CNS. HO-1 protein was detected by ELISA in the CNS-derived EVs, with the exception of L1CAM-enriched EVs from urine. HO-1 protein was not detected by ELISA in urinary L1CAM-enriched EVs, though the 32 kDa band was observed under the denaturing conditions of Western blot (Forsstrom et al. 2015). Considering the native conditions of ELISA, the HO-1 protein detected using this technique likely reflects HO-1 present on the surface of the lipid bilayer of EVs (Holm et al. 2015, Koch et al. 1996, Jansen et al. 2009). The denaturing conditions of Western blot, on the other hand, could reflect both surface and intra-vesicular HO-1. The fact that L1CAM-enriched EVs from urine displayed the presence of HO- 1 by Western blot but not ELISA suggests that HO-1 may be present within the lipid bilayer, in addition to being found on the surface of EVs. However, the L1CAM-enriched EVs from urine were the only EVs to exhibit this phenomenon. Future studies may be warranted to determine whether HO-1 is present both on and within the lipid bilayer of EVs from biofluids. Considering the minimal HO-1 detected in EVD fractions, our results indicate that the majority of extracellular HO-1 in human biofluids is transported by EVs. The average size of EVs isolated using the current techniques was consistent across all human biofluids tested. According to NTA analysis, both smaller EVs such as exosomes (30 – 150 nm in diameter) and larger EVs such as microvesicles (50 – 1000 nm in diameter) were detected within each fraction of each biofluid isolated. EVs were most prevalent in the mid-to-larger end of the size spectrum. With respect to EV abundance, no significant differences in total amounts of EVs isolated were observed among specific fractions of certain biofluids. The current data set corroborates a previous study reporting higher EV concentrations in plasma than in CSF (Eitan et al. 2016). Future studies should include analyses of EV concentrations and sizes across biofluids as a function of age, ethnicity, disease and therapeutic interventions (e.g. medications, radiotherapy, etc.). In this regard, Rani and colleagues recently published a pilot study reporting that the number of L1CAM-enriched EVs isolated from saliva was significantly greater in Parkinson disease subjects compared to non-neurological controls (Rani et al. 2019). In the current study, we focused on the stress protein, HO-1 as possible cargo of human biofluid EVs given the perceived role of HO-1 in a broad spectrum of human systemic and neurological disorders (Schipper et al. 2019). To our knowledge, this is the first study to confirm

236 the presence of the 32 kDa HO-1 protein in EVs purified from human saliva, plasma, serum, urine and CSF. Results suggest that circulating HO-1 is predominantly transported by EVs. HO-1 immunoblots also disclosed the presence of a 50-70 kDa band in EVs derived from the five biofluid compartments, though its presence in plasma was faint. This upper band may represent either bound NADPH:cytochrome P450 reductase (Sato et al. 2013, Linnenbaum et al. 2012), a key electron donor in the HO-1-catalyzed heme degradation pathway, or a multimeric form of HO-1 (Linnenbaum et al. 2012, Hwang et al. 2009). Others have shown the presence of HO-1 mRNA in EVs (El-Rifaie et al. 2018), and mass spectrometry analyses have identified HO-1 in proteomic profiles of healthy human urinary EVs (Wang et al. 2012) as well as EVs released by various cancer cells (Kalra et al. 2012). In contradistinction to EV HO-1, total extracellular HO-1 has been studied extensively as a potential biomarker in various disease states. HO-1 mRNA and protein levels were found to be suppressed in Alzheimer disease CSF, plasma and blood mononuclear cells compared to non-neurological and neurological controls (Schipper et al. 2000, Anthony et al. 2003). In Parkinson disease subjects, HO-1 protein concentrations were significantly elevated in serum and saliva relative to non-neurological control subjects (Song et al. 2018, Mateo et al. 2010). Extracellular HO-1 protein has also been detected in plasma of subjects with atherosclerotic coronary and peripheral artery disease (Kishimoto et al. 2018a, Kishimoto et al. 2018b), serum of subjects with rheumatoid arthritis and ankylosing spondylitis (Yuan et al. 2016), serum of pre-eclampsia patients (Eide et al. 2008), urine of diabetic nephropathy subjects (Li et al. 2017) and breast milk of nursing individuals (Li Volti et al. 2010, Peila et al. 2016). Interestingly, results from the present study show substantially diminished levels of HO-1 within plasma EVs compared to other biofluids tested, with the greatest concentrations of HO-1 protein in CSF and salivary EVs. The striking difference between plasma and serum HO-1 levels suggests possible dilution of HO-1 in plasma by clotting factors (Yu et al. 2011). Salivary and serum HO-1 concentrations were similar, notwithstanding the fact that salivary protein concentrations are approximately 25-fold lower than that typically observed in serum (Al-Muhtaseb 2014). Our findings may guide the selection of appropriate biofluids for HO- 1 protein determinations in various clinical settings.

237 The classical endoplasmic reticulum-Golgi secretory pathway directs proteins containing a signal peptide (leader sequence) from the endoplasmic reticulum to the Golgi complex, from which they subsequently move to the trans-Golgi network and then to the plasma membrane (Kim et al. 2018). Considering that HO-1 is a leaderless protein lacking a signal peptide sequence, one or other non-canonical protein secretory pathways must be at play. Non-classical or unconventional protein secretory pathways include: i) direct translocation of proteins across the plasma membrane via membrane transporters; ii) blebbing; iii) lysosomal secretion; and iv) egress via EVs (Kim et al. 2018). Results of the current study support the latter mechanism as HO- 1 protein was specifically enriched in all EV fractions and minimally detected, if at all, in EVD fractions. The functional significance of HO-1 transport by EVs in peripheral biofluids remains to be elucidated. Depending on the microenvironment and clinical context, HO-1 can exert a protective or detrimental effect (Schipper et al. 2019; Nitti et al. 2018). HO-1 transport by EVs in peripheral biofluids may: i) act as a signaling mechanism to alert the entire organism to tissue- specific damage; the presence of HO-1 protein on the surface of EVs may facilitate this signaling function, ii) contribute to antioxidant protection of nearby tissues, or iii) serve as an attempt to reduce intracellular build-up of HO-1 protein via vesicular packaging and release into extracellular space. Future studies should delineate the functional significance of vesicular HO-1 in health and in various diseased states. In Alzheimer disease and Parkinson disease, HO-1 protein is significantly overexpressed in discrete brain regions heavily impacted by the disease process, namely the hippocampus and substantia nigra, respectively (Schipper et al. 1998). We postulate that neurodegenerative and neuroinflammatory CNS pathologies may be reflected in peripheral tissues via centrifugal EV transport of specific cargo, like HO-1. This conjecture is supported by the fact that GFAP.HMOX1 mice engineered to conditionally overexpress HMOX1 in brain astrocytes display increased levels of circulating HO-1 in serum EVs compared to age-matched wild-type control mice (Cressatti and Schipper, unpublished results). This ability of EVs to cross the blood-brain barrier via transcytosis has been experimentally confirmed in vivo (Alvarez-Erviti et al. 2011, Zhuang et al. 2011, Haney et al. 2015). Akin to GFAP.HMOX1 mice, overexpression of mutant copper-zinc superoxide dismutase (SOD1) in primary astrocyte cultures was associated with increased release of EVs

238 containing mutant SOD1 (Basso et al. 2013). Furthermore, these astrocyte-derived EVs were capable of transferring mutant SOD1 to spinal neurons and induce selective motor neuron death in a mouse model of amyotrophic lateral sclerosis (Basso et al. 2013). Of note, astrocyte-derived EVs may contain 20-fold higher amounts of multiple disease-related proteins than EVs of neuronal origin (Goetzl et al. 2016). We speculate that the uptake mechanism of HO-1, or other salient proteins, by EVs occurs during EV biogenesis within the cell type of origin (e.g. astrocytes, neurons, etc.). These EVs are subsequently released into the extracellular space and enabled to infiltrate nearby cells or cross the blood-brain barrier, reaching peripheral biofluids via the circulation. An alternative, or possibly concomitant, source of neural-derived circulating EVs containing HO-1 is via direct innervation of peripheral tissues that modulate biofluid production and chemical composition. For instance, saliva composition and secretion from parotid, submandibular and sublingual glands are regulated by the sympathetic and parasympathetic nervous systems which may be a source of neural-derived EVs and vesicular HO-1 in this particular biofluid (Tumilasci et al. 2006). Immunoreactive HO-1 has been detected in salivary gland pleomorphic adenomas (Fan et al. 2011), but whether the protein is produced locally in the acinar cells or derives from the gland’s autonomic innervation remains to be determined. The mechanism by which vesicular HO-1 reaches systemic circulation may be biofluid-specific and/or disease-specific and merits focus in future studies. In addition to carrying salient proteins involved in disease processes, EVs can also transport microRNAs (miRNAs) across the blood-brain barrier (Margolis and Sadovsky 2019). Chevillet and colleagues reported that exosomes (typically 30 – 150 nm in diameter) are improbable carriers of miRNAs, seeing as there was considerably less than one stoichiometric molecule of a given miRNA per single exosome (mean ± SD across six exosome sources: 0.00825 ± 0.02 miRNA molecules/exosome) (Chevillet et al. 2014). They conjectured that larger classes of EVs, such as microvesicles (typically 50 – 1000 nm in diameter), are more likely carriers of physiologically relevant numbers of miRNA molecules which may participate in miRNA-based intercellular communication and serve as a source of potential biomarkers (Chevillet et al. 2014). We previously showed in GFAP.HMOX1 mice that miR-153 and miR-223, acting downstream of HO-1, were significantly downregulated in brain compared to age-matched wild-type

239 preparations (Cressatti et al. 2019b). Intriguingly, similar downregulation of miR-153 and, to a lesser extent, miR-223, was observed in the serum of GFAP.HMOX1 mice (Cressatti et al. 2019b) and the saliva of human Parkinson disease subjects (Cressatti et al. 2019a) compared to wild-type and non-neurological controls, respectively. Incorporation of any given component of the cytoplasm or other cellular compartment into an EV is determined by: 1) proximity to the budding membrane and size of the EV (passive loading) and 2) specific association with the membrane and any energy-dependent process (active loading) (Thery et al. 2018). Small EVs (< 200 nm) are less likely to incorporate cargo from cellular organelles, such as mitochondria, Golgi or endoplasmic reticulum, than larger EVs (Thery et al. 2018). Microvesicles, a relatively large subtype of EV, are thus more plausible transporters of endoplasmic reticulum-associated HO-1 protein and miRNAs relative to smaller EVs, such as exosomes (Thery et al. 2018). The data presented herein support this contention, as the average size of EVs isolated from the five human biofluids surveyed falls within the range of microvesicles (approximately 340 nm). Our findings hold promise that analyses of systemic microvesicles originating from the CNS, including L1CAM- derived EVs from neurons and GLAST-derived EVs from astrocytes, may open a new window into normal and pathological brain function and facilitate biomarker discovery for the diagnosis and prognosis of diverse neurological afflictions. There were several limitations to the current study. Sample sizes for plasma, serum, urine and CSF groups were relatively low (n = 10-14), and some key demographic information was missing from subjects donating the latter three biofluids due to anonymity restrictions. Larger- scale diagnostic trials for specific disease states should include complete demographic measures and medical histories on all enrolled subjects. Homogeneous populations of EVs are difficult to obtain given their substantial variability with respect to size, prevalence in specific extracellular compartments and molecular mechanisms responsible for their biogenesis and release (Thery et al. 2018). Many biological and technical factors may affect circulating EVs, including circadian variations, exercise levels, diet, sample collection volume, among many more (Thery et al. 2018), and must be tightly regulated in diagnostic trials. In order to account for the limitations of the polymer precipitation method (high recovery and low specificity), this protocol was combined with an additional immuno-affinity isolation method (low recovery and high specificity) in the

240 current study. Further, a moderate amount of contamination was detected in some of the EVD fractions, particularly in the serum EVD preparation. This may be due to the fact that serum contains significantly greater concentrations of low-molecular weight proteins (e.g. albumin, globulins, fibrinogen) relative to other biofluids tested (Al-Muhtaseb 2014). This will be important to consider in the development of improved EV isolation techniques. L1CAM is highly expressed in neurons, but is also expressed at low levels in other cell types such as cancer cells and lymphocytes (Mustapic et al. 2017, Shi et al. 2014). Similarly, while GLAST is primarily expressed by astrocytes, GLAST expression has also been noted (albeit minimally) in retinal glial cells (Walcott and Provis 2003) and in mitochondria of cardiac myocytes (Ralphe et al. 2004). Lastly, L1CAM-enriched and GLAST-enriched EVs may not only be derived from the CNS but could also be released by neurons and astrocytes within the enteric or autonomic nervous systems. These points will be important to consider for the future identification and development of CNS-specific EV markers. In this study, we ascertained the presence of HO-1 protein in EVs of various human biofluids and adduced evidence that the extracellular HO-1 is transported predominantly via EVs. This observation has important implications for the determination of physiologically-relevant HO- 1 concentrations in human and probably other mammalian biofluids and may inform the design and execution of biomarker studies. HO-1 plays a major role in various disease states, and differential expression profiles of vesicular HO-1 may represent a promising approach to biomarker development. It will be important to determine, for example, whether proteomic (and other ‘omic’) analyses of recovered EV fractions will provide more specific and reproducible biomarker data than similar evaluations performed on whole biofluids as is the standard of practice today. Acknowledgements We thank Dr. Janusz Rak and Laura Montermini for assistance with the NanoSight equipment, and Sienna Drake for assistance with original artwork in the graphical abstract.

241 Funding sources The funding sources of this research include: Canadian Institutes of Health Research (HMS), Parkinson Canada (MG and HMS), Fonds de recherche du Québec – Santé/Parkinson Canada (MC) and Mitacs (AMV). Conflicts of interest HMS and MG have served as officers of HemOx Biotechnologies. HMS has served as consultant to Osta Biotechnologies, Molecular Biometrics Inc., TEVA Neurosciences, and Caprion Pharmaceuticals. MC, JMG, LJ, AMV, SE, AL, RG and HG have no conflicts of interest to declare.

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248 18.7. Chapter 5 Tables and Figures Table 1. EV isolation workflow using Total Exosome Isolation Reagent (Thermo Fisher) specific to each biofluid. Plasma samples were subjected to an additional Proteinase K step prior to the addition of Total Exosome Isolation reagent, based on manufacturer’s instructions. CSF, cerebrospinal fluid; RT, room temperature. Total Starting Total Exosome 1st 2nd Volume Exosome Incubation 3rd Biofluid Isolation Centrifuge Centrifuge (µl) Isolation Period Centrifuge Reagent Reagent Cat. No. 2000 x g, 10,000 x g, Saliva 4484453 N/A 500 0.5 vol 1 h, 4°C 10 min, RT 1 h, 4°C 2000 x g, 10,000 x g, 10,000 x g, Plasma 4484450 500 0.2 vol 30 min, 4°C 20 min, RT 20 min, RT 5 min, RT 2000 x g, 10,000 x g, Serum 4478360 N/A 500 0.2 vol 30 min, 4°C 30 min, RT 10 min, RT 2000 x g, 10,000 x g, Urine 4484452 N/A 500 1 vol 1 h, RT 30 min, 4°C 1 h, 4°C 2000 x g, 10,000 x g, 10,000 x g, CSF 4484453 700 1 vol 1 h, 4°C 30 min, 4°C 30 min, 4°C 1 h, 4°C

249 Table 2. Distribution of covariates across biofluids. CSF, cerebrospinal fluid; GLAST, GLAST- enriched EVs; L1CAM; L1CAM-enriched EVs; LGD, L1CAM-depleted/GLAST-depleted EVs; Q1, lower quartile; Q3, quartile. Saliva Plasma Serum Urine CSF Sample Size (n) 40 14 10 10 11 Age 43.0 54.5 55.0 45.5 38.0 [Median (Q1, Q3)] (29.0,57.5) (50.0,66.5) (37.3,65.0) (35.0,70.3) (29.0,41.0) Female 22 (55.0%) 9 (64.3%) 7 (70.0%) 5 (50.0%) 6 (60.0%) Sex [Count (%)] Male 18 (45.0%) 5 (35.7%) 3 (30.0%) 5 (50.0%) 4 (40.0%) 3.29 11.6 11.9 6.82 27.4 LGD (2.03,4.69) (1.97,20.0) (8.53,13.2) (0.55,16.04) (17.9,63.7)

Relative HO-1 4.40 3.31 9.37 0.01 31.2 [Median (Q1, L1CAM (3.46,5.17) (0.44,5.06) (5.91,11.3) (0.01,0.01) (13.3,37.7) Q3)]

1.39 3.95 10.3 2.40 28.5 GLAST (0.59,2.36) (2.07,4.31) (8.29,11.7) (0.58,5.18) (25.0,48.6)

250 Table 3. Multivariable linear regression models of relative HO-1 for various human biofluids adjusted for age and sex. Relative HO-1 concentration was modeled using type of EV, age and sex as linear covariates. Regression coefficients (β) and 95% confidence intervals (CI) of covariates are presented, along with P values. Regression coefficients (β) for each type of EV represent the change in mean relative HO-1 concentration from the respective LGD EV group, after adjusting for variability in age and sex. CSF, cerebrospinal fluid; GLAST, GLAST-enriched EVs; L1CAM; L1CAM-enriched EVs; LGD, L1CAM-depleted/GLAST-depleted EVs; Ref, reference group.

Saliva Plasma Serum Urine CSF n 40 14 10 10 11 P P P P P β [CI] β [CI] β [CI] β [CI] β [CI] value value value value value 12.5 8.5 20.5 36.0 4.0 Intercept - (1.6, - (3.3, - (-4.3, - (10.6, - (2.4, 5.7) 26.1) 13.6) 45.4) 61.4)

LGD Ref Ref Ref Ref Ref

-0.2 0.7 -8.1 0.002 -2.6 0.1 -14.0 0.06 -12.3 0.3 Type of L1CAM (-1.5, (-12.9, - (-6.2, (-28.9, (-34.3, EVs 1.0) 3.3) 0.9) 0.8) 9.8)

GLAST -2.5 < -2.5 0.001 -1.7 0.3 -7.9 0.3 -1.7 0.9 (-3.7, - 0.001 (-13.1, - (-5.3, (-22.7, (-23.7, 1.2) 3.5) 1.8) 7.0) 20.4) 0.02 0.04 -0.05 -0.06 -0.01 Age (-0.02, 0.4 0.3 (-0.05, 0.4 (-0.4, 0.8 (-0.6, 0.8 (-0.2, 0.2) 0.05) 0.1) 0.3) 0.5)

Female Ref Ref Ref Ref Ref

Sex Male -0.6 0.2 -0.7 0.7 1.4 0.4 -8.0 0.2 5.6 0.6 (-1.7, (-4.8, 3.3) (-1.9, (-21.8, (-15.5, 0.4) 4.6) 5.9) 26.7)

251

252 Figure 1. Size and concentration characterization of LGD EVs across human biofluids by NTA. EVs were isolated by polymer precipitation followed by immuno-affinity purification. Average size of LGD EVs isolated across all biofluids tested (A). NTA analysis and size distribution for LGD EVs isolated from saliva (B, C), plasma (D, E), serum (F, G), urine (H, I) and CSF (J, K). Three recordings of 30 s at 37°C were obtained and processed for NTA analysis. For B, D, F, H, J, concentration (Y-axis) = particles x 109/ml. For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). n = 3-5 per biofluid (biological replicates); n = 3 (technical replicates). n, number of subjects.

253 Figure 2

A B C Saliva 1

75 kDa- 48 kDa- 35 kDa- ←HO-1

63 kDa- ←CD63 100 kDa- ←Alix

48 kDa- ←TSG101 245 kDa- 180 kDa- ←L1CAM E D 63 kDa- ←GLAST

Figure 2. HO-1 in EVs isolated from human saliva. EVs were isolated by polymer precipitation followed by immuno-affinity purification. EV abundance (concentration) was measured by CD63 ELISA across each EV fraction (A). EV distribution between fractions showed moderate contamination of EVs within the EVD fraction (11.5%; B). Further EV characterization was performed by Western blot (C). HO-1 was present in EV fractions, as shown by Western blot (C) and ELISA (standardized to EV abundance; D). Pooled EV fractions (LGD, L1CAM-enriched and GLAST-enriched EVs) show significantly greater levels of HO-1 compared to the EVD fraction, measured by ELISA (E). For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). For D and E, Kruskal-Wallis and Mann-Whitney tests were used to analyze results, respectively, and error bars depict interquartile range (Q1, Q3). n = 40 for ELISA (biological replicates); n = 4-7 for Western blot (biological replicates). *, P < 0.05; ***, P < 0.001; ****, P < 0.0001. EVD, EV-depleted; LGD, L1CAM-depleted/GLAST-depleted; n, number of subjects.

254 Figure 3

A B C Plasma 1

63 kDa- 48 kDa- 35 kDa- ←HO-1 63 kDa- ←CD63 100 kDa- ←Alix

48 kDa- ←TSG101 245 kDa- 180 kDa- ←L1CAM E 63 kDa- D ←GLAST

Figure 3. HO-1 in EVs isolated from human plasma. EVs were isolated by polymer precipitation followed by immuno-affinity purification. EV abundance (concentration) was measured by CD63 ELISA across each EV fraction (A). EV distribution between fractions showed minimal contamination of EVs within the EVD fraction (8.6%; B). Further EV characterization was performed by Western blot (C). HO-1 was present in EV fractions, as shown by Western blot (C) and ELISA (standardized to EV abundance; D). Pooled EV fractions (LGD, L1CAM-enriched and GLAST-enriched EVs) show greater levels of HO-1 compared to the EVD fraction, measured by ELISA (E). For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). For D and E, Kruskal-Wallis and Mann-Whitney tests were used to analyze results, respectively, and error bars depict interquartile range (Q1, Q3). n = 14 for ELISA (biological replicates); n = 4-7 for Western blot (biological replicates). *, P < 0.05; **, P < 0.01. EVD, EV- depleted; LGD, L1CAM-depleted/GLAST-depleted; n, number of subjects.

255 Figure 4

A B C Serum 1

35 kDa- ←HO-1 63 kDa- ←CD63 100 kDa- ←Alix

48 kDa- ←TSG101 245 kDa- 180 kDa- ←L1CAM 63 kDa- ←GLAST E D

Figure 4. HO-1 in EVs isolated from human serum. EVs were isolated by polymer precipitation followed by immuno-affinity purification. EV abundance (concentration) was measured by CD63 ELISA across each EV fraction (A). EV distribution between fractions showed moderate contamination of EVs within the EVD fraction (21.4%; B). Further EV characterization was performed by Western blot (C). HO-1 was present in EV fractions, as shown by Western blot (C) and ELISA (standardized to EV abundance; D). Pooled EV fractions (LGD, L1CAM-enriched and GLAST-enriched EVs) show significantly greater levels of HO-1 compared to the EVD fraction, measured by ELISA (E). For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). For D and E, Kruskal-Wallis and Mann-Whitney tests were used to analyze results, respectively, and error bars depict interquartile range (Q1, Q3). n = 10 for ELISA (biological replicates); n = 4-7 for Western blot (biological replicates). *, P < 0.05; **, P < 0.01; ****, P < 0.0001. EVD, EV-depleted; LGD, L1CAM-depleted/GLAST-depleted; n, number of subjects.

256 Figure 5

A B C Urine 1

75 kDa-

48 kDa- 35 kDa- ←HO-1

63 kDa- ←CD63 100 kDa- ←Alix

E 48 kDa- ←TSG101 D 245 kDa- 180 kDa- ←L1CAM 63 kDa- ←GLAST

Figure 5. HO-1 in EVs isolated from human urine. EVs were isolated by polymer precipitation followed by immuno-affinity purification. EV abundance (concentration) was measured by CD63 ELISA across each EV fraction (A). EV distribution between fractions showed minimal contamination of EVs within the EVD fraction (5.5%; B). Further EV characterization was performed by Western blot (C). HO-1 was present in EV fractions, as shown by Western blot (C) and ELISA (standardized to EV abundance; D). Pooled EV fractions (LGD, L1CAM-enriched and GLAST-enriched EVs) show significantly greater levels of HO-1 compared to the EVD fraction, measured by ELISA (E). For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). For D and E, Kruskal-Wallis and Mann-Whitney tests were used to analyze results, respectively, and error bars depict interquartile range (Q1, Q3). n = 10 for ELISA (biological replicates); n = 4-7 for Western blot (biological replicates). *, P < 0.05. EVD, EV- depleted; LGD, L1CAM-depleted/GLAST-depleted; n, number of subjects.

257 Figure 6

A B C CSF 1

75 kDa-

48 kDa- 35 kDa- ←HO-1

63 kDa- ←CD63 100 kDa- ←Alix

48 kDa- ←TSG101 E 245 kDa- D 180 kDa- ←L1CAM 63 kDa- ←GLAST

Figure 6. HO-1 in EVs isolated from human CSF. EVs were isolated by polymer precipitation followed by immuno-affinity purification. EV abundance (concentration) was measured by CD63 ELISA across each EV fraction (A). EV distribution between fractions showed no contamination of EVs within the EVD fraction (B). Further EV characterization was performed by Western blot (C). HO-1 was present in EV fractions, as shown by Western blot (C) and ELISA (standardized to EV abundance; D). Pooled EV fractions (LGD, L1CAM-enriched and GLAST-enriched EVs) show significantly greater levels of HO-1 compared to the EVD fraction, measured by ELISA (E). For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). For D and E, Kruskal-Wallis and Mann-Whitney tests were used to analyze results, respectively, and error bars depict interquartile range (Q1, Q3). n = 11 for ELISA (biological replicates); n = 4-7 for Western blot (biological replicates). ****, P < 0.0001. EVD, EV-depleted; LGD, L1CAM- depleted/GLAST-depleted; n, number of subjects.

258 Figure 7

Figure 7. Comparison of HO-1 levels in pooled EVs isolated from human biofluids. EVs were isolated by polymer precipitation followed by immuno-affinity purification. HO-1 concentrations (ng/ml) were measured by sandwich ELISA across each EV fraction. HO-1 levels from LGD, L1CAM- enriched and GLAST-enriched fractions were pooled together. Kruskal-Wallis was used to analyze results and error bars depict interquartile range (Q1, Q3). n = 40 (saliva), 14 (plasma), 10 (serum), 10 (urine) and 11 (CSF) (biological replicates). **, P < 0.01; ****, P < 0.0001. CSF, cerebrospinal fluid; n, number of subjects.

259

260 Supplementary Figure 1. Size and concentration characterization of L1CAM-enriched EVs across human biofluids by NTA. EVs were isolated by polymer precipitation followed by immuno-affinity purification. Average size of L1CAM-enriched EVs isolated across all biofluids tested (A). NTA analysis and size distribution for L1CAM-enriched EVs isolated from saliva (B, C), plasma (D, E), serum (F, G), urine (H, I) and CSF (J, K). Three recordings of 30 s at 37°C were obtained and processed for NTA analysis. For B, D, F, H, J, concentration (Y-axis) = particles x 109/ml. For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). n = 3-5 per biofluid (biological replicates); n = 3 (technical replicates). n, number of subjects.

261

262 Supplementary Figure 2. Size and concentration characterization of GLAST-enriched EVs across human biofluids by NTA. EVs were isolated by polymer precipitation followed by immuno-affinity purification. Average size of GLAST-enriched EVs isolated across all biofluids tested (A). NTA analysis and size distribution for GLAST-enriched EVs isolated from saliva (B, C), plasma (D, E), serum (F, G), urine (H, I) and CSF (J, K). Three recordings of 30 s at 37°C were obtained and processed for NTA analysis. For B, D, F, H, J, concentration (Y-axis) = particles x 109/ml. For A, ANOVA was used to analyze results and error bars depict standard error of the mean (SEM). n = 3-5 per biofluid (biological replicates); n = 3 (technical replicates). n, number of subjects.

263 19. Discussion Results from parkinsonian GFAP.HMOX18.5-19m mice and humans with Parkinson disease (PD) show that heme oxygenase-1 (HO-1) may be acting as a critical transducer contributing to the pathogenesis of PD. At 19 months of age, GFAP.HMOX18.5-19m mice recapitulate key features of the disease relative to age-matched wild-type (WT) controls as evidenced by the following: (i) impaired locomotion (rotarod), circling behaviour, motor incoordination (pole test), altered ambulation (gait test) and reduced olfaction (buried pellet test); (ii) dopaminergic neuron degeneration in the substantia nigra, with substantial vacuolation manifesting in the remaining neurons, and decreased dopamine levels in the striatum; (iii) upregulated pituitary homeobox 3 (Pitx3)- and dopamine transporter (DAT)-targeting microRNA (miRNA)-133b and nuclear receptor related-1 protein (Nurr1)-targeting miR-145 in nigrostriatum; (iv) significant elevation of gamma amino butyric acid (GABA) in the substantia nigra; (v) increased iron deposition, and improved rotarod performance after treatment with the iron chelator, deferiprone; (vi) augmented α- synuclein, serine 129 phosphorylated α-synuclein and ubiquitin both within and surrounding the dopaminergic neurons of the substantia nigra, as well as increased α-synuclein in erythrocytes; (vii) downregulation of α-synuclein-targeting miR-153 and miR-223 in brain nigrostriatum and periphery (serum); (viii) enhanced protein carbonylation, a marker of oxidative stress, in the striatum; (ix) dysregulated autophagy and accumulation of striatal osmiophilic inclusions, indices of autophagosome formation and mitophagy; and (x) reduced and disorganized mitochondrial cristae and fragmented mitochondrial membranes within the striatum (Cressatti et al. 2019b, Song et al. 2017a, Tavitian et al. 2019). Notably, this phenotype was not observed in mice expressing the HMOX1 transgene for an identical duration between 1.5 and 12 months of age (Song et al. 2017a), underscoring the importance of brain aging for symptom manifestation in both human and experimental parkinsonism. Furthermore, primary astrocyte and neuron cultures from GFAP.HMOX18.5-19m mice display upregulation of messenger RNAs (mRNAs) involved in oxidative stress (manganese superoxide dismutase [MnSOD]), mitophagy (parkin, phosphatase and tensin homolog [PTEN]-induced kinase 1 [PINK1]), mitochondrial fission (dynamin-related protein 1 [Drp1]) and apoptosis (p53, B-cell lymphoma 2 [Bcl2], Bcl-2- associated X protein [BAX], Bcl-2 homologous antagonist killer [BAK]) and downregulation of

264 mRNAs involved in dopaminergic neuron development and maintenance (Nurr1, Pitx3), dopamine metabolism (tyrosine hydroxylase [TH], DAT), neuroprotection (Daisuko-Junko-1 [DJ- 1]) and mitochondrial fusion (mitofusion 1 [Mfn1], Mfn2) compared to WT control preparations (Cressatti et al. 2019b). Many, though not all, of these parkinsonian hallmarks were abrogated by small interfering RNA (siRNA) against Snca (Cressatti et al. 2019b). Akin to GFAP.HMOX18.5-19m mice, miR153 and miR-223 levels were significantly lower in the saliva of PD patients compared to non-neurological (healthy) controls (Cressatti et al. 2019a). One possible mechanism of action for CNS changes being reflected in peripheral biofluids is the transfer of specific cargo across the blood-brain barrier (BBB) via extracellular vesicles (EVs). In fact, HO-1 protein, acting upstream of miR-153 and miR-223, was predominantly found in central nervous system (CNS)-derived and non-CNS-derived EV fractions across five different human biofluids, including saliva, plasma, serum, urine and cerebrospinal fluid (CSF) (Cressatti and Schipper, accepted for publication). This dissertation offers several candidates, including HO-1, miR-153/miR-223 and/or α-synuclein, as potential novel therapeutic or diagnostic avenues for future PD research. 19.1. HMOX1 Transducer Model We do not believe HO-1 to be the cause of idiopathic PD but rather a transducer that funnels accumulating environmental and genetic risk factors into relevant pathophysiology (Fig. 2). Numerous stressors linked to PD, including dopamine, 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP)-like xenobiotics, interleukin-1b (IL-1b), tumor necrosis factor-α (TNF- α), hydrogen peroxide and heavy metals, to name a few, may contribute to the specific and sustained upregulation of HMOX1 in astrocytes. As recapitulated in GFAP.HMOX18.5-19m mice, environmental and genetic risk factors likely combine over the course of normal aging, resulting in repeated or continuous induction of HMOX1 and culminating (around mid-life) in prolonged release and accumulation of the heme degradation products, ferrous iron and carbon monoxide (CO). Outweighing the antioxidative effects of biliverdin/bilirubin, overproduction of ferrous iron and CO in astrocytes results in increased oxidative stress, mitochondrial iron trapping, macroautophagy, pro-toxin bioactivation, diminished ATP production and decreased glutathione (GSH) levels (Schipper et al. 2019). Treatment of HMOX1-transfected or primary GFAP.HMOX1 astrocytes with iron chelators or a CO antagonist abrogates many of the previously mentioned

265 consequences of HO-1 overexpression (Lin et al. 2015, Song et al. 2009, Song et al. 2006). Evidence from in vitro co-cultures and GFAP.HMOX1 mice teaches that excessive and continued glial stress plays a major role in observed levels of enhanced excitotoxicity, oxidative stress, α- synuclein production and comprise degeneration of nearby dopaminergic neurons (Cressatti et al. 2019b, Song et al. 2017a, Song et al. 2006, Song et al. 2012a, Zukor et al. 2009). Adding further predictive validity to our model, inhibition of HO-1 activity in vitro or in vivo rescues the phenotype (Gupta et al. 2014, Zukor et al. 2009).

Dopaminergic Neurons miRNA mimic Astrocytes ↓miR-153 Aging Oxidative ↑CO Stress ↓miR-223 Genetic ↑HO-1 ↑Fe2+ Propagation Environmental (↑Biliverdin/Bilirubin) ↑⍺-Synuclein

↓miR-153 HO-1 inhibitor (e.g. OB-28) ↓miR-223 Aggregation

↑HO-1 ↑HO-1 ↓miR-153 ↓miR-223 ↑⍺-Syn Neurodegeneration CNS ↓miR-153 ↓miR-223 Equilibrium Periphery ↓miR-153 ↓miR-223 ↑HO-1 Serum Erythrocytes ↑⍺-Syn

↓miR-153 ↑HO-1 ↑⍺-Synuclein ↓miR-223 Bone = EV marrow

Salivary Gland Saliva

↓miR-153 ↓miR-153 ? ↓miR-223 ↓miR-223

Figure 2. Transducer model for role of HO-1 in PD. Red text denotes potential therapeutic strategies. Shapes with dotted borders represent speculative hypotheses. See text for more details. CNS, central nervous system; CO, carbon monoxide; EV, extracellular vesicle; Fe2+, ferrous iron; HO-1, heme oxygenase-1; miRNA, microRNA; α-Syn, α-synuclein. In contrast to existing toxin and genetic animal models of PD described earlier (see Section 8.2.11), the GFAP.HMOX18.5-19m mouse model of PD unveils a third category of animal model, namely the transducer model. GFAP.HMOX1 mice recapitulate key features of the human disorder, as humans with PD similarly display: (i) motor incoordination, shuffling gait and anosmia (Goetz et al. 2008, Kalia and Lang 2015, Postuma et al. 2015); (ii) dopaminergic neuron

266 degeneration and decreased dopamine levels in basal ganglia (Ehringer and Hornykiewicz 1960, Greffard et al. 2006, Hirsch et al. 1988); (iii) enhanced basal ganglia GABA production (Alexander 2004, Emir et al. 2012, Oz et al. 2006); (iv) pronounced iron deposition (Ward et al. 2014); (v) augmented α-synuclein, serine 129 phosphorylated α-synuclein and ubiquitin mRNA and protein (Anderson et al. 2006, Baba et al. 1998, Braak et al. 2003, Spillantini et al. 1997), typically associated with Lewy pathology, as well as increased α-synuclein in erythrocytes (Matsumoto et al. 2017, Nakai et al. 2007, Vicente Miranda et al. 2017); (vi) enhanced oxidative stress (Blesa et al. 2015); (vii) reduced GSH levels (Jenner et al. 1992, Sian et al. 1994); (viii) dysregulated autophagy and mitophagy (Alvarez-Erviti et al. 2010, Anglade et al. 1997, Chu et al. 2009, Dehay et al. 2010); (ix) mitochondrial damage and dysfunction (Hauser and Hastings 2013, Winklhofer and Haass 2010); (x) diminished ATP production (Chan et al. 1991, Davey and Clark 1996, Perier and Vila 2012); (xi) imbalance in mitochondrial fission and fusion (increased fission and decreased fusion) (Venderova and Park 2012); and (xii) enhanced cell death pathways, including apoptosis and potentially ferroptosis (Anglade et al. 1997, Guiney et al. 2017, Mogi et al. 2000). Particularly relevant here, GFAP.HMOX18.5-19m mice replicate augmented levels of astroglial HO- 1 protein observed in the human PD nigrostriatum (Schipper et al. 1998). Taken together, observations from GFAP.HMOX18.5-19m mice support the notion that core pathological features common to neurodegeneration, such as non-regulated brain iron trapping, oxidative stress, mitochondrial damage and macroautophagy, represent a single lesion devolving from the sustained induction of HMOX1 within astrocytes. This formulation strengthens the conceptual link between normal brain aging, often characterized by a milder version of this core pathology, and the major senescence-associated neurodegenerative disorders, like PD (Schipper et al. 2019). For instance, when present in abundance, certain pathological features are considered characteristic of PD. This includes gliosis, increased α-synuclein protein, brain iron deposition and mitochondrial insufficiency (Kalia and Lang 2015). However, when present at low densities, these are instead considered features of normal brain aging (Chu and Kordower 2007, Harada et al. 2013). Recognition that this core cytopathology drives the neurodegenerative process may shift the design of disease-modifying therapeutics towards disruption of molecular pathways which act to integrate the constituents of this multifaceted lesion (Schipper et al.

267 2019). This highlights the astroglial HO-1 transducer as a potential therapeutic target to simultaneously mitigate several core pathological features of the disease. 19.2. Why Astrocytes? Our glia-centric focus on HO-1 expression is pivotal to our laboratory’s longstanding and original perspective on mechanisms of neurodegeneration in the aging and parkinsonian brain. This approach is based on the following considerations: 1) The excess iron reported in the aging and PD brain largely implicates glial and other non-neuronal cells (Schipper and Song 2015). 2) HO-1 is significantly upregulated in astrocytes, not neurons, of the PD substantia nigra relative to normal age-matched control values (Schipper et al. 1998). Astrocytes and microglia have a greater propensity to mount a strong HO-1 (as well as other stress protein) responses compared to neurons and oligodendrocytes (Dwyer et al. 1995, Manganaro et al. 1995, Snyder et al. 1998). 3) Hmox1 induction by stressors implicated in PD (e.g. hydrogen peroxide, heavy metals, TNF-α, etc.) is a common pathway leading to mitochondrial iron deposition, oxidative mitochondrial damage and macroautophagy in aging subcortical astroglia (Schipper et al. 1998, Schipper 2004a, Schipper and Song 2015, Schipper et al. 2009b). 4) The ability of astrocytes to effectively revert to anaerobic metabolism for their energy needs, also known as the Warburg effect, may permit astroglia (but not neurons) to sacrifice a considerable fraction of their mitochondria with minimal consequence (Schipper et al. 1999). 5) Finally, the progressive accumulation of glial mitochondrial iron within subcortical brain regions enhances the vulnerability of nearby dopaminergic neurons to oxidative injury and may thereby render the senescent CNS more prone to PD (Schipper 2001a, Schipper 2004a). Results from GFAP.HMOX18.5-19m mice show robust behavioural abnormalities, neurodegenerative changes and aberrant neurotransmitter and gene expression profiles, illustrating unequivocally that profound neuronal dysfunction may closely follow primary insults to the astrocytic compartment. This is further supported by the fact that astrocytes are essential for normal synaptic transmission and neuronal plasticity (Haydon and Carmignoto 2006) and a driver of neurological degeneration in PD (Krobert et al. 1997). Targeted suppression of HO-1 within the astroglial compartment may disrupt the consolidation of core neuropathology common to PD, thereby slowing disease progression. The following sections aim to link astroglial

268 HO-1 directly to key parkinsonian pathomechanisms, as evidenced by the studies described herein looking at GFAP.HMOX18.5-19m mice and human PD. 19.3. The Dopaminergic System Akin to human PD, midbrain dopaminergic neurons in 19-month old GFAP.HMOX18.5-19m mice are particularly vulnerable to degeneration. Typically, in order to observe clinical phenotypes in parkinsonian animal models (e.g. toxin or genetic), roughly 50% of the dopaminergic neurons in the substantia nigra of the brain should be destroyed (Le et al. 2014). Fittingly, GFAP.HMOX18.5- 19m mice display a 47% reduction in the number of TH-positive (dopaminergic) neurons in the substantia nigra compared to age-matched WT control mice (Song et al. 2017a). Furthermore, many remaining dopaminergic neurons display large cytoplasmic vacuoles, potential cytopathological indices of increased autophagy, problems in fusion of autophagosomes with lysosomes and/or disrupted elimination of unwanted cellular components (Venderova and Park 2012). This nigral dopaminergic degeneration likely accounts for locomotor behaviour abnormalities observed in GFAP.HMOX18.5-19m mice, including motor incoordination, diminished hind base width and length and greater scuffled footprints (Song et al. 2017a, Tavitian et al. 2019). The circling behaviour observed in GFAP.HMOX18.5-19m mice may further reflect hemispheric asymmetries in dopaminergic tone within the substantia nigra and striatum (Song et al. 2017a), similar to stereotypy seen in rodents following unilateral injection of 6-OHDA (Hamadjida et al. 2019). Hemispheric differences in dopamine depletion were not assessed in the present study and should be included in future experiments involving GFAP.HMOX18.5-19m mice. Further, while greater numbers of dopaminergic neurons within the olfactory bulb may account for olfactory deficits (hyposmia) observed in GFAP.HMOX18.5-19m mice (Ennis et al. 2001, Huisman et al. 2004, Pifl et al. 2017, Tavitian et al. 2019), this was not assayed herein and should be explored in future experiments. Basal ganglia dopaminergic neurons are uniquely susceptible to degeneration due to the pro-oxidant actions of dopamine and the production of dopamine quinones and hydrogen peroxide in this brain region, which participate in neurotoxic reactions that promote oxidative stress (Bisaglia et al. 2010, Segura-Aguilar et al. 2014). Iron accrued from sustained HO-1-mediated heme catabolism likely participates in Fenton chemistry alongside reactive oxygenase species (ROS) produced within GFAP.HMOX18.5-19m and PD basal ganglia,

269 further contributing to dopaminergic neurodegeneration. While TH and DAT protein levels were significantly decreased in neurons co-cultured with GFAP.HMOX1 astrocytes relative to neurons co-cultured with WT astrocytes, no differences were observed in TH and DAT protein levels between GFAP.HMOX1-derived and WT neurons grown in the absence of GFAP.HMOX1 astrocytes (Song et al. 2017a). This underscores the dependence of the nigrostriatal dopaminergic deficit on ongoing exposure to the HO-1 overexpressing astroglia. Reduction of Nurr1 and Pitx3, transcription factors involved in the growth and maintenance of dopaminergic neurons, in GFAP.HMOX18.5-19m midbrain astrocytes and neurons may also promote dopaminergic deficits in our model (Song et al. 2017a). In addition to dopamine depletion, levels of crucial antioxidant and trophic factors are reduced in PD substantia nigra, including GSH (Jenner et al. 1992, Sian et al. 1994). Likewise, GFAP.HMOX1 mice display diminished GSH levels associated with oxidative protein modifications (Song et al. 2017b). Treatment of GFAP.HMOX1 mice with a whey protein isolate acting as a GSH precursor, called Immunocal®, not only restored GSH homeostasis in the CNS of transgenic (TG) mice, but also attenuated many redox abnormalities observed in GFAP.HMOX1 mice compared to age-matched WT controls (Song et al. 2017b). 19.4. Other Neurotransmitter Systems GFAP.HMOX18.5-19m mice recapitulate some, though not all, of the other salient neurotransmitter system alterations documented in human PD. Calcium-related excitotoxicity contributes to neurodegeneration in the PD substantia nigra, and calcium buffering is partly controlled by the inhibitory neurotransmitter, GABA (Allaman et al. 2011, Maiti et al. 2017). In human PD and experimental parkinsonism, GABAergic projections from the basal ganglia output nuclei are reported to be tonically overactive and show variable amounts of abnormal oscillatory activity (Alexander 2004, Emir et al. 2012, Gwiazda et al. 2002, Kish et al. 1986, Ondo and Hunter 2003, Oz et al. 2006). Similarly, GFAP.HMOX18.5-19m mice at 19 months of age show significantly elevated levels of GABA in the substantia nigra compared to age-matched WT controls (Song et al. 2017a). While other neurotransmitter systems have been linked to human PD pathology (see Section 8.2.10i), no significant differences in these neurotransmitter levels were observed between WT and GFAP.HMOX18.5-19m mice (Song et al. 2017a).

270 19.5. Iron Falling in line with prolonged HO-1 overexpression models, increased iron deposition was observed in the striatum of 19-month old GFAP.HMOX18.5-19m mice compared to age-matched WT controls (Song et al. 2017a). The Schipper laboratory previously showed that Hmox1 induction significantly enhances the incorporation of radio-labeled iron into astroglial mitochondria (Mehindate et al. 2001, Schipper et al. 1999). This mitochondrial iron sequestration was suppressed following treatment with either tin mesoporphyrin, a competitive inhibitor of HO activity, or dexamethasone, a transcriptional inhibitor of Hmox1, suggesting mitochondrial iron trapping is dependent on preceding induction of Hmox1 (Mehindate et al. 2001, Schipper et al. 1999). As per previously described HMOX1-transfected astrocytes grown in vitro (Zukor et al. 2009), brain iron sequestration in GFAP.HMOX1 mice is not associated with overt changes in iron regulatory proteins 1/2 (IRP1/2), transferrin receptor, ferroportin or ferritin protein concentrations (Song et al. 2012b), and therefore may be considered unregulated (transferrin- independent). Furthermore, treatment with the iron chelator, deferiprone, improved rotarod performance in GFAP.HMOX18.5-19m mice compared to WT and vehicle-treated TG groups (Song et al. 2017a). The improved locomotor behaviour observed in these mice after iron chelation therapy directly implicates this heme degradation product in midbrain dopaminergic neuron toxicity. Likewise, in the aging degenerating CNS, a significant proportion of pathologically- deposited, redox-active iron is HO-1-dependent. HO-1 has even been linked to accelerated ferroptosis, a mechanism of cell death, and iron-dependent lipid peroxidation during ferroptosis (Chang et al. 2018, Kwon et al. 2015), suggesting a potential role for iron in dopaminergic neuron cell death as seen in PD. With respect to the latter in our model, observations of iron deposition, depleted GSH, lipid peroxidation and morphological changes in mitochondria suggest ferroptosis may be at play (Song et al. 2017a, Song et al. 2006, Song et al. 2012a, Vaya et al. 2007). Though iron chelation therapy with deferiprone in humans has shown promise (Boddaert et al. 2007, Kessler et al. 2018, Poli et al. 2017), there remains a theoretical risk of secondary (‘bystander’) injury to other tissues in the course of brain iron mobilization. An enzymatic (e.g. HO-1) and glial-specific contribution to oxidative mitochondrial attrition (via iron and other factors) in diseased neural tissues may prove more amenable to pharmacological manipulation

271 than free radical damage resulting from rogue chemical processes, and could be considered as an alternative, or possibly adjunct, to iron chelation therapy (Schipper et al. 2019). 19.6. α-Synuclein α-Synuclein has long been considered a major player in PD pathology (see Section 8.2.10iii). In GFAP.HMOX18.5-19m mice, α-synuclein and pathological serine 129 phosphorylated α-synuclein were significantly increased within and surrounding the dopaminergic neurons of the substantia nigra compared to age-matched WT controls (Cressatti et al. 2019b, Song et al. 2017a). Significant elevations in ubiquitin, ubiquitin binding protein p62 (p62) and HO-1, previously associated with Lewy body inclusions albeit to a lesser extent than α-synuclein (Gai et al. 2000, Mahul-Mellier et al. 2020, Schipper et al. 1998), were also observed in our TG mice, though no overt Lewy pathology was noted (Song et al. 2017a). The lack of Lewy body inclusions observed in 19-month old GFAP.HMOX18.5-19m mice, a common criticism of parkinsonian animal models (see Section 8.2.11), may be rationalized as follows: (i) GFAP.HMOX18.5-19m mice may represent an early-stage model of PD, considering other early-stage features of parkinsonism in this model, such as reduced olfaction and only 47% loss of nigral dopaminergic neurons (Song et al. 2017a, Tavitian et al. 2019); whether GFAP.HMOX18.5-19m mice would display Lewy body inclusions later in life (e.g. at 24 months of age) remains to be determined; or (ii) HMOX1 overexpression may not be sufficient to elicit Lewy body inclusion formation. To address the latter, crossing GFAP.HMOX1 mice with an α-synuclein overexpressing model may propel Lewy body inclusion formation. Enhanced α-synuclein production and aggregation has been linked to increased levels of iron (see Section 8.2.10iii), and induction of HMOX1 results in greater α-synuclein protein in vitro (Cressatti et al. 2019b). Further supporting the link between HO-1 and α-synuclein, HMOX1 overexpression from embryogenesis until 12 months of age, as seen in the GFAP.HMOX10-12m mouse model of schizophrenia, similarly resulted in significant elevation of α-synuclein mRNA and protein (Song et al. 2012a). Targeting α-synuclein is an important therapeutic consideration for PD, highlighted by the fact that siRNA inhibition of the gene encoding this protein, Snca, in primary GFAP.HMOX1 astrocytes attenuated oxidative stress to levels observed in negative control and WT preparations (Cressatti et al. 2019b). Moreover, when co-culturing these primary GFAP.HMOX1

272 astrocytes with WT neurons, followed by treatment with siRNA against Snca, WT neurons displayed normalization of mRNAs involved in oxidative stress (MnSOD), dopaminergic neuron development and maintenance (Nurr1, Pitx3), dopamine metabolism (TH, DAT), mitophagy (DJ- 1), mitochondrial fission (Drp1) and mitochondrial fusion (Mfn2, Mfn1) (Cressatti et al. 2019b). This underscores the importance of α-synuclein suppression in mitigating key pathomechanisms of PD, possibly in combination with upstream HO-1 inhibition. Potentially viable targets of α- synuclein mitigation include miRNAs, miR-153 and miR-223, which were found to negatively regulate α-synuclein mRNA and protein (Cressatti et al. 2019b). 19.7. MicroRNAs MiRNAs have gained immense traction as key regulators in development, normal aging and disease, including PD (Basak et al. 2016, Lukiw 2007, Martinez 2017). In 2015, we published a study looking at miRNA profiles in HMOX1-transfected primary rat astrocytes compared to sham- transfected controls, and identified three significantly upregulated miRNAs (miR-140*, miR-17 and miR-16) and six significantly downregulated miRNAs (miR-297, miR-206, miR-187, miR-181a, miR-138 and miR-29c) (Lin et al. 2015). Moreover, the effects of HO-1 induction on glial miRNA profiles were abrogated by a competitive HO inhibitor (tin mesoporphyrin), an iron chelator (deferoxamine) and a CO antagonist (methylene blue), directly implicating HO-1, iron and CO, respectively, in the aberrant miRNA expression profiles (Lin et al. 2015). On the other hand, the addition of bilirubin, the final product of heme catabolism, had little effect on these miRNA levels in cultured astrocytes (Lin et al. 2015). Furthermore, these salient miRNA profiles were recapitulated in WT cells treated with the iron donor, Fe(NO3)3 (Lin et al. 2015). Taken together, these results lend support to the canonical nature of HO-1 activity in our system and its role in alterations of relevant miRNAs. Akin to miRNA changes in HMOX1-transfected primary rat astrocytes, GFAP.HMOX18.5-19m mice and primary GFAP.HMOX1 astrocyte-neuron co-cultures display altered miRNA expression profiles. Notably, Pitx3- and DAT-targeting miR-133b and Nurr1-targeting miR-145 in nigrostriatum were significantly upregulated compared to WT preparations, commensurate with downregulation of PitX3, DAT and Nurr1 (Cressatti et al. 2019b, Song et al. 2017a). Fitting with apparent upregulation of α-synuclein observed in GFAP.HMOX18.5-19m mouse brains, α-synuclein-

273 targeting miR-153 and miR-223 were significantly downregulated in TG substantia nigra and striatum compared to WT controls (Cressatti et al. 2019b). Conserved binding sites for miR-153 and miR-223 were predicted to lie within the 3’-untranslated region (UTR) of SNCA with partial complementarity (TargetScan software), and miR-153 was confirmed to bind the 3’-UTR of SNCA and suppress a-synuclein mRNA and protein (Doxakis 2010, Fragkouli and Doxakis 2014, Je and Kim 2017). This partial complementarity suggests regulation at the level of both SNCA mRNA via targeted mRNA degradation and a-synuclein protein via translation repression, a notion that is supported by our mimic and inhibitor experiments (Cressatti et al. 2019b). In the above- mentioned HMOX1-transfected primary rat astrocytes, miR-153 expression trended downwards while miR-223 showed no significant change, though these results were not further validated by RT-qPCR (Lin et al. 2015). Other targets of miR-153 include b-amyloid and nuclear factor erythroid 2-related factor 2 (Nrf2). Similar to a-synuclein deposition in the PD brain, suppression of miR- 153 has been correlated with high levels of amyloid precursor protein and b-amyloid in the AD brain (Liang et al. 2007, Long et al. 2012). Additionally, inhibition of miR-153 promotes the expression of Nrf2 and HO-1 (Ji et al. 2017), and this miRNA has been reported to be dysregulated in the APPswe/PS1ΔE9 mouse model of Alzheimer disease (AD) (Liang et al. 2012) as well as the MPTP mouse model of PD (Zhu et al. 2018). Other targets of miR-223 include NF-kB and IL-1b. Intriguingly, circulating levels of miR-153 and miR-223 were similarly lower in the GFAP.HMOX18.5-19m mice compared to age-matched WT controls (Cressatti et al. 2019b), commensurate with systemic alterations in a-synuclein gene and protein expression profiles in GFAP.HMOX18.5-19m mouse erythrocytes as well as idiopathic human PD (Cressatti et al. 2019b, Gao et al. 2015, Matsumoto et al. 2017, Song et al. 2017a, Vivacqua et al. 2019). The peripheral changes in miR-153 and miR-223 levels in GFAP.HMOX18.5-19m mice are what led to the study of these key miRNAs in human PD saliva as potential biomarkers of the disease. 19.8. Biomarkers Diagnosis of PD remains a challenge, with a 20% misdiagnosis rate overall and a 47-74% misdiagnosis rate among early stage (H&Y stage 1) PD patients, on average (Adler et al. 2014, Rizzo et al. 2016). This results in delayed administration of appropriate medication regimens, which may lead to symptom mismanagement and decreased quality of life (Massano and Bhatia

274 2012). However, with the future development of neuroprotective therapeutic strategies that stop or slow the destruction of neurons in PD brain, misdiagnosis will waste precious time, making research in this field imperative. Presently, neuroimaging modalities (e.g. magnetic resonance imaging [MRI], positron emission tomography [PET], single-photon emission computer tomography [SPECT], transcranial sonography) offer some utility in the clinical diagnosis and staging of idiopathic PD (Emamzadeh and Surguchov 2018), though these techniques remain expensive and labour-intensive. An easily quantifiable and widely accessible clinical biomarker would be a welcomed advance in the field of PD research. In 2018, we published a study reporting increased concentrations of salivary HO- 1 in early stage (Hoehn and Yahr [H&Y] stage 1) PD patients compared to non-neurological (healthy) controls (Song W. et al. 2018). This corroborated previous findings of elevated HO-1 levels in serum of PD patients (Mateo et al. 2010). Saliva offers advantages over other biofluids as its acquisition is non-invasive, inexpensive and requires minimal training of personnel (Roi et al. 2019, Wang et al. 2015b). The 2018 study on salivary HO-1 served as a template for the investigation of miR-153 and miR-223, acting downstream of HO-1 and targeting a-synuclein, in PD saliva (Cressatti et al. 2019a). We observed that expression levels of miR-153 and miR-223 were significantly reduced in PD saliva relative to non-neurological controls, and these expression patterns were unaffected by age, sex, various comorbidities, disease duration or medication exposure (Cressatti et al. 2019a). The area under the receiver operating characteristic (ROC) curve separating controls from PD patients was 79% (confidence interval: 64-99%) for miR-153 and 74% (confidence interval: 60-93%) for miR-223 (Cressatti et al. 2019a), suggesting moderately good markers of PD. Another miRNA that has been linked to a-synuclein regulation, miR-7 (Doxakis 2010, Junn et al. 2009), was also assayed in saliva, though we did not observe significant alterations in miR-7a or miR-7b in PD patients relative to controls (Cressatti et al. 2019a). Additionally, measurement of the ratios of key proteins acting upstream (HO-1) or downstream (oligomeric or total a-synuclein) of miR-153 or miR-223 to these miRNA expression levels did not improve the accuracy of the test as a PD neurodiagnostic relative to ascertainment of miR-153 or miR-223 alone (Cressatti et al. 2019a). Alterations in salivary miRNAs described

275 herein are consistent with our earlier findings in brain and serum of parkinsonian GFAP.HMOX18.5-19m mice (Cressatti et al. 2019b). MiR-153, miR-223 and SNCA expression levels in human brain are highest in midbrain, an important region at the epicentre of PD pathophysiology (Doxakis 2010, Farh et al. 2005, Tagliafierro et al. 2017). They have also been detected in extracellular compartments, including blood (Matsumoto et al. 2017, Vallelunga et al. 2014, Vicente Miranda et al. 2017), CSF (Gao et al. 2015, Gui et al. 2015) and saliva (Patel et al. 2011, Vivacqua et al. 2016, Vivacqua et al. 2019), with their levels fluctuating in response to disease state. Several groups in addition to our own have linked miR-153 and, to a lesser extent, miR-223 to PD pathology (Cressatti et al. 2019b, Doxakis 2010, Je and Kim 2017, Vallelunga et al. 2014). Alterations in miR-153 levels have been documented in PD CSF (Gui et al. 2015) and plasma (Zhang et al. 2017), while changes in miR-223 have been reported in PD serum (Vallelunga et al. 2014). Ours is the first study to document aberrant expression levels of miR-153 and miR-223 in the saliva of PD patients to our knowledge. However, considering other CNS conditions similarly involve differential expression of miR-153 and miR-223, it is critical to assay these miRNA levels in PD patients relative to neurological controls (e.g. other neurodegenerative conditions, other forms of parkinsonism, other synucleinopathies). Currently underway is the study of HO-1 concentrations as well as miR-153 and miR-223 expression levels in PD saliva compared to neurological controls (Galindez, Velly and Schipper, unpublished results). 19.9. Extracellular Vesicles The above described findings in parkinsonian GFAP.HMOX18.5-19m mouse brain and PD saliva raise the question as to how CNS changes are reflected in the periphery. It remains to be determined whether these changes occur as one or more of the following: (i) separate yet concurrent primary insults to CNS and peripheral systems; (ii) a primary insult initiated in the peripheral system and progressing to the CNS via retrograde transmission; or (iii) a primary insult initiated in the CNS and progressing to the peripheral system via anterograde transmission. The Braak staging hypothesis (see Section 8.2.10iii) provides evidence in support of the second option, with a- synuclein pathology emerging in the enteric nervous system and eventually progressing up the brainstem towards the midbrain and beyond (Braak et al. 2003, Braak et al. 2004). Though

276 evidence from our model does not refute any of the above-mentioned possibilities, it does lend support to the third option. TG GFAP.HMOX18.5-19m mice were engineered to conditionally overexpress HMOX1 in astrocytes between 8.5 and 19 months of age, which results in behavioural, pathological and biochemical alterations reminiscent of PD (Cressatti et al. 2019b, Song et al. 2017a, Tavitian et al. 2019). This glial HO-1 overexpression (beginning at 8.5 months of age) is the primary insult that evokes a decrease in circulating miR-153 and, to a lesser extent, miR-223 levels by 11 months of age and continues to progress at least until 19 months of age (Cressatti et al. 2019b). The mechanism by which CNS miRNA and protein alterations are reflected in peripheral biofluids, as supported by our model, may involve EVs (see Section 8.4). EVs are generally divided into two predominant types based on size and origin, namely exosomes and microvesicles (Thery et al. 2018, van Niel et al. 2018). Due to the highly heterogeneous nature of exosomes and microvesicles and the difficulty in isolating a pure population of one type over the other, we broadly refer to these structures as EVs. These membrane-bound particles are released by all cells and can travel across endothelial cells of the BBB via receptor-mediated endocytosis, releasing their contents into extracellular fluids (Alvarez-Erviti et al. 2011, Porro et al. 2019). Considering HMOX1 does not contain an amino-terminus signal peptide destining HO-1 to the secretory pathway, the fact that this protein has been detected in numerous circulating biofluids (by our group and others [Anthony et al. 2003, Eide et al. 2008, Kishimoto et al. 2018a, Kishimoto et al. 2018b, Li et al. 2017, Mateo et al. 2010, Song et al. 2018, Yuan et al. 2016]) is curious. Non-classical or unconventional protein secretion pathways include: i) direct translocation of proteins across the plasma membrane via membrane transporters; ii) blebbing; iii) lysosomal secretion; and iv) release via EVs (Kim et al. 2018). Regarding our model, evidence adduced in Chapter 5 (see Section 18) supports the latter pathway. In GFAP.HMOX1 mice, HO-1 protein is significantly increased in serum EVs compared to WT control mice (data not shown). In humans, HO-1 has been minimally studied with respect to EVs. El-Rifaie and colleagues reported increased HO-1 mRNA in exosomes isolated from peripheral blood mononuclear cells of psoriasis subjects (El-Rifaie et al. 2018), though the finding of HO-1 in EVs was not the main focus of their study. With respect to cell-to-cell communication, one report showed that EVs derived from

277 human lung mesenchymal stem cells under inflammatory conditions have enhanced NF-kB and HO-1 mRNA expression in an in vitro human model of cystic fibrosis (Zulueta et al. 2018). Finally, HO-1 protein has also been detected in numerous mass spectrometry analyses of EVs derived from various human cancer cell types (summarized in Vesiclepedia; see [Kalra et al. 2012]), in addition to human urine exosomes (Wang et al. 2012). To the best of our knowledge, the research described herein is the first study to identify HO-1 protein as predominantly being carried within EVs across human biofluids. The 32 kDa HO-1 protein band was present in EVs isolated from five different human biofluids, namely saliva, plasma, serum, urine and CSF; and HO-1 levels were significantly higher in pooled EV fractions relative to EV-depleted (EVD) fractions. We further analyzed subpopulations of EVs, specifically L1 cell adhesion molecule protein (L1CAM)-enriched EVs derived from neurons and glutamate aspartate transporter 1 (GLAST)-enriched EVs derived from astrocytes of the brain. Similarly, HO-1 protein was apparent by enzyme-linked immunosorbent assay (ELISA) in CNS-derived EVs alike, with the exception of L1CAM-enriched EVs from urine. That no HO-1 protein was detected by ELISA in urinary L1CAM-enriched EVs, though the 32 kDa band was observed in the same sample by the denaturing conditions of Western blotting (Forsstrom et al. 2015, Jansen et al. 2009), implies that HO-1 is present solely within the lipid bilayer membrane of these specific EVs. Curiously, L1CAM-enrinched EVs from urine were the only EVs to exhibit this phenomenon, suggesting EVs from the other biofluids tested carry HO-1 both inside and outside the lipid bilayer. Overall, results from the study herein suggest that the majority of extracellular HO-1 is being transported by EVs of human biofluids. In addition to carrying salient proteins, EVs also transport miRNAs across the BBB (Margolis and Sadovsky 2019). In 2014, Chevillet and colleagues reported that exosomes (30 – 150 nm in diameter) are improbable carriers of miRNAs, seeing as there was far less than one stoichiometric molecule of a given miRNA per exosome (mean ± standard deviation across six exosome sources: 0.00825 ± 0.02 miRNA molecules/exosome) (Chevillet et al. 2014). They surmised that larger classes of EVs, such as microvesicles (50 – 1000 nm in diameter), may represent more likely carriers of physiologically significant numbers of miRNA molecules, functioning as an alternative vehicle for miRNA-based intercellular communication and a source

278 of biomarkers (Chevillet et al. 2014). Similarly, due to the cellular localization of HO-1, the larger size of microvesicles makes them more likely carriers of this endoplasmic reticulum protein over exosomes (Thery et al. 2018). The data presented in Chapter 5 (see Section 18) support these hypotheses, as the average size of EVs analyzed falls within the size range of microvesicles (approximately 340 nm). Based on evidence accrued from GFAP.HMOX18.5-19m mice and human biofluids, we hypothesize that CNS changes in key protein (e.g. HO-1, a-synuclein) and miRNAs (e.g. miR-153, miR-223) are being reflected in the periphery via centrifugal EV transport. The peripheral changes observed across systems may be a result of equilibrium maintenance by the BBB. This has important therapeutic and diagnostic implications for PD research. For instance, systemic exosomal siRNA delivery in TG mice expressing the human phosphorylation-mimic S129D a- synuclein (which exhibit aggregation pathology) significantly reduced levels of a-synuclein mRNA and protein as well as intracellular protein aggregates within dopaminergic neurons of the substantia nigra relative to WT controls (Cooper et al. 2014). While the therapeutic potential of EVs has not been fully elucidated in humans, their use holds promise for the treatment of different disorders of the CNS, when many drugs are of limited use due to their inability to penetrate the BBB (Galieva et al. 2019). The ability of EVs to cross the BBB via transcytosis has been experimentally confirmed (Alvarez-Erviti et al. 2011, Haney et al. 2015, Zhuang et al. 2011). Furthermore, EVs have been extensively studied in recent years as a potential source of biomarkers for PD, particularly neural-derived EVs which offer a ‘window’ into the CNS (see Section 8.4.1). We are currently using nano-flow liquid-chromatography mass spectrometry to analyse differences, if any, between salivary EV and whole saliva proteomic profiles (Cressatti and Schipper, unpublished results). This line of inquiry should reveal whether EVs portray a more precise snapshot of PD pathophysiology than whole biofluids. 19.10. The Dopamine Paradox The data presented thus far implicate sustained or repeated upregulation of astroglial HMOX1 during mid-to-late life as a driver of core neurological and peripheral pathologies common to neurodegenerative disorders, like PD. This gliopathy renders nearby dopaminergic neuronal constituents prone to oxidative injury and cell death (Frankel and Schipper 1999, Song et al.

279 2007). Similar evidence accrued from schizophrenia-like GFAP.HMOX10-12m, in which astroglial HMOX1 is upregulated earlier, during embryogenesis until 12 months of age (see Section 8.5.2ii), may shed light on what we have referred to as the ‘great dopamine paradox.’ While human neurodevelopmental and neurodegenerative disorders differ with respect to risk factors, demographics, neurological and behavioural symptoms, neuroimaging, cytopathology and neurochemistry, overlap still exists (Schipper et al. 2019). Observations in both schizophrenia- like GFAP.HMOX10-12m and parkinsonian GFAP.HMOX18.5-19m mice raise the intriguing possibility that identical sets of stressors and convergent downstream mechanisms elicit either early-onset developmental (e.g. schizophrenia) or later-life degenerative (e.g. PD) brain disorders, depending on whether the glial HO-1 response is evoked prior to or following the maturation of dopaminergic and other salient neural circuitry (Schipper et al. 2019). This is particularly relevant considering that following treatment with neuroleptic (anti- dopaminergic) agents, patients with schizophrenia (a hyperdopaminergic state) frequently experience parkinsonian (a hypodopaminergic state) features. However, parkinsonian signs (e.g. rigidity, bradykinesia, tremor) have also been curiously reported in a significant proportion of young, drug-naïve schizophrenics at first psychotic episode (Caligiuri et al. 1993). Similarly, PD patients receiving levodopa (L-dopa) replacement experience psychosis, yet spontaneous hallucinations arising in non-medicated persons with idiopathic PD and dementia with Lewy bodies have also been reported (Ffytche et al. 2017, Snow and Arnold 1996). In a recent publication, a genome-wide association analysis of PD and schizophrenia revealed shared genetic architecture and nine genomic loci jointly associated with both disorders (Smeland et al. 2020). These clinical observations suggest that, within a given individual, the mesolimbic/mesocortical dopaminergic circuitry governing psychosis and the nigrostriatal dopaminergic pathway subserving locomotion may be differentially impacted by disease (e.g. schizophrenia or PD) to either augment or curtail dopaminergic transmission in a region-specific manner (Schipper et al. 2019). Region-specific disparities in the susceptibility of dopaminergic circuitry to the trophic and degenerative influences of glial HMOX1 induction may account for the mixed schizophrenia and PD traits within affected individuals. In this fashion, the leucine-rich repeat kinase 2 (LRRK2) G2019S knock-in mouse model of familial PD exhibit spontaneous conversion from early-life

280 hyperdopaminergia with excessive behaviour to late-life hypodopaminergia and reduced exploratory behaviour (Sossi et al. 2010, Volta et al. 2017). Of particular interest here, co-incident schizophrenia and early-onset parkinsonism are observed in subjects with the 22q11.2 deletion syndrome (Butcher et al. 2013), as discussed in Section 8.3.1. Intriguingly, and perhaps coincidentally, HMOX1 is located on chromosome 22q12 (Dennery 2000) in close proximity to the genetic lesion of the aforementioned 22q11.2 deletion syndrome. Whether or the extent to which HMOX1 is impacted by the chromosomal anomaly in individuals with this syndrome remains to be determined. Overall, the convergent mechanisms underpinning the emergence of hyper- and hypodopaminergic phenotypes in GFAP.HMOX1 mice highlight the importance of suppression of glial HO-1 activity at strategic junctures in the life cycle in order to prevent or arrest the progression of dopamine-dependent neuropsychiatric and neurodegenerative conditions (Schipper et al. 2019). 19.11. Protective Effects of HO-1 Despite the dystrophic effects of HO-1 described above, abundant evidence has confirmed that products of the HO-1 reaction, mainly CO and biliverdin/bilirubin, may confer cytoprotection in brain and other tissues by direct antioxidant action or by signaling survival pathways (Calabrese et al. 2010a, Calabrese et al. 2010b, Le et al. 1999). This includes mitigation of oxidative stress, regulation of apoptosis, modulation of inflammation and promotion of angiogenesis (Loboda et al. 2016). In fact, two known cases of human HO-1 deficiency resulted in a severe pro- inflammatory phenotype, intracranial hemorrhaging and early childhood death (Radhakrishnan et al. 2011, Yachie et al. 1999). Likewise, HO-1 knock-out mice display evidence of chronic inflammation and increased intrauterine or juvenile death (Koizumi 2007). Furthermore, HO-1 protein may behave non-canonically as a transcription factor capable of modulating survival gene induction upon nuclear translocation, though only under certain circumstances (Lin et al. 2007). Overexpression of canonically-active HO-1 protein in GFAP.HMOX1 mice, under acute settings, elicits robust neuroprotection, as observed during acute intracerebral hemorrhage (see Section 8.5.2iii) (Chen-Roetling et al. 2017, Chen-Roetling et al. 2015). As such, the behaviour of HO-1 in the setting of acute neurological illness (e.g. stroke or trauma) is more often than not trophic in nature (Schipper et al. 2019). The participation of HO-1 in chronic states (e.g. PD), on the other

281 hand, is predominantly maladaptive due to the accumulation of redox-active iron (Schipper et al. 2019). The contrast between neuroprotective and neurodystrophic effects of HO-1 highlight the Janus-faced nature of this stress protein. Chronicity, redox microenvironment and tissue-type seem to be key in dictating the outcome of HO-1 overexpression. In mammalian CNS aging, HO- 1 may acquire a toxic gain-of-function, evident by the fact that its activation under conditions of acute stress may confer health benefits whereas its long-term engagement is deleterious. As discussed in Section 8.5.1, GT-repeat length polymorphisms within the HMOX1 promoter and several identified single nucleotide polymorphisms (see Section 8.5.3) may modulate the ‘gain’ on cellular stressor transduction and thereby influence disease expression. In addition to HO-1, additional endogenous antioxidative mechanisms exist to alleviate the production of ROS and RNS in brain, namely superoxide dismutase, catalase, GSH peroxidase, ascorbic acid, uric acid and vitamin E, among others (Lalkovicova and Danielisova 2016). The neuropathological signature of the PD brain is likely a result of the dysregulation of many of these endogenous antioxidant systems combined with increased levels of ROS, dopamine oxidation and tissue iron (Sutachan et al. 2012). 19.12. Contributions to Original Knowledge Altogether, the data presented herein contribute original knowledge to the field of PD research. One major contribution is the characterization of the novel GFAP.HMOX18.5-19m mouse model of PD. This model recapitulates numerous behavioural, neuropathological and biochemical features of the disease (see Section 19.1), a feat that has proven difficult in many of the existing experimental models of parkinsonism. We recently donated the GFAP.HMOX1 mouse line to the Jackson Laboratory (Bar Harbor, Maine), thereby making it widely available to the neuroscience community at large. In 2014, Jankovic and colleagues surmised that future animal models of PD should aim to mimic the genetic-environmental pathogenesis, presumed to cause the progressive neurodegeneration associated with this disorder (Le et al. 2014). The GFAP.HMOX18.5-19m mouse provides new insight into the link between environmental and genetic factors via induction of HO-1. The accumulation of exposures to environmental and epigenetic risk factors with advancing age may explain why onset of idiopathic PD occurs later in life. We hypothesize that

282 HO-1 acts as a transducer between exogenous and endogenous stimuli, and chronic overexpression of this stress protein culminates in a self-reinforcing loop of neurodegenerative and parkinsonian hallmarks. This identifies HO-1 as a potential disease-modifying target in the treatment of PD. Though metalloporphyrin inhibitors of HO activity have demonstrated clinical utility in the management of neonatal jaundice (hyperbilirubinemia) and several adult hepatopathies, secondary effects including skin photosensitization (blistering) and anemia may complicate their long-term use. Furthermore, metalloporphyrins competitively block both HO-1 and HO-2 activity with similar efficacy and have difficulty passing the BBB. In order to circumvent many of the problems inhering to the metalloporphyrins, Walter Szarek and colleagues at Queens University developed a compound called OB-28. This non-peptidic, imidazole-based molecule has excellent BBB permeability and selectively inhibits HO-1 (rather than HO-2) with minimal toxicity (Alaoui- Jamali et al. 2009, Kinobe et al. 2006, Schipper et al. 2009a). As evidenced earlier (see Section 8.5.2v), daily intraperitoneal treatment of a mouse model of AD with OB-28 significantly inhibited HO-1 activity in brain, ameliorated cognitive deficits and reduced indices of oxidative stress (Gupta et al. 2014). Delivery systems of siRNA targeted for HO-1 knock-down specifically in astrocytes (Syapin 2008) may also warrant consideration in light of earlier successes with this approach in neurons (Kumar et al. 2007) and hepatocytes (Rozema et al. 2007). In order to validate the use of HO-1 inhibitors as a treatment strategy, currently underway are experiments observing the effects of astroglial Hmox1 knock-out on MPTP- and rotenone-induced parkinsonism in mice (Smart, Pantopoulos and Schipper, unpublished results). Acting downstream of HO-1, miR-153 and miR-223 were identified as negative regulators of a-synuclein and moderately good diagnostic biomarkers of idiopathic PD (Cressatti et al. 2019a, Cressatti et al. 2019b). The presence of these miRNA alterations in saliva is particularly relevant, considering saliva acquisition is a minimally invasive and highly accessible protocol for the elderly PD population. Furthermore, peripheral changes in miR-153 and miR-223 were similarly observed in GFAP.HMOX18.5-19m mouse and human PD brain, and EVs may offer a suitable mechanism of action to explain this phenomenon. It is important to note that this is not only relevant to miR-153 and miR-223, but also to other key players involved in PD

283 neuropathology, including native and oligomeric a-synuclein, DJ-1, tau, other salient miRNAs and HO-1 (see Section 8.4.1). Understanding how peripheral pathologies reflect CNS afflictions may accelerate our knowledge relating to CNS physiology in health and disease. Finally, we described the novel finding of HO-1 protein being predominantly transported by EVs in various circulating human biofluids. This is not only important for the HO-1 research community, but also for the biomarker community at large. Peripheral EVs may offer a unique ‘window’ into various CNS conditions, including PD. In order to continue to advance the research presented as part of the current PhD dissertation, it is vital to first address limitations inherent to our line of investigation. 19.13. Limitations of the Study The limitations of the studies described herein include the following: 1) Reproducibility of the GFAP.HMOX18.5-19m mouse model of PD remains to be demonstrated in another laboratory outside our own institute. The donation of GFAP.HMOX1 mice to the Jackson Laboratories helps to make this parkinsonian model more widely available for the PD research community at large. 2) The novel scoring system described in Chapter 2 (see Section 12) for the pole test, though performed in blinded fashion by two different testers, has not yet been validated in another model of experimental parkinsonism. 3) Hemispheric differences in dopaminergic neuron counts and dopamine levels were not assayed, and should be included in future studies involving GFAP.HMOX18.5-19m mice. This will help reconcile stereotypic circling behaviour observed in GFAP.HMOX18.5-19m mice, a trait typically associated with unilateral 6-hydroxydopamine (6- OHDA) lesion models (Hamadjida et al. 2019). 4) The diagnostic study evaluating miR-153 and miR-223 expression levels in the saliva of PD patients was a single-site trial in this initial phase, and should be conducted across multiple centres and countries in order to further validate the results. 5) Additionally, this diagnostic trial compared PD patients to non-neurological controls. While comparison against non-neurological controls is a necessary step, assessing salivary miRNA levels in PD patients against neurological controls is of utmost importance to ascertain specificity, considering the overlap between PD and other neurodegenerative disorders, parkinsonisms and synucleinopathies. 6) Finally, the field of EV research is relatively new, and several limitations arise with regard to isolation and characterization of specific EV populations. In 2018, the

284 International Society for EVs released an updated list of minimal information for studies of EVs (MISEV2018) (Thery et al. 2018). We followed these guidelines in utilizing at least two isolation techniques, namely a high recovery/low specificity method (e.g. precipitation/polymer kits) followed by a low recovery/high specificity method (e.g. immuno-affinity isolation). However, as the field continues to grow and technology advances, these techniques are continuously evolving. Our laboratory continues to adapt our EV isolation protocol to obtain the highest standards of EV purity. Furthermore, while we used several techniques to characterize separated EVs (e.g. nanoparticle tracking analysis [NTA], ELISA, Western blot) in line with MISEV2018 guidelines, contamination by unwanted particles is difficult to discern and this remains a challenge across all studies of EVs. 19.14. Future Directions The research described herein built upon existing data conducted previously by graduate students and staff members of our laboratory and should continue to propel future studies exploring the role(s) of HO-1 in the pathogenesis of PD. As mentioned throughout, several research projects stemming from this work are already underway: 1) The effects of astroglial Hmox1 knock-out on rotenone-induced parkinsonism in mice are being evaluated in order to further validate the use of HO-1 inhibitors as a disease-modifying strategy (Smart, Pantopoulos and Schipper, unpublished results). 2) Assessment of HO-1 concentrations as well as miR-153 and miR-223 expression levels in PD saliva compared to neurological controls to determine the specificity of the neurodiagnostic for idiopathic PD (Galindez, Velly and Schipper, unpublished results). 3) Analysis of differences, if any, between salivary EVs and whole saliva proteomic profiles using nano-flow liquid-chromatography mass spectrometry (Cressatti and Schipper, unpublished results). Additional future directions the research described herein could take include the analysis of the following: (i) dopaminergic neuron tone in the olfactory bulb, potentially accounting for olfactory deficits observed in GFAP.HMOX18.5-19m mice (Tavitian et al. 2019); (ii) whether the parkinsonian phenotype is exacerbated or new signs appears (e.g. cognative dysfunction, a- synuclein-containing inclusions, dysautonomia, etc.) if GFAP.HMOX18.5-19m mice are aged until 24 rather than 19 months of age; (iii) whether the model exhibits reversibility should

285 GFAP.HMOX18.5-19m mice be placed back on the doxycycline diet (ceasing HMOX1 overexpression) after 19 months of age; (iv) whether the parkinsonian phenotype in GFAP.HMOX18.5-19m mice is rescued with the treatment of L-dopa, adding further predictive validity to our model; (v) finally, crossing GFAP.HMOX1 mice with mutant a-synuclein TG mice may help delineate whether Lewy body pathology is accelerated by astroglial HMOX1 overexpression in double-mutant offspring. While many additional experiments can be proposed, the above-mentioned future directions are what we believe to be the most relevant for implicating HO-1 in the pathogenesis of idiopathic PD. 19.15. Overall Impact The advent of conditional GFAP.HMOX1 TG mice endows the biomedical community with a robust resource to investigate the roles of glial stress and HO-1 in brain aging, PD and other neurological afflictions. Our establishment and extensive characterization of the GFAP.HMOX18.5- 19m mouse enabled us to unify several seemingly disparate pathological features of PD, viz. oxidative stress, iron mobilization, mitochondrial insufficiency and macroautophagy (mitophagy), into a single lesion arising from the action of HO-1 within astrocytes. Although we do not regard aberrant HO-1 expression as a cause of PD, we view glial HO-1 hyperactivity as a pivotal transducer that funnels an array of noxious stimuli through limited neurodegenerative pathways culminating in nigrostriatal injury. The current tier of experiments in GFAP.HMOX18.5-19m mice forges an unprecedented, mechanistic link between glial HMOX1 induction and many cardinal features of PD pathogenesis. In humans, expression levels of miR-153 and miR-223, acting downstream of HO-1 and negatively regulating a-synuclein, were decreased two-fold in PD saliva compared to non-neurological controls, supporting these salient miRNAs as potentially useful biomarkers of the disease. That CNS changes are being reflected in peripheral biofluids, such as saliva, raises the possibility that EVs shuttle pathologically-relevant proteins and nucleic acids across the BBB, a phenomenon with important implications for PD and other neurological conditions. Most importantly, contemporary pharmacotherapy for PD is almost exclusively symptomatic in nature and effective neuroprotection would be a welcome development. Several metalloporphyrin inhibitors of HO activity are already in clinical use for the control of neonatal hyperbilirubinemia (jaundice) and certain adult liver conditions and, if secondary (‘bystander’)

286 effects are successfully mitigated, could be adapted for the treatment of PD. The small-molecule inhibitor, OB-28, may confer additional advantages for human use in light of its selectivity for HO- 1 over HO-2, BBB permeability and favourable toxicity profile (Gupta et al. 2014). After many years of exploring the fundamentals of glial HO-1 behaviour in CNS senescence and disease, we may be at the cusp of translating this experience into development of definitive, disease- modifying approaches to the management of PD and related neurodegenerative disorders - an unmet clinical need that heavily impacts the health and wellbeing of our aging Canadian population.

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