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HU-DISSERTATION-2015.Pdf (12.74Mb) Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Hu, Xinli. 2015. Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:17467297 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases A dissertation presented by Xinli Hu to The Division of Medical Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Biological and Biomedical Sciences Harvard University Cambridge, Massachusetts May 2015 © 2015 Xinli Hu All rights reserved Dissertation Advisor: Dr. Soumya Raychaudhuri Xinli Hu Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases Abstract Autoimmune diseases are chronic and debilitating conditions arising from abnormal immune responses directed against normal body tissues; they collectively affect the lives of 5-10% of the world population. These diseases often show familial clustering, suggesting strong genetic heritability. For many of autoimmune diseases, variation in the human leukocyte antigen (HLA) genes is the primary modulator of genetic risk. Recently, genome-wide association studies (GWAS) identified hundreds of genomic regions outside the HLA that harbor additional risk-conferring variants. The ultimate goal is to identify the precise causal variants and understand the mechanisms by which they lead to autoimmunity, which is challenged by complexities of the genome and the immune system. In this work, my colleagues and I developed and applied experimental and computational tools to reveal critical clues from multiple genetic and biological data types. First, we devised a statistical algorithm to identify the critical cell types involved in different autoimmune diseases. Two strongly heritable and common diseases, rheumatoid arthritis (RA) and type 1 diabetes (T1D), both involve the adaptive immune system, specifically the CD4+ T cells. We then conducted focused studies in CD4+ T cells using high-throughput genomic and proteomic technologies, and showed that immunological phenotypes and functions varied with genetic differences across individuals. To facilitate this study, we developed an automated computational tool to efficiently and reliably analyze the large-scale data. Finally, the HLA genes, which encode a family of highly variable antigen-recognition proteins, are the longest-known and strongest modulators of genetic risk in T1D. However, the extraordinary level of polymorphism and complex structure in the HLA region iii largely hindered precise localization and functional investigation of the causal mutations. We used dense-genotyping and robust statistical analyses to pinpoint the amino acid residue changes at a few key amino acid positions that explained the majority of disease risk within the HLA. The work presented in this dissertation revealed the specific immune cell populations, genetic variants, and cellular functions that affect RA, T1D, and other autoimmune diseases. Furthermore, it offers a rational framework, as well as powerful open-source computational tools, that can be applied in future functional genomic studies. iv TABLE OF CONTENTS Abstract iii Table of contents v Acknowledgment vi Attributions viii Chapter 1. Introduction 1 Chapter 2. Genes in autoimmune risk loci are specifically expressed in critical immune cell types 17 Chapter 3. X-Cyt: automated cytometric data analysis 60 Chapter 4. Regulation of gene expression in autoimmune disease loci and the genetic Basis of proliferation in CD4+ effector memory T cells 106 Chapter 5. Fine-mapping the HLA genetic associations in type 1 diaBetes 168 Chapter 6. Conclusion and discussion 215 v ACKNOWLEDGMENT First and foremost, I thank my amazing parents for their unconditional love and support. You encourage me to do my best professionally; more importantly, you remind me to remain balanced and humble. I would not have come this far in school or in life without your inexhaustible wisdom and forgiveness. If I had achieved anything at all, all credit goes to you. I have been extremely fortunate to have Dr. Soumya Raychaudhuri as my PhD advisor. Thank you for teaching me everything I know about genetics. You are not only an incredible physician-scientist and intellect, but also a marvelous person and a great friend. Your knowledge and compassion have made every aspect of the past six years incredibly fulfilling and truly enjoyable. Every fellow trainee who has been lucky enough to receive your mentorship appreciates and admires your special ability to “keep it real”; I am especially grateful for your patience, understanding, and a great sense of humor, which were invaluable and kept me going through even the toughest times. I would like to thank all past and current members of the Raychaudhuri lab for their support and companionship. You are a special crowd, and made NRB255 the most relaxed, friendly, fun, and productive work environment. I would also like to thank members of my dissertation advisory committee, Drs. Joel Hirschhorn, Vijay Kuchroo, and George Church, for your time and helpful discussions. In addition, I would like to thank Drs. Jill Mesirov, David Hafler, and Philip De Jager, who introduced me to this wonderful community of researchers at Harvard/MIT. Working with you, I first experienced the ins and outs of multidisciplinary research, and came to love it. Thank you to my family and friends near and far, who supported me over the years. Thank you to Yin-Yin Wang, Jennifer Wei, and my cousin Zhang Ying, for your companionship, for listening to me and keeping me going through thick and thin. Thank you to Kuai Letian for sharing with me vi your passion for science and life. Thank you to Zhang Zhourui for being a great friend and sister for the last 15 years. Thanks to all of my childhood friends in Nanjing for keeping the seemingly distant parts of my life always colorful. Finally, I would like to thank HMS/HST for giving me this rare opportunity, and my classmates for being such inspiring and generous people. All across the world, there are many with talent and potential, but for whom opportunity is a luxury. I am grateful for all that has been bestowed upon me; it has been a humbling experience. vii ATTRIBUTIONS Chapter 2 Xinli Hu designed and wrote the algorithm, performed data analysis, and wrote the manuscript. Hyun Kim performed data analysis and edited the manuscript. Eli Stahl and Robert Plenge provided statistical guidance for data analysis and edited the manuscript. Mark Daly conceived of the study and provided guidance for data analysis. Soumya Raychaudhuri conceived of the study, designed and wrote the algorithm, performed data analysis, and wrote the manuscript. Chapter 3 Xinli Hu conceived of the study, designed and wrote the algorithm, performed data analysis, and wrote the manuscript. Hyun Kim performed all experiments and manual analyses, and edited the manuscript. Patrick J. Brennan designed experiments and assays for the iNKT cell studies, provided guidance on experimental protocols and data analysis, and edited the manuscript. Buhm Han provided critical feedback on data analysis and edited the manuscript. viii Clare Baecher-Allan provided critical guidance on the design and experimental protocols of the T cell study, and edited the manuscript. Philip L. De Jager provided samples for the study, and edited the manuscript. Michael B. Brenner provided critical guidance on experimental design and edited the manuscript. Soumya Raychaudhuri conceived of the study, designed the experiments, provided guidance on data analysis, and edited the manuscript. Chapter 4 Xinli Hu designed the study, performed data analyses, and wrote the manuscript. Hyun Kim performed all experiments, conducted data analyses, and wrote the manuscript. Towfique Raj ,Gosia Trynka, Kamil Slowikowski and Nick Teslovich performed data analyses, and edited the manuscript. Patrick J. Brennan designed the experiments, provided feedback on data analysis, and edited the manuscript. Wei-Min Chen and Suna Onengut provided genotype data and edited the manuscript. ix Clare Baecher-Allan provided critical guidance on the design and experimental protocols of the T cell study, and edited the manuscript. Philip L. De Jager provided genotype data and blood samples. Stephen S. Rich provided genotype data, critical guidance on data analyses, and edited the manuscript. Barbara E. Stranger provided feedback on data analyses and edited the manuscript. Michael B. Brenner provided guidance on experimental protocol, data analyses, and edited the manuscript. Soumya Raychaudhuri conceived the study, designed the experiments, performed and provided guidance on data analyses, and wrote the manuscript. Chapter 5 Xinli Hu and Aaron J. Deutsch designed and performed the analyses, and wrote the manuscript. Tobias L. Lenz performed data analysis, and edited the manuscript. Suna Onengut-Gumuscu and Wei-Min Chen provided genotype data and guidance on data analysis. Buhm Han provided scripts and critical
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