Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease.
Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease.
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DOI：
10.1186/s12916-022-02583-y
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发表时间：
2022-11-07
期刊：
影响因子：
9.3
通讯作者：
Wu, Chong
中科院分区：
文献类型：
--
作者：
King, Austin;Wu, Lang;Deng, Hong-Wen;Shen, Hui;Wu, Chong
多基因风险评分(PRSS)对于改善指南推荐的冠心病(CAD)预测临床风险模型的价值存在争议。在这里，我们检验了综合的多基因风险评分是否改善了合并队列方程以外的冠心病预测。在2006年至2010年登记的291,305名无关的英国白人英国生物库参与者中进行了一项观察研究。9499例冠心病流行病例的病例对照样本和相同数量的随机选择的对照被用来调整和整合多基因风险分数。一个272,307人的单独队列(对2020年的随访)被用来检查合并队列方程、综合多基因风险评分和PRS增强的合并队列方程对发生CAD病例的风险预测性能。通过使用7.5%的阈值进行区分和风险重新分类来分析每个模型的性能。在用于分析预测准确性的272,307人(平均年龄，56.7岁)的队列中，在12年的随访期内有7036例CAD事件。对综合多基因风险评分、合并队列方程和PRS增强合并队列方程进行模型判别，报告的C统计量分别为0.640(95%CI，0.634-0.646)、0.718(95%CI，0.713-0.723)和0.753(95%CI，0.748-0.758)。在合并队列方程中以7.5%的风险阈值添加综合多基因风险评分后，病例的风险重新分类净改善0.117(95%CI，0.102至0.129)，非病例的 − 0.023(95%CI， − 0.025至 − 0.022)[总体：0.093(95%CI，0.08至0.104)]。对于事故CAD案例，这意味着正确地重新分类到高风险类别的比例为14.2%，错误地重新分类到低风险类别的比例为2.6%。将CAD的综合多基因风险评分添加到汇集的队列问题中，提高了英国生物库白种人对事件CAD和临床风险分类的预测准确性。这些发现表明，综合的多基因风险评分可能会增强英国白人人群中的冠心病风险预测和筛查。网上版载有补充材料，可在10.1186/s12916-022-02583-y查阅。
The value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case–control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold. In the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634–0.646), 0.718 (95% CI, 0.713–0.723), and 0.753 (95% CI, 0.748–0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and − 0.023 (95% CI, − 0.025 to − 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category. Addition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population. The online version contains supplementary material available at 10.1186/s12916-022-02583-y.
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影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
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Marchini J
影响因子：
5
作者：
Fry A;Littlejohns TJ;Sudlow C;Doherty N;Adamska L;Sprosen T;Collins R;Allen NE
通讯作者：
Allen NE
影响因子：
16.6
作者：
Duncan, L.;Shen, H.;Domingue, B.
通讯作者：
Domingue, B.
影响因子：
24
作者：
Aragam, Krishna G.;Dobbyn, Amanda;Natarajan, Pradeep
通讯作者：
Natarajan, Pradeep
影响因子：
105.7
作者：
Hippisley-Cox, Julia;Coupland, Carol;Brindle, Peter
通讯作者：
Brindle, Peter