Cardiovascular disease (CVD) is the leading cause of mortality in the United States. Twin and family-based studies have demonstrated a strong genetic contribution to a wide-array of CVD-related traits. Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with CVD-related traits such as body mass index, lipid levels and hypertension. In aggregate these associated genetic variants explain only a small proportion of the overall genetic contribution to these traits. The interplay between genes and environmental exposures is likely to play a substantial role in explaining away some of these missing trait heritabilities. GWAS studies have largely ignored this consideration, despite the growing empirical evidence that such interactions are important. One major limitation has been that statistical power to detect these interactions is severely limited by the added complexity and dimensionality of studying such interactions. High multiple-test corrected significance thresholds from studying pair-wise interactions require interaction effects to be considerable and the sample size of the study cohort to be very large. In this study, we propose to apply a novel approach to reduce the dimensionality of this interaction problem. Prior to testing specific interactions, we propose to first identify a reduced set of variants that demonstrate some evidence, based on heteroscedasticity of genotype effects, for being subject to interaction. We also propose to use our unique knowledge of the public NHGRI genetic database dbGaP to identify, harmonize and combine genetic, phenotypic and environmental exposure data across large relevant genetic-epidemiological studies to increase our statistical power. The goal of this study is to identify important GxE interactions that impact CVD in order to provide greater insight into the molecular mechanisms of the disease and facilitate more targeted and more effective intervention strategies.

Public Health Relevance

Cardiovascular disease (CVD) is the leading killer of Americans. The proposed work will identify novel genetic-environmental interactions that influence CVD related traits such as blood pressure, lipid levels and adiposity. The results may lead to improved disease diagnosis and treatment.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZRG1)
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Jaquish, Cashell E
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University of North Carolina Chapel Hill
Schools of Medicine
Chapel Hill
United States
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Corty, Robert W; Valdar, William (2018) QTL Mapping on a Background of Variance Heterogeneity. G3 (Bethesda) 8:3767-3782
Raffield, Laura M; Ellis, Jaclyn; Olson, Nels C et al. (2018) Genome-wide association study of homocysteine in African Americans from the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Coronary Artery Risk in Young Adults study. J Hum Genet 63:327-337
Duan, Qing; Xu, Zheng; Raffield, Laura M et al. (2018) A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations. Genet Epidemiol 42:288-302
Corty, Robert W; Kumar, Vivek; Tarantino, Lisa M et al. (2018) Mean-Variance QTL Mapping Identifies Novel QTL for Circadian Activity and Exploratory Behavior in Mice. G3 (Bethesda) 8:3783-3790
Corty, Robert W; Valdar, William (2018) vqtl: An R Package for Mean-Variance QTL Mapping. G3 (Bethesda) 8:3757-3766
Raghavan, S; Zhang, W; Yang, I V et al. (2017) Association between gestational diabetes mellitus exposure and childhood adiposity is not substantially explained by offspring genetic risk of obesity. Diabet Med 34:1696-1700
Raffield, Laura M; Zakai, Neil A; Duan, Qing et al. (2017) D-Dimer in African Americans: Whole Genome Sequence Analysis and Relationship to Cardiovascular Disease Risk in the Jackson Heart Study. Arterioscler Thromb Vasc Biol 37:2220-2227
Li, Jin; Shi, Jinxiu; Huang, Wei et al. (2015) Variant Near FGF5 Has Stronger Effects on Blood Pressure in Chinese With a Higher Body Mass Index. Am J Hypertens 28:1031-7