为高风险人群开发和验证风险预测算法,该算法结合了心血管疾病的遗传和传统风险因素
Tuuli Puusepp1,2, Ave Põld3, Lili Milani2
1Institute of Mathematics and Statistics, University of Tartu.
PloS one
|October 21, 2025
概括
多基因风险评分 (PRS) 在与传统因素相结合时,显著改善了心血管疾病 (CVD) 风险预测. 这种增强的风险评估即使在年轻人中也是有价值的.
科学领域:
- 遗传学和心血管流行病学
- 生物标志物在疾病预测中的作用
- 公共卫生和预防医学
背景情况:
- 心血管疾病 (CVD) 仍然是全球主要的死亡原因.
- 传统的风险因素 (如年龄,性别,生活方式) 为心血管疾病风险评估提供了基线.
- 整合遗传信息,如多基因风险得分 (PRS),可能会提高风险预测的准确性.
研究的目的:
- 开发和验证一种CVD风险预测模型,将PRS与传统风险因素一起结合起来.
- 评估PRS在生物银行队列中的不同年龄组的增量预测值.
- 评估PRS在常规心血管风险评估中的有用性.
主要方法:
- 利用了128,209名爱沙尼亚生物库参与者的数据,没有流行心血管疾病.
- 采用考克斯比例危险模型和阿伦-约翰森曲线来估计危险比率和累积发病率.
- 使用分割样本方法,竞争性风险建模,Harrell的C指数和净重新分类指数 (NRI) 验证了预测性表现.
主要成果:
- PRS与心血管疾病风险有显著的关联,每标准偏差的危险比为1.1至1.36.
- 将PRS添加到常规因素中,在25-59岁的男性中改善了0.028的模式歧视 (C统计),在60岁以上的男性中改善了0.016的模式歧视.
- 持续的NRI表明风险重新分类的实质性改善:年龄在25-59岁之间为19.1%,年龄在60岁以上为13.9%.
结论:
- 多基因风险评分是高风险人群中心血管疾病的强大,独立的预测指标.
- 将PRS纳入风险评估模型提供了显著的附加值,特别是对于年轻人来说.
- 建议在心血管风险评估中定期实施PRS,从年轻时开始.
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