Cerebrovascular disease remains a major public health problem with a disproportionate impact on Hispanics. While our knowledge of stroke risk factors has improved, little is known regarding genetic influences. Given that stroke is a complex disease and a discrete trait, evaluation of quantitative cerebrovascular risk phenotypes will reduce etiologic heterogeneity, and therefore facilitate gene discovery. The goal of the Family Study of Stroke Risk and Carotid Atherosclerosis is to identify genetic determinants of specific cerebrovascular risk phenotypes which are precursors to stroke. In the first cycle, we assembled a family study database of 1390 subjects from 100 high-risk Dominican families, established the heritability of specific quantitative traits including carotid intima media thickness (IMT) and completed a genome wide scan. Preliminary peaks for carotid IMT were identified on chromosomes 14q (D14S606) and 7p (D7S817) and warrant further study.
The aims of this project are to identify the genes associated with carotid intima media thickness and carotid plaque burden. Starting with our preliminary peaks we will perform fine mapping using an iterative approach of linkage and family based association analyses to identify SNPs associated with our quantitative traits. We will also measure a new quantitative carotid phenotype, carotid plaque burden, from our stored imaging studies and evaluate for linkage followed by fine mapping. We will validate any putative trait-associated SNPs in a separate cohort study among Dominicans from our original Northern Manhattan Study. We have the unique ability to combine our Family Study with a validation association study drawn from other Dominican subjects in the Northern Manhattan Study cohort. The powerful approach of combining linkage with association in one ethnic group will facilitate gene discovery. These studies have the potential to identify novel genes underlying cerebrovascular risk phenotypes and stroke in the rapidly growing Hispanic population and help design innovative approaches to risk prediction and prevention.
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