Atherosclerosis is the major cause of coronary artery disease (CAD), the single largest killer of American men and women. Oxidative stress leading to endothelial dysfunction is an underlying factor whereby hypertension contributes to the atherosclerotic process. This project entitled "Genes of Oxidative Stress and Atherosclerotic Complications of Hypertension" proposes to characterize the role of oxidative stress pathway gene variation in the genetic architecture of coronary artery calcification (CAC), a measure of subclinical coronary atherosclerosis. This research project will use a gene network approach to identify genes that influence the ability of the coronary artery to resist injury due to hypertension. All DNA resources, CAD risk factors, physical examination data and CAC measures are already available to this project from three cohorts. Models of the hypothesized relationships between genetic polymorphisms, covariates, hypertension and subclinical coronary atherosclerosis will be evaluated using CAC, already measured on individuals with a personal or family history of essential hypertension from the Genetic Epidemiology Network of Arteriopathy (GENOA), Rochester, MN fieldcenter and on individuals with a personal or family history of hypertension from the Epidemiology of Coronary Artery Calcification (ECAC) study, also from Rochester, MN. The generalizability of findings which replicate will be sought in the individuals of the Multi-Ethnic Study of Atherosclerosis (MESA). We will use this oxidative stress gene network-based approach to move beyond single polymorphism effects and investigate how single-genes, gene-by-gene interactions and gene-by-environment interactions combine to influence CAC quantity in individuals with hypertension or at increased risk of hypertension.
Atherosclerosis is the major cause of coronary artery disease (CAD), the single largest killer of American men and women. Increasing our understanding of the role of genetic variation in sub-clinical coronary atherosclerosis in diverse populations can contribute to the earlier identification of individuals with increased susceptibility to clinical disease, the development of new, more efficacious treatments, and tailoring of treatments to those most likely to respond.
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