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Raffield Wfu 0248D 10776.Pdf Analysis of the genetic and epidemiological contributors to aging-related traits in the Diabetes Heart Study Laura Marie Tonks Raffield A Dissertation Submitted to the Graduate Faculty of Wake Forest University Graduate School of Arts and Sciences in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy In Molecular Genetics and Genomics May 2015 Winston-Salem, North Carolina Committee: Dr. Donald Bowden (Advisor) Dr. Timothy Howard (Chair) Dr. Fang-Chi Hsu Dr. Barbara Nicklas Dr. Maggie Ng Acknowledgements First, I would like to thank my advisor, Donald Bowden, for giving me the opportunity to work in the Bowden lab. I cannot think of an environment that would have been a better fit for my goals and interests, and I’ve learned a great deal both about human genetics and about science as a profession. I truly appreciate your dedication to mentoring, your advice on analyses, manuscript writing, grants, and your support for my ideas and projects; I couldn’t have asked for a better advisor. I would also like to thank my committee members for all of their help. Thanks to Timothy Howard for his help navigating graduate school and leading my committee and for his sense of humor and open door for students. I am so grateful to Fang-Chi Hsu for her perennial kindness and patience with my many, many statistics related questions and for all of her advice… I have learned so much from you! Thanks to Maggie Ng for patiently answering many questions over the years and for giving me many helpful ideas on how to improve on analyses. Finally, many thanks to Barbara Nicklas for her advice and insights in the field of aging research and for encouraging me to get to know a number of people at the Sticht Center and to attend the Gerontological Society of America meeting, both of which were amazing learning experiences. I have been so lucky to be part of the Bowden lab group… thanks to all of you for helping me out countless times and being excellent company, I will miss everyone! I would especially like to thank those who helped me with this dissertation research: Amanda Cox, for her help training me in the lab and her inexhaustible patience and kindness, Nichole Allred, for help with countless questions and many conversations that brightened my day, JJ Xu, for his patience and help with the DHS database, Carrie Smith, for all her hard work on the DHS study, Pam Hicks, for being an amazing lab manager and awesome company, and Jackie Hellwege, for all her help during graduate school, including helping me edit this dissertation, and for being a great office next door neighbor. ii Thanks also to the many investigators at Wake Forest that I have had the privilege to collaborate with… there are too many people to list here, but I would especially like to thank for their help with this dissertation Barry Freedman, for his advice, enthusiasm, and encouragement, and for all his work with the DHS study, and Christina Hugenschmidt, for her help understanding our cognition and neuroimaging data and for organizing journal clubs and other opportunities to help others learn more about the aging brain. Thanks also to everyone in the Genomics Center for their help and support, and to the many individuals who have volunteered to take part in the Diabetes Heart Study and other studies in the lab; obviously, this research is not possible without you! I would also like to thank the many individuals at the Medical University of South Carolina, especially Tammy Nowling and Gary Gilkeson, and at the University of North Carolina, especially Steve Matson, for their help and support and for encouraging my interest in research and in attending graduate school. Last but certainly not least, many thanks to my amazing family and friends for their unconditional love and support; I’m so blessed to have you all in my life. Thanks especially to my parents, for always believing in me and being on my side, my siblings, Emily and William, for being so encouraging and making me laugh, and my husband, Taylor, for just generally being the best and helping me more times and in more ways than I can count. iii Table of Contents Page Number List of Tables vi List of Figures xii Abbreviations xiii Abstract xv Chapter 1: Introduction 1 Chapter 2: Analysis of Coding Variants in C1q/TNF Superfamily Genes in the 15 Diabetes Heart Study and Replication in Additional Cohorts Chapter 3: Family-Based Linkage Analysis of Cardiometabolic Traits in the 31 Diabetes Heart Study Chapter 4: Heritability and Genetic Association Analysis of Neuroimaging 60 Measures in the Diabetes Heart Study Published in Neurobiology of Aging Chapter 5: Impact of HDL genetic risk scores on coronary artery calcified 155 plaque and mortality in individuals with type 2 diabetes from the Diabetes Heart Study Published in Cardiovascular Diabetology Chapter 6: Analysis of a Cardiovascular Disease Genetic Risk Score in the 187 Diabetes Heart Study Published in Acta Diabetologica Chapter 7: Predictors of all-cause and cardiovascular disease mortality in type 250 2 diabetes: Diabetes Heart Study Submitted to Diabetology & Metabolic Syndrome Chapter 8: Cross-sectional analysis of calcium intake for associations with 280 vascular calcification and mortality in individuals with type 2 diabetes from the Diabetes Heart Study Published in American Journal of Clinical Nutrition Chapter 9: Associations of Coronary Artery Calcified Plaque Density with 304 Mortality and Prior Cardiovascular Disease Events in Type 2 Diabetes: the Diabetes Heart Study Chapter 10: Associations between Anxiety and Depression Symptoms and 324 Cognitive Testing and Neuroimaging in Type 2 Diabetes Chapter 11: Associations between Type 2 Diabetes Status and Glycemic 351 iv Control and Neuroimaging Measures in the Diabetes Heart Study-Mind Chapter 12: Summary and Conclusions 366 Appendices A.1. Analysis of Apolipoprotein E Polymorphisms and Alzheimer’s 372 Disease Genetic Risk Score in the Diabetes Heart Study A.2. Longitudinal Analysis of Thoracic Bone Mineral Density in the 384 Diabetes Heart Study A.3. Association of Magnesium Intake with Vascular Calcification and 390 Mortality in the Diabetes Heart Study A.4. Additional Genotyped Variants in the Diabetes Heart Study Cohort 398 References 404 Curriculum Vitae 422 v List of Tables Page Number Chapter 1 Table 1: Select Age-related Phenotypes available in Diabetes Heart Study and 13 Diabetes Heart Study-Mind Table 2: Baseline Demographic and Clinical Characteristics of Diabetes Heart 14 Study Participants Chapter 2 Table 1: Demographic characteristics of the Diabetes Heart Study population 25 stratified by type 2 diabetes (T2D) affected status. Table 2: Significant single variant association analysis results for Exome Chip 26 coding variants in C1q/TNF superfamily members and their binding partners and receptors. Table 3: Significant gene-based analysis results using the sequence kernel 27 association test (SKAT) for coding variants in C1q/TNF superfamily members and their binding partners and receptors. Table 4: Basic demographic data for genotyped individuals from cohorts 28 included in the Claude Pepper Older Americans Independence Center Biospecimen Repository, including the Diet, Exercise, and Metabolism for Older Women Study (DEMO), the Intensive Diet and Exercise for Arthritis (IDEA) study, the Reconditioning Exercise and COPD Trial II (REACT), and the Lifestyle Interventions and Independence for Elders pilot (LIFE-P). Table 5: Variants genotyped in Claude Pepper Older Americans Independence 29 Center Biospecimen Repository cohorts. Table 6: Meta-analysis of association analysis results from METAL for Claude 30 Pepper Older Americans Independence Center Biospecimen Repository cohorts and the Diabetes Heart Study. Results include only cohorts with a given phenotypic measure, and results are stratified by EA (European American) cohorts only and EA and African American (AA) cohorts combined. Chapter 3 Table 1: Demographic characteristics of the Diabetes Heart Study population 39 stratified by type 2 diabetes (T2D) affected status. Table 2: Top association analysis results (p≤ 1 x 10-5) from the Exome Chip 40 with some evidence for linkage (logarithm of the odds (LOD) >1.0) and a trait- specific minor allele count ≥ 5 for the 34 cardiometabolic traits available in most Diabetes Heart Study participants. Table 3: Top association analysis results (p≤ 1 x 10-5) from the genome-wide 41 association study array with some evidence for linkage (logarithm of the odds (LOD) >1.0) and a trait-specific minor allele count ≥ 5 for the 34 cardiometabolic traits available in most Diabetes Heart Study participants. Table 4: Top association analysis results (p≤ 1 x 10-5) from the Exome Chip 42 with some evidence for linkage (logarithm of the odds (LOD) >1.0) and a trait- specific minor allele count ≥ 5 for the 9 traits available in 520 individuals from the Diabetes Heart Study or less. Table 5: Top association analysis results (p≤ 1 x 10-5) from the genome-wide 43 association study array with some evidence for linkage (logarithm of the odds (LOD) >1.0) and a trait-specific minor allele count ≥ 5 for the 9 traits available in 520 individuals from the Diabetes Heart Study or less. vi Chapter 4 Table 1: Demographic characteristics of the 465 DHS-Mind participants with 78 genotyping data. Table 2: Heritability estimates for MRI imaging variables in related individuals 80 from the Diabetes Heart Study Cohort. Table 3: Genetic association (assuming an additive model of inheritance) 82 between candidate SNPs and neuroimaging measures. Table S1A: Association statistics for the top 50 SNPs associated with TBV. 84 Table S1B: Association statistics for the top 50 SNPs associated with GMV. 87 Table S1C: Association statistics for the top 50 SNPs associated with WMV. 90 Table S1D: Association statistics for the top 50 SNPs associated with GMFA.
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