Genetics of atherosclerosis in renal disease

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DESCRIPTION (provided by applicant): Atherosclerotic cardiovascular disease (CVD) is an inflammatory disorder with a complex genetic basis. Chronic kidney disease (CKD), a major risk factor for CVD, is rapidly increasing in the U.S. The mechanistic link between these diseases remains largely undetermined. Recent studies suggest that insulin resistance, kidney dysfunction and CVD share common genetic bases. Innate immunity and insulin resistance converge in atherosclerosis and are prominent features of CKD. We hypothesize that, in this setting, genetic variation in innate immune and insulin resistance pathway genes will contribute individually and through multi-locus effects, to clinically important risk of CVD in the CKD population beyond traditional risk factors. The Chronic Renal Insufficiency Cohort (CRIC) Study, a prospective NIH sponsored multi-center study (n=3,000) of renal and CVD complications of CKD, provides a unique opportunity to examine these hypotheses. We will use re-sequencing data, available for most of our candidate genes (n=52) through NIH- sponsored programs, to select tagSNPs that define the common variation in innate immune (Aim 1) and insulin resistance (Aim 2) candidate genes. We will test the relationship of tagSNPs and haplotypes with inflammatory and insulin resistance biomarkers, coronary artery calcification (CAC), a direct measure of atherosclerosis, and clinical CVD outcomes. Our unifying hypothesis (Aim 3), with mechanistic, therapeutic and public health implications, is that multi- locus combinations of candidate gene will contribute in a clinically important manner to the attributable risk or CVD in the CKD population. This will be one of the first comprehensive, prospective, studies that will generate unbiased population-based risk data addressing this important and largely neglected component of genetic risk. We will pursue functional studies of SNPs, haplotypes and multi-locus genotypes, found to be associated with CVD that may, ultimately, change the paradigm of how we utilize human genetic data for therapeutic, diagnostic and public health purposes.