Date of Award

Spring 5-2020

Degree Name

Doctor of Philosophy (PhD)

Advisor(s)

ERIC BOERWINKLE, PHD

Second Advisor

HAN CHEN, PHD

Third Advisor

MINJAE LEE, PHD

Abstract

Cardiovascular disease (CVD), including conditions of the heart, small vessel diseases of the brain and related diseases of the circulatory system, including hypertension, are leading causes of morbidity and mortality in the world. CVD risk factors include, but are not limited to, dyslipidemia (elevated levels of low-density lipoprotein cholesterol [LDL-C] and total cholesterol [TC], decreased levels of high density lipoprotein cholesterol [HDL-C]) and increased systolic blood pressure (BP). Multiple genes affecting lipoproteins and BP levels have been identified, but only ~5% of the population variation in lipid profiles, and ~2% of the population variation in BP and hypertension are explained by the discovered genetic loci. Levels of CVD risk factors change with age, and genetic factors influence that change. Understanding the longitudinal change of risk factors may improve CVD risk prediction. To help identify underlying mechanisms of the onset and progression of CVD, I first performed an exome-wide association study of levels and longitudinal change of CVD risk factor phenotypes among European-Americans (EAs) and African-Americans (AAs) of the Atherosclerosis Risk in Communities (ARIC) study. Set-based aggregation tests identified two loci, driven by one low-frequency missense variant. An aggregation of variants in DCLK3, an epithelial-to-mesenchymal transition-related genes regulator, is associated with an increase in HDL-C levels with time in AAs. An aggregation of variants in RAB7L1, involved in lysosomal trafficking and maintenance, is associated with an increase in LDL-C levels with time in EAs. Additionally, RAB7L1 is associated with increased incidence of heart failure in ARIC EAs. Second, I investigated how potential effect modifiers (Body Mass Index [BMI], estimated Glomerular Filtration Rate [eGFR], white blood cell counts) alter the relationship of genetic loci with the levels of the CVD risk factors, and identified three novel genetic loci. In EAs, single variant analysis showed that missense variant rs17076657, belonging to RXFP2 (encoding for a relaxin hormonal receptor), interacts with eGFR to affect SBP levels, while PLEKHG4 variant rs11860295 interacts with BMI to affect HDL-C levels. In AAs, gene-based analysis revealed an interaction of an aggregation of variants in NME7 (involved in biogenesis and function of primary cilia) with eGFR to affect TC levels. These results improve our understanding of possible effect-modifiers on longitudinal change of risk factors and CVD outcomes, stressing the importance of a comprehensive analysis of the available longitudinal cohort data.

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