Urbut Sarah M, Yeung Ming Wai, Khurshid Shaan, Cho So Mi Jemma, Schuermans Art, German Jakob, Taraszka Kodi, Fahed Akl C, Ellinor Patrick, Trinquart Ludovic, Parmigiani Giovanni, Gusev Alexander, Natarajan Pradeep
Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA.
medRxiv. 2023 Nov 8:2023.11.08.23298229. doi: 10.1101/2023.11.08.23298229.
Currently, coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. We designed a novel and general multistate model (MSGene) to estimate age-specific transitions across 10 cardiometabolic states, dependent on clinical covariates and a CAD polygenic risk score. MSGene supports decision making about CAD prevention related to any of these states. We analyzed longitudinal data from 480,638 UK Biobank participants and compared predicted lifetime risk with the 30-year Framingham risk score. MSGene improved discrimination (C-index 0.71 vs 0.66), age of high-risk detection (C-index 0.73 vs 0.52), and overall prediction (RMSE 1.1% vs 10.9%), with external validation. We also used MSGene to refine estimates of lifetime absolute risk reduction from statin initiation. Our findings underscore the potential public health value of our novel multistate model for accurate lifetime CAD risk estimation using clinical factors and increasingly available genetics.
目前，冠状动脉疾病（CAD）是全球成年人死亡的主要原因。准确的风险分层有助于实现最佳的终生预防。我们设计了一种新颖的通用多状态模型（MSGene），以估计跨越10种心脏代谢状态的特定年龄转变，该转变取决于临床协变量和CAD多基因风险评分。MSGene支持与这些状态中的任何一种相关的CAD预防决策。我们分析了来自480,638名英国生物银行参与者的纵向数据，并将预测的终生风险与30年弗雷明汉风险评分进行了比较。经外部验证，MSGene在辨别能力（C指数为0.71对0.66）、高危检测年龄（C指数为0.73对0.52）和总体预测（均方根误差为1.1%对10.9%）方面均有改善。我们还使用MSGene来完善对他汀类药物起始治疗后终生绝对风险降低的估计。我们的研究结果强调了我们新颖的多状态模型在利用临床因素和日益可用的遗传学进行准确的终生CAD风险估计方面的潜在公共卫生价值。
