Combining European and U.S. risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study

Abstract

Aims: A polygenic risk score (PRS) has the potential to improve individual atherosclerotic cardiovascular disease (ASCVD) risk assessment. To determine whether a PRS combined with two clinical risk scores, the Systematic COronary Risk Evaluation 2 (SCORE2) and the Pooled Cohort Equation (PCE) improves the prediction of ASCVD.

Methods and results: Using a population-based European prospective cohort, with 6733 participants at the baseline (2003-2006), the PRS presenting the best predictive accuracy was combined with SCORE2 and PCE to assess their joint performances for predicting ASCVD Discrimination, calibration, Cox proportional hazard regression, and net reclassification index were assessed. : 4218 subjects (53% women; median age, 53.4 years), with 363 prevalent and incident ASCVD, were used to compare four PRSs. The metaGRS_CAD PRS presented the best predictive capacity (AUROC = 0.77) and was used in the following analyses. 3383 subjects (median follow-up of 14.4 years), with 190 first-incident ASCVD, were employed to test ASCVD risk prediction. The changes in C statistic between SCORE2 and PCE models and those combining metaGRS_CAD with SCORE2 and PCE were 0.008 (95% CI, -0.00008-0.02, P = 0.05) and 0.007 (95% CI, 0.005-0.01, P = 0.03), respectively. Reclassification was improved for people at clinically determined intermediate-risk for both clinical scores [NRI of 9.6% (95% CI, 0.3-18.8) and 12.0% (95% CI, 1.5-22.6) for SCORE2 and PCE, respectively].

Conclusion: Combining a PRS with clinical risk scores significantly improved the reclassification of risk for incident ASCVD for subjects in the clinically determined intermediate-risk category. Introducing PRSs in clinical practice may refine cardiovascular prevention for subgroups of patients in whom prevention strategies are uncertain.

Keywords: Adult; Cardiovascular disease; Genetic predisposition to disease; Polygenic risk score; Predictive value of tests; Primary prevention; ROC curve; Risk; Risk assessment; Sensitivity and specificity.