Coronary artery disease (CAD) and myocardial infarction (MI) are the leading causes of death in the Western world. Numerous epidemiological studies have demonstrated the impact of various risk factors, such as arterial hypertension, hypercholesterolemia and diabetes mellitus. While these risk factors are partially under genetic control, a positive family history remains an additional independent predictor of CAD, suggesting the presence of additional susceptibility genes. In order to identify novel MI genes, we propose a family-based genome-wide high density association scan using the 1,000,000 Affymetrix SNP (single nucleotide polymorphism) chip genotyping platform in our large set of 1,000 families with MI and CAD. The phenotypic data in this population includes data on standard risk factors, medical history, extensive biochemical characterization, as well as a detailed description of the coronary anatomy as determined by angiography and follow-up examinations. With this extensive dataset and the complex nature of CAD and MI, a family-based analysis holds important advantages. This is related in particular to a reduced phenotypic heterogeneity in families, prior evidence of a significant genetic component as demonstrated by the identification of linkage signals, the possibility of combined linkage and association analyses, analyses incorporating shared genetic and environmental components as well as the analysis of genetic and environmental variance for multiple phenotypes. For the statistical analysis we will use standard analysis and linear models that consider the direct association of a SNP (or haplotype, or diplotype) on a trait while accounting for and quantifying residual genetic and/or environmental effects among the families. This approach should enable us to identify genetic markers, which contribute significantly to the risk of CAD, MI and associated risk factors. For replication, we have established a collaboration giving us access to a replication sample from the Marshfield Clinic Personalized Research Project which represents a population-based cohort. In addition, we will also test significant SNPs in an African American and US Caucasian cohort of patients with coronary angiographies. These populations will allow us to test the extent to which SNPs initially associated in the Caucasian families contribute to MI and CAD risk in other groups.
The risk of coronary artery is determined in part by genetic factors. We propose to perform a genome-wide association study to identify susceptibility genes for coronary artery disease, myocardial infarction and its related risk factors. This study will improve our understanding of the interplay of genetic and traditional risk factors.
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