Polygenic Prediction of Recurrent Events After Early-Onset Myocardial Infarction

BACKGROUND: Myocardial infarction (MI) is a complex disease caused by both lifestyle and genetic factors. This study aims to investigate the predictive value of genetic risk, in addition to traditional cardiovascular risk factors, for recurrent events following early-onset MI. METHODS: The Italian Genetic Study of Early-Onset Myocardial Infarction is a cohort study enrolling patients with MI before 45 years. Monogenic variants causing familial hypercholesterolemia were identified, and a coronary artery disease polygenic score (PGS) was calculated. Ten-fold cross-validated Cox proportional hazards models were fitted sequentially including all clinical variables, the PGS, and monogenic variants on the composite outcome of cardiovascular death, recurrent MI, stroke, or revascularization. RESULTS: During a 19.9-year follow-up, 847 (50.7%) patients experienced recurrent events. Each 1-SD higher PGS was associated with a 21% higher hazard of recurrent events (hazard ratio, 1.21 [95% CI, 1.13–1.31]; P =4.04×10 −6 ). Except for secondary prevention, PGS was the strongest determinant of recurrent event risk (C index, 0.56 [95% CI, 0.54–0.58]) compared with clinical risk factors. Overall, predictive performance of clinical risk factors (C index, 0.69 [95% CI, 0.67–0.71]) improved after adding the PGS (C index, 0.69 [95% CI, 0.68–0.71]; P =0.006). When dividing the population by PGS quintiles, the highest fifth had a 57% higher hazard of recurrent events than the lowest fifth (hazard ratio, 1.57 [95% CI, 1.26–1.96]; P =5.57×10 −5 ). CONCLUSIONS: When compared with other clinical risk factors, PGS was the strongest predictor of event recurrence among patients with an early-onset MI. Though the discriminative power of recurrent event prediction in this cohort was modest, the addition of PGS significantly improved discrimination.