| Popis: |
Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan–Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10−5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10−4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged |
