Gene-based map of cardiovascular diseases
Abstract
Background: Rare coding variants contribute to cardiovascular disease, but their effects across disease groups remain incompletely characterized. In particular, the influence of functionally and clinically informed variant classification and sex-specific genetic effects on gene-phenotype associations remains understudied. Methods: We analyzed whole-genome sequencing data from up to 483,311 UK Biobank participants across six genetic ancestry groups and eight cardiovascular phenotype groups. Gene-burden testing integrated state-of-the-art missense classification and predicted pathogenic germline variants. We performed combined-sex and sex-stratified analyses, followed by cross-ancestry meta-analysis. We additionally adjusted for cardiometabolic traits in sensitivity analyses, estimated penetrance among qualifying-variant carriers, and assessed genetic prevalence across eight ancestry groups. Results: We identified 86 exome-wide significant gene-phenotype associations: 40 established and 46 novel. Novel associations included EHMT2 with atrial fibrillation, P2RX1 with arrhythmias, P2RY4 with complete atrioventricular block, and NOSTRIN with atherosclerotic heart disease in females. After cardiometabolic adjustment, 60 associations retained exome-wide significance and 18 additional associations emerged, including CDH11, PARVA, and ADAMDEC1 with atherosclerosis-related phenotypes. Conclusions: These findings identify novel cardiovascular gene-phenotype associations implicating purinergic signaling, endothelial nitric oxide regulation, and vascular wall biology. Variant selection shapes penetrance estimates and the interpretation of inherited susceptibility.
02 /Specification & Classification
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