Genomic Risk Prediction of Recurrent Cardiovascular Diseases in the UK Biobank

Abstract

Polygenic risk score (PRS) shows promise in predicting the risk of cardiovascular diseases (CVD) based on the genotypes of an individual, but most analyses have traditionally focused on the diseases’ onset. The usefulness of PRS to predict recurrence remains unclear. In this study, we built a meta-PRSCVD upon the candidate PRSs developed from state-of-the-art PRS methods for three CVD subtypes of significant importance: coronary artery disease (CAD), ischemic stroke, and heart failure. To evaluate the prediction performance of the meta-PRSCVD, we restricted our analysis to 24,704 white British CAD patients in the UK Biobank, among which 6,999 had CVD recurrent events. Results showed that the meta-PRSCVDwas significantly associated with CVD recurrence with a hazard ratio per standard deviation increase of 1.24 (95% CI: 1.20-1.27). After adjustment for age, sex, and the first ten principal components of genotypes, the meta-PRSCVD predicted the recurrence with an AUC of 0.64 (95% CI: 0.62-0.66). When restricted to the early-onset patients (onset age <= 55), the AUC was further increased to 0.75 (95% CI 0.72-0.78). Our results highlight the potential role of genomic screening for secondary preventions of CVD, especially among early-onset CAD patients.