心血管疾病(CVD)仍然是全球死亡的主要原因,由遗传和环境因素的复杂相互作用引起的。这项研究旨在评估多基因风险评分和合并队列方程(PCE)的综合疗效,以预测韩国人群未来的CVD风险。在这项纵向研究中,在17年的随访期内,对来自Ansan和Ansung队列的7,612名个体进行了分析。参与者使用韩国生物样本库阵列进行基因分型,和质量控制的遗传数据进行了归因分析。使用PRS-CS计算PRS的加权和(wPRSsum)与来自心肌梗死的汇总统计,缺血性卒中,冠状动脉疾病,和高血压全基因组关联研究。重新校准的PCE用于评估临床风险,根据wPRSsum和PCE将参与者分为风险组.使用Cox比例风险模型和Kaplan-Meier分析评估这些风险评分与心血管事件之间的关联。wPRSsum方法显示与心血管事件有显著关联(HR=1.15,p=7.49×10-5),前20%的高危遗传组的HR为1.50(p=5.04×10-4)。重新校准的PCE有效区分了低和高10年CVD风险组,生存率有明显差异。使用wPRSsum和PCE构建的预测模型在预测精度上略有提高,尤其是年龄<55岁的男性(C指数=0.640)。我们证明,尽管wPRSsum与PCE的集成并没有明显优于仅PCE模型(C指数:组合为0.703,仅PCE为0.704),它增强了CVD风险的分层.最高风险组,通过高wPRSum和PCE分数的组合识别,对于入射CVD,HR为4.99(p=1.45×10-15)。这些发现强调了将遗传风险评估与传统临床工具相结合以进行有效的CVD风险分层的潜力。尽管将wPRSsum添加到PCE中提供了边际预测性改进,它在识别高危个体和支持个性化治疗策略方面被证明是有价值的。这项研究加强了多PRS与临床风险评估工具的结合,为更有针对性的方法在不同人群中预防和管理心血管疾病铺平了道路。
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 <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with
PCE did not significantly outperform the
PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.