简单、标准化地将遗传风险纳入复杂性状的非遗传风险预测工具中：以冠心病为例。
Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example.
机构信息
Department of Medicine, Stanford University School of Medicine Stanford, CA, USA.
Department of Medicine, Stanford University School of Medicine Stanford, CA, USA ; Department of Health Research and Policy, Stanford University School of Medicine Stanford, CA, USA ; Department of Statistics, Stanford University School of Humanities and Sciences Stanford, CA, USA.
出版信息
Front Genet. 2014 Aug 1;5:254. doi: 10.3389/fgene.2014.00254. eCollection 2014.
PURPOSE
Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.
MATERIALS AND METHODS
We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.
RESULTS
The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. RESULTS are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider.
CONCLUSION
The proposed method facilitates the standardized incorporation of a GRS in risk assessment.
目的
遗传风险评估正成为临床决策的重要组成部分。遗传风险评分（GRS）允许对复杂特征的遗传风险进行综合评估。一个在技术和临床方面都很重要的问题是如何最轻松有效地将 GRS 与基于已确立的非遗传风险因素的临床风险评估相结合，并将此信息清晰地呈现给患者和医疗保健提供者。
材料和方法
我们使用对数链接函数说明了一种将 GRS 与独立的临床风险评估相结合的方法。我们将该方法应用于社区动脉粥样硬化风险研究（ARIC）队列中冠心病（CHD）的预测。我们根据效果变化、区分度和校准度的度量标准评估了不同的构建方法。
结果
在临床风险评分（CRS）中加入 GRS 可提高 ARIC 中 CHD 的区分度和校准度。结果是相似的，无论 CRS 是使用外部还是内部系数、GRS 中是否包含风险因素单核苷酸多态性（SNP）或基线时有糖尿病的患者是否被排除在外。我们概述了如何使用我们的方法报告 GRS 的构建和性能，并说明了向受试者及其医疗保健提供者呈现遗传风险信息的一种方法。
结论
所提出的方法有助于在风险评估中标准化地纳入 GRS。
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