Gene-Environment Interactions in Complex Disease

BACKGROUND:

Cardiovascular disease (CVD), the number one cause of death in industrialized countries today is a complex disease with a multifactorial etiology involving many genetic and environmental factors. Public health prevention programs designed to reduce the risk and occurrence of CVD commonly focus on modifiable environments and behaviors such as diet and physical activity, with varied results among individuals. This heterogeneity in response to CVD interventions is at least in part of genetic origin. Although a number of candidate genes have been identified which appear to influence the development of CVD, little is known about how these genetic effects may vary within demographic (e.g., race and gender) and environmental (e.g., diet and exercise) contexts; thus, it is of utmost importance to determine how genes and environments interact to produce CVD.

DESIGN NARRATIVE:

The purpose of this study is to characterize the environment-dependent effects of 87 biologic and positional candidate genes in a population-based sample of 11,625 African-American and Caucasian men and women from the Atherosclerosis Risk in Communities (ARIC) study. Candidate loci were selected based on confirmed functional significance, consistent association with CVD or its risk factors, and or identified as positional candidates in genome-wide linkage scans. Environmental contexts will focus on dietary measures (e.g., total kcals, Keys score, alcohol intake), obesity, measures of physical activity (sport, leisure, and work indices), smoking, and menopause status/hormone use (women only). Outcome variables will include measures of quantitative risk factors (e.g., total cholesterol, BMI, blood pressure), subclinical disease (carotid wall thickness), and clinical disease (incident coronary heart disease (CHD) and stroke). Existing DNA samples will be used for genotyping of candidate loci, and no further contact with study participants will be necessary. The ARIC cohort, because of its large size and wealth of environmental and physiological measures, provides an ideal, timely, and efficient opportunity to evaluate the effects of modifiable environments on genetic variation which may influence CVD risk and disease outcomes with the ultimate goal of establishing more efficacious programs for the treatment and prevention of CVD.