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Prevalence and Phenotypic Characterization of Rare Genetic Disorders Within Psychiatric Populations

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Prevalence and Phenotypic Characterization of Rare Genetic Disorders within Psychiatric Populations by Venuja Sriretnakumar A thesis submitted in conformity with the requirements for the degree of Doctorate of Philosophy Graduate Department of Laboratory Medicine and Pathobiology University of Toronto © Copyright by Venuja Sriretnakumar 2021 Prevalence and Phenotypic Characterization of Rare Genetic Disorders within Psychiatric Populations Venuja Sriretnakumar Doctorate of Philosophy Laboratory Medicine and Pathobiology University of Toronto 2021 Abstract Many rare genetic syndromes are known to phenotypically manifest with psychiatric symptoms that can be indistinguishable from primary psychiatric disorders. While the majority of ongoing research in psychiatric genetics has been dedicated to the identification and characterization of genes involved in primary psychiatric disorders, there has been a lack of research to determine the extent to which rare genetic variants contribute to the overall psychiatric disease load. This thesis aims to investigate the prevalence of clinically well-characterized pathogenic copy number variant (CNV) syndromes and treatable genetic disorders that can present with neuropsychiatric symptoms within the general psychiatric patient population. In our first study, a greater than expected number of syndromic CNVs was observed amongst a cohort of 348 schizophrenia patients. In our second, pilot, study of 2 046 psychiatric patients, an enrichment for variants associated with four treatable inborn errors of metabolism were found in comparison to the control population. In the third, expansion, study ii screening for 108 treatable genetic disorders, there was also an enrichment found for the screened genetic disorders in a general psychiatric patient population relative to the expected disease prevalence in the general population. Moreover, an increased carrier frequency for screened genetic disorders was also seen amongst psychiatric patients. Taken together, discovering genetic diseases in psychiatric patients will shift how health care is delivered to these vulnerable patients by addressing underlying conditions rather than masking symptoms with medications and will especially help patients who don't respond to regular medications. This will lead to significant cost savings to the health care system. Ultimately, this study will pave the way for the development of a genetic testing strategy screening psychiatric patients for genetic diseases and identification of specific characteristics associated with psychiatric symptomatology in treatable genetic diseases that will allow for earlier targeted screening and treatments. iii Acknowledgments First and foremost I would like to thank both my supervisors, Drs. Joyce So and James L. Kennedy for their support, and mentorship through my graduate career. Thank you Joyce for your continual supervision (even from across international borders), for the unwavering effort to secure funding through countless grants and scholarship applications, for the occasional push to write (without which I would not be here today), and for all the laughs and conversations interlaced with the perfect amount of cynicism. Thank you Jim for the unique and unforgettable student experience you provided through your funding to attend numerous domestic and international conferences, all the travels from which have broaden my perspectives and further nourished my appetite for new discoveries and experiences; and thank you for the many, many interesting stories told and shared. Thank you to my supervisory committee, Drs. John B. Vincent, Jordan Lerner-Ellis, and Clement Zai for their support and aid in shaping this thesis into a robust study that is presented here today. Thank you to my colleagues and now good friends Amanda Lisoway, Sejal Patel, Ricardo Harripaul, Victoria Marshe, Julia Tomasi, Cheng Chen, Keith Misquitta, Eric Huang, and Nuwan Hettige for all the unforgettable memories made, ‘feel-good-Friday’ talks, and all the laughs in between. I would also like to thank Anna Mikhailov, Syed Wasim, Natalie Freeman, Maria Tampakeras, Sajid Shaikh, Kayla Vleuten, Sheraz Cheema, and Ayeshah Mohiuddin for their technical and/or administrative assistance in and out of the lab. Last but not least, a great big thanks goes to my parents, family, and friends, without whom I would not be where I am today, nor achieved as much as I did. Thank you to my brother for the occasional chauffeur services; thank you to my aunt for all the delicious meals and treats; and thank you Amma and Dada for your never-ending love, support, and encouragement to pursue my dreams; and most importantly for putting up with my wild mood swings and tantrums through your unlimited patience! Finally, I would like to iv thank my then boyfriend, and now husband, Dusha, for his constant encouragement and support through all the ups and downs of grad life and life as a whole, without whom I would have lost my sanity long ago. One question I’ve been asked the most frequent thus far in my life by family, friends, close relatives, and strangers alike was: “when do you finish school?” and to that I say: “NOW!”. v Table of Contents Abstract ……………………………………………………………………………………………………..… ii Acknowledgements ……………………………………………..………………………………………. iv Table of Contents …………………………………………………………………………………..…….. vi List of Tables ………………………………………………………………………………………..………. xiii List of Figures …………………………………………………………………………………………….… xvi List of Abbreviations ……………………………………………………………………………………. xviii Chapter 1 – Introduction ………………………………………………………………………….….. 1 1.1 Psychiatric Illnesses …………………………………………………………………………..……. 2 1.1.1 Schizophrenia Spectrum Disorders .………………………………………..……. 2 1.1.2 Bipolar Disorder ………………………………………………………………………..…… 3 1.1.3 Major Depressive Disorder ……………………………………………..…………….. 4 1.1.4 Obsessive-Compulsive Disorder ………………………………………………..….. 6 1.1.5. Generalized Anxiety Disorder ……………………………………………………..… 7 1.2 Psychiatry Nosology and Diagnostics ………………………………………….………… 8 1.2.1 Phenotypic Classification …………………………………………………….….…….. 8 1.2.2 Genetic Classification ………………………………………………………………..…… 9 1.2.3 Psychiatric Spectrum ……………………………………………………..………………. 12 vi 1.3 Psychiatric and Neurodevelopmental Disorders ……………………………………. 16 1.3.1 Neurodevelopmental Continuum ………………………………………….……… 16 1.3.2 Pleiotropy ……………………………………………………………………………………… 17 1.4 Psychiatry and Genetic Diseases …………………………………………………………….. 18 1.4.1 Copy Number Variants and Psychiatric Illnesses ……………..……………. 19 1.4.1.1 22q11.2 Deletion Syndrome ....…………………………..…..…………….. 20 1.4.1.2 1q21.1 Deletion Syndrome ………………………….………………………. 22 1.4.1.3 3 2p16.3 NRXN1 Deletion …………………………………………..………… 23 1.4.1.4 15q13.3 Deletion Syndrome …………………………………………..……. 23 1.4.1.5 16p11.2 Deletion and Duplication Syndromes …………………….. 24 1.4.2 Inborn Errors of Metabolism and Psychiatric Illnesses …………..……… 26 1.4.2.1 Lysosomal Storage Disorders ………………………………………………. 26 1.4.2.2 Metal Metabolism Disorders ………………………………..….…………… 28 1.4.2.3 Urea Cycle Disorders ………………………………………………..………….. 30 1.4.2.4 Amino Acid Disorders ………………………………………………….………. 31 1.4.2.5 Porphyrias ……………………………………………………………………..……… 32 1.4.3 Other Treatable Genetic Disorders and Psychiatry ………….……………. 33 1.4.4 Implications of CNV Syndromes and Treatable Genetic Disorders in Psychiatric Patients …………………………………..……………….………………. 34 vii 1.5 Thesis Overview ……………………………………………………………………………………… 37 1.5.1 Rationale ………………………………………………………………………………..……… 37 1.5.2 Hypothesis ………………………………………………………………………………..…… 37 1.5.3 Objective 1 …………………………………………………………………………………….. 38 1.5.4 Objective 2 …………………………………………………………………………………….. 38 1.5.5 Objective 3 …………………………………………………………………………………….. 38 1.5.6 Implications …………………………………………………………………………………… 39 Chapter 2 – Copy number variant syndromes are frequent in schizophrenia: progressing towards a CNV-schizophrenia model ………………………………………. 40 2.1 Summary …………………………………………………………………………………………..……. 41 2.2 Introduction ………………………………………………………………………………………..….. 41 2.3 Materials and Methods …………………………………………………………………………… 42 2.3.1 Samples …………………………………………………………………….…………..………. 42 2.3.2 CNV Detection…..…………………………………………………………..………...……. 43 2.3.3 Phenotyping ……………..………………………………………………………………..…. 43 2.3.4 CNV Calling ………..……………………………………………………………………..….. 43 2.3.5 Cluster Analyses ……………………………………….…………………………….…….. 44 2.3.6. CNV Gene Analyses ……………………………………………………..………….…… 44 2.3.7 Characterization of Syndromic and Candidate Brain CNVs …..………. 44 viii 2.3.8 Statistical Analyses ………………………………………………………………….……. 45 2.4 Results ………………………………………………………………………………………………..….. 45 2.4.1 CNV Calling ………..………………………………………………………………….….….. 45 2.4.2 Cluster Analyses ……………………………………………………………..…………….. 45 2.4.3 CNV Gene Analyses ……………………………………………………………………… 45 2.4.4 CNV Characterization …………………………………………………………………… 46 2.4.5 Statistical Analyses ………………………………………………………………..……… 48 2.5 Discussion ………………………………………………………………………………………..…….. 54 2.6 Conflict of Interest …………………………………………………………………………………. 63 2.7 Contributors ……….…………………………………………………………………………..……… 64 2.8 Funding ………………………..……………………………………………………………..…………. 64 2.9 Acknowledgements ………………………………………………………………….……………. 64 2.10 Supplementary Materials ………………………………………………………..……………. 64 2.10.1 Supplementary Tables ………………………………………………..…………….. 64 2.10.2 Supplementary Figures ……………………………………………..………………. 75 Chapter 3 – Enrichment of pathogenic variants in genes associated with inborn errors of metabolism in psychiatric populations …….……….………………. 78 3.1 Summary …………………………………………………………………………………………………
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  • Recurrent Inversion Toggling and Great Ape Genome Evolution

    Recurrent Inversion Toggling and Great Ape Genome Evolution

    HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Nat Genet Manuscript Author . Author manuscript; Manuscript Author available in PMC 2020 December 15. Published in final edited form as: Nat Genet. 2020 August ; 52(8): 849–858. doi:10.1038/s41588-020-0646-x. Recurrent inversion toggling and great ape genome evolution David Porubsky1,2,9, Ashley D. Sanders3,9, Wolfram Höps3, PingHsun Hsieh1, Arvis Sulovari1, Ruiyang Li1, Ludovica Mercuri4, Melanie Sorensen1, Shwetha C. Murali1,5, David Gordon1,5, Stuart Cantsilieris1,6, Alex A. Pollen7, Mario Ventura4, Francesca Antonacci4, Tobias Marschall8, Jan O. Korbel3, Evan E. Eichler1,5,* 1Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA. 2Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, Saarbrücken, Germany. 3European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany. 4Dipartimento di Biologia, Università degli Studi di Bari “Aldo Moro”, Bari, Italy. 5Howard Hughes Medical Institute, University of Washington, Seattle, Washington, USA. 6Centre for Eye Research Australia, Department of Surgery (Ophthalmology), University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia. 7Department of Neurology, University of California, San Francisco (UCSF), San Francisco, California, USA. 8Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Germany. 9These authors contributed equally to this work. Abstract Inversions play an important role in disease and evolution but are difficult to characterize because their breakpoints map to large repeats. We increased by six-fold the number (n = 1,069) of previously reported great ape inversions using Strand-seq and long-read sequencing. We find that the X chromosome is most enriched (2.5-fold) for inversions based on its size and duplication content.