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Exome Sequencing Reanalysis on a Manitoba Cohort

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Exome Sequencing Reanalysis on a Manitoba Cohort Harnessing the Power of Old Data: Exome Sequencing Reanalysis on a Manitoba Cohort by Taryn Bryn Tristan Athey A Thesis submitted to the Faculty of Graduate Studies of The University of Manitoba in partial fulfilment of the requirements of the degree of MASTER OF SCIENCE Department of Biochemistry and Medical Genetics Genetic Counselling Program Max Rady College of Medicine Rady Faculty of Health Sciences University of Manitoba Winnipeg, Manitoba, Canada Copyright ©2020 by Taryn Athey ABSTRACT Rare disorders are thought to affect 1 in 12 Canadians, yet more than 50% of these patients currently do not have a diagnosis. Undiagnosed and misdiagnosed patients with rare disorders cause a significant burden to the healthcare system and the uncertainty often greatly affects their quality of life. Exome sequencing (ES) is an unbiased genetic testing method that sequences most of the known coding regions in the genome. ES is used when targeted methods have failed to provide a diagnosis and has been found to lead to a definitive diagnosis in 25-50% of cases, depending on the criteria used for case selection. Clinical ES is limited by the bioinformatics method used to call variants, the interpretation of those variants, and the knowledge of gene-disease associations at the time of interpretation. Therefore, it is not surprising that systematic reanalysis of ES data at regular intervals has been shown to provide a diagnosis in an additional 10-15% of cases. ES reanalysis is not routinely done for Manitoba patients; for this reason, we have developed a pilot project to reanalyze the ES data for patients who previously had non-diagnostic ES. We recruited 33 participants from 25 families who have received ES that failed to provide a definitive genetic diagnosis. The raw ES data for each participant was collected from the sequencing laboratories and variants were called using the bcbio-nextgen bioinformatics pipeline. Variants were annotated using the Ensembl Variant Effect Predictor. Custom filters were used to prioritize variants for review and pathogenicity of variants was assessed using the American College of Medical Genetics guidelines. We found candidate variants in 14 (56%) of the families analyzed, including 3 strong candidate variants and 6 variants in novel genes that have not previously been associated with disease. This study suggests that reanalyzing already generated ES data is an efficient way to increase genetic diagnoses for I patients in Manitoba. As well, analysis of variants in genes with unknown function may lead to future gene discovery projects, adding to our overall knowledge of human genetics. II ACKNOWLEDGMENTS Thank you to my thesis supervisor, Dr. Patrick Frosk, for his guidance throughout the project, for sharing his vast knowledge of medical genetics, for going through endless lists of gene candidates with me, and for teaching me that negative is just a state of mind. Thank you to my thesis committee, Claudia Carriles, Taila Hartley, and Dr. Pingzhao Hu, for all of your individual insights and guidance. Thank you to my program director, Jessica Hartley, for keeping me organized and for our office chats. This work could not have been completed without the help of Shirley Harvey who contacted participants for their consent, found all of the charts I had to review, and always knew the answer to my questions. I also want to extend my gratitude to the Care4Rare team: Grace Ediae, Magda Price, and Michelle Vandeloo, for assisting with Care4Rare ethics procedures and data accession. Thank you to Matt Osmond for his matchmaking expertise and guidance during exome rounds. A big thank you to the inaugural class, Angela Krutish, Ashleigh Hansen, and Rachelle Dinchong, for leading the charge and for showing me that success is possible. Thank you to my classmates, Emily Bonnell and Selina Casalino, for the love, support, commiseration, and good times throughout the program. Best of luck to the remaining genetic counselling students, Natasha Osawa, Cassie McDonald, and Dorothy Michalski, I’m so glad to have gotten to know you this past year. I would also like to extend my appreciation to the many supervisors I had throughout this program. I am grateful to my husband, Charlie Keown-Stoneman, for spending more time on airplanes these past two years than the rest of his life combined, and for always answering the phone when I was having a tough day. Thank you to the rest of my friends and family for their endless love and support. III I would like to acknowledge the families who were involved in this study. Living through a diagnostic odyssey cannot be easy, and I feel privileged to have had the opportunity to assist them in finding diagnoses. I received funding from the University of Manitoba Graduate Fellowship (Department of Biochemistry and Medical Genetics). IV TABLE OF CONTENTS ABSTRACT ....................................................................................................................................................... I ACKNOWLEDGMENTS .................................................................................................................................. III TABLE OF CONTENTS ..................................................................................................................................... V LIST OF TABLES ............................................................................................................................................. IX LIST OF FIGURES ............................................................................................................................................ X LIST OF ABBREVIATIONS .............................................................................................................................. XI CHAPTER 1: BACKGROUND AND REVIEW OF THE LITERATURE .................................................................... 1 1.1. Rare Disease ....................................................................................................................................... 1 1.2. Traditional Methods of Diagnosis ...................................................................................................... 2 1.3. Exome Sequencing ............................................................................................................................. 3 1.3.1. Criteria for Testing ...................................................................................................................... 3 1.3.2. Factors that Affect Diagnostic Rates ........................................................................................... 4 1.3.3. Beyond Single Nucleotide Causes of Disease .............................................................................. 6 1.3.4. Secondary Findings ..................................................................................................................... 8 1.3.5. When Exome Sequencing Cannot Find a Diagnosis .................................................................... 9 1.4. Exome Sequencing Reanalysis ........................................................................................................... 9 1.4.1. New Disease-Gene Associations ................................................................................................. 9 1.4.2. Variant Interpretation ............................................................................................................... 10 1.4.3. Trio Exome Sequencing as a Way to Increase Diagnoses ......................................................... 11 1.4.4. Bioinformatic Considerations .................................................................................................... 12 1.4.5. When to Reanalyse ................................................................................................................... 13 1.5. Clinical Analysis Versus Research Analysis ....................................................................................... 13 1.6. Potential Benefits of Genetic Diagnosis ........................................................................................... 14 1.7. Manitoba Population ....................................................................................................................... 17 1.8. Thesis Rationale ............................................................................................................................... 18 CHAPTER 2: METHODS ................................................................................................................................ 20 2.1. Ethics Approval ................................................................................................................................ 20 2.2. Participant Recruitment ................................................................................................................... 20 2.3. Chart Review and Phenotype Abstraction ....................................................................................... 22 2.4. Data Transfer ................................................................................................................................... 23 V 2.5. Bioinformatics Pipeline .................................................................................................................... 24 2.6. Variant Filtration .............................................................................................................................. 24 2.6.1. Filter 1: New Disease-Gene Associations and Previously Miscalled Variants
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