Abstract

Background: Peripheral artery disease (PAD) is a heritable atherosclerotic condition. With growing knowledge of the genetic basis for PAD and related risk factors, there is opportunity to identify high-risk individuals for prevention and potentially intervention based on polygenic background. Aims: To develop and validate an integrated genome-wide polygenic score for PAD (GPS PAD ), evaluate association of polygenic risk with major adverse limb events (MALE), and compare predictive performance in diverse ancestral populations to previously published polygenic scores. Methods: We developed GPS PAD by integrating genetic association summary statistics for PAD and related traits stratified by ancestry. GPS PAD was trained in a sample of 96,239 European individuals from the UK Biobank, and validated in multi-ancestry cohorts, including a holdout validation UK Biobank dataset (N=304,294), and external All of Us (AoU; N=237,173) and Mass General Brigham Biobank datasets (N=37,017). GPS PAD performance was benchmarked against previously published polygenic scores and clinical risk factors. Results: GPS PAD was comprised of 603,595 variants with weights informed by association with PAD and ten PAD risk factors across five ancestry groups. GPS PAD had an OR-per SD of 1.63 in the holdout UK Biobank dataset (95% CI 1.60-1.68). GPS PAD outperformed previously published scores in non-European subgroups in the UK Biobank and achieved superior cross-population portability in external validation cohorts. GPS PAD was associated with incident PAD in the UK Biobank (HR 1.66; 95% CI 1.61-1.71) and achieved improvements in discrimination (ΔC-statistic 0.030) that were nearly equivalent to the additive performances of diabetes (ΔC-statistic 0.029) and smoking (ΔC-statistic 0.034) to the baseline model including age, sex, and 10 principal components of ancestry. Among individuals with prevalent PAD, GPS PAD was associated with incident MALE in the UK Biobank (HR 1.48; 95% CI 1.24-1.77). GPS PAD consistently identified individuals with PAD at high MALE-risk in the Mass General Brigham Biobank (HR 1.34; 95% CI 1.12-1.60), and AoU (HR 1.33; 95% CI 1.12-1.58). Conclusions: These findings contribute a polygenic score for PAD that predicts disease and MALE with cross-cohort performance and transferability to diverse ancestries. Integrated polygenic scores may be used to stratify PAD risk and target more aggressive management, lifestyle modification, and surveillance efforts.