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遗传易感性与冠状动脉疾病的相关性预测复发事件:一项中国前瞻性队列研究。

Genetic predisposition to coronary artery disease is predictive of recurrent events: a Chinese prospective cohort study.

机构信息

Department of Cardiology, Peking University First Hospital, Beijing 100034, China.

Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.

出版信息

Hum Mol Genet. 2020 Apr 15;29(6):1044-1053. doi: 10.1093/hmg/ddaa025.

Abstract

Evidence of the effects of genetic risk score (GRS) on secondary prevention is scarce and mixed. We investigated whether coronary artery disease (CAD) susceptible loci can be used to predict the risk of major adverse cardiovascular events (MACEs) in a cohort with acute coronary syndromes (ACSs). A total of 1667 patients hospitalized with ACS were enrolled and prospectively followed for a median of 2 years. We constructed a weighted GRS comprising 79 CAD risk variants and investigated the association between GRS and MACE using a multivariable cox proportional hazard regression model. The incremental value of adding GRS into the prediction model was assessed by integrated discrimination improvement (IDI) and decision curve analysis (DCA). In the age- and sex-adjusted model, each increase in standard deviation in the GRS was associated with a 33% increased risk of MACE (hazard ratio: 1.33; 95% confidence interval: 1.10-1.61; P = 0.003), with this association not attenuating after further adjustment for traditional cardiovascular risk factors. The addition of GRS to a prediction model of seven clinical risk factors and EPICOR prognostic model slightly improved risk stratification for MACE as calculated by IDI (+1.7%, P = 0.006; +0.3%, P = 0.024, respectively). DCA demonstrated positive net benefits by adding GRS to other models. GRS was associated with MACE after multivariable adjustment in a cohort comprising Chinese ACS patients. Future studies are needed to validate our results and further evaluate the predictive value of GRS in secondary prevention.

摘要

遗传风险评分 (GRS) 对二级预防效果的证据稀缺且混杂。我们研究了冠心病 (CAD) 易感基因座是否可用于预测急性冠脉综合征 (ACS) 患者的主要不良心血管事件 (MACE) 风险。共纳入 1667 例因 ACS 住院的患者,前瞻性随访中位数为 2 年。我们构建了一个包含 79 个 CAD 风险变异的加权 GRS,并使用多变量 Cox 比例风险回归模型研究了 GRS 与 MACE 之间的关系。通过综合判别改善 (IDI) 和决策曲线分析 (DCA) 评估了将 GRS 加入预测模型的增量价值。在年龄和性别调整模型中,GRS 每增加一个标准差,MACE 的风险增加 33%(风险比:1.33;95%置信区间:1.10-1.61;P=0.003),进一步调整传统心血管危险因素后,这种关联并未减弱。将 GRS 添加到七个临床危险因素和 EPICOR 预后模型的预测模型中,IDl(增加 1.7%,P=0.006;增加 0.3%,P=0.024)和 DCA(增加 0.3%,P=0.024)均略微改善了 MACE 的风险分层。DCA 表明,将 GRS 添加到其他模型中可获得净获益。在中国 ACS 患者队列中,经过多变量调整后,GRS 与 MACE 相关。需要进一步的研究来验证我们的结果,并进一步评估 GRS 在二级预防中的预测价值。

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