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Integrative analysis of tissue specific transcriptomics with GTEx data to identify platelet aggregation genes

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Aggregation of activated platelets on ruptured or eroded atherosclerotic plaques initiates thromboses of the arterial system, resulting in ischemic syndromes. The propensity of platelets to aggregate in vivo can be characterized by in vitro assays and used to identify individuals with hyper-aggregable platelets who are then at risk for myocardial infarction, stroke, and peripheral arterial occlusions. These platelet function assays are moderately to highly heritable supporting the hypothesis that genetic variations underlie individual variability in the tendency for arterial thrombosis. During the past ten years, in an ongoing NHLBI-funded study called GeneSTAR (Genetic Study of Aspirin Responsiveness), a genome-wide association study (GWAS) revealed multiple common genetic loci that pass stringent GWAS thresholds in African American and European Americans families at high risk for CAD. Common variants were found to determine variability in native platelet aggregation as well as residual platelet aggregation after low dose aspirin (ASA) intervention. However, collectively the loci identified through this common variant approach account for less than 35% the total heritability of these phenotypes in the GeneSTAR families. Leveraging three independent pre-existing grants within the GeneSTAR Program along with our recently obtained TOPMed Program Award we have a unique opportunity to perform integrative multi-omic analyses (genomics and transcriptomics) beyond the scope of traditional genetic association studies, to identify functional genetic determinants of platelet aggregation in African American and European American families at high risk for coronary artery disease (CAD). We plan to use GWAS and whole genome sequence data integrated with RNA sequence data on two cell types of relevance (megakaryocytes and platelets). In this R21 that is devoted to the secondary analysis of three datasets we will rely on internal and external expertise to generate a model for transcriptome imputation leveraging public data from the Genotype-Tissue Expression (GTEx) project followed by tests for association across a wide range of platelet aggregation phenotypes. Our goal is to uncover the determinants of high residual heritability of platelet aggregation through the new and novel application of transcriptomic imputation.
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