ABSTRACT Cardiovascular disease is a main cause of death and disability in individuals with chronic kidney disease (CKD) but little is known on the genetic factors accounting for the increased cardiovascular disease burden in CKD. Genome-wide association studies have identified several loci for cardiovascular disease and subclinical atherosclerosis traits. Studies have also shown that genetic variants that regulate gene expression have important roles in complex traits. We propose to test regulatory regions of the genome associated with cardiovascular outcomes using approaches that integrate gene expression data to genome-wide genotypes. We will use the comprehensive clinical and biomarker data from the Chronic Renal Insufficiency Cohort (CRIC), a multi-ethnic and longitudinal study of individuals with CKD. CRIC has adjudicated cardiovascular events in all participants and the study has already documented a high burden of atherosclerosis and cardiovascular disease in CKD. We will perform genome-wide association studies of cardiovascular outcomes using dense imputed genotypes from multi-ethnic reference panels obtained from the Trans-Omics for Precision Medicine (TOPMed) Program to identify new loci in individuals with CKD (Aim 1). To identify putative causal genes associated with cardiovascular disease in CKD, we will use predicted gene expression approaches and expression quantitative trait loci from ancestry-matched datasets (Aim 2) and multi-tissues (Aim 3). This project uses innovative concepts and approaches by integrating transcripts and genotypes for gene discovery in a high-risk population for cardiovascular disease. This project aligns with NHLBI mission to reduce the burden of CVD.