...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Molecular Epidemiology and Genetics >Evaluation of genetic risk scores for prediction of dichotomous outcomes
【24h】

Evaluation of genetic risk scores for prediction of dichotomous outcomes

机译：评估遗传风险评分以预测二分结果

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Substantial uncertainty exists as to whether combining multiple disease-associated single nucleotide polymorphisms (SNPs) into a genotype risk score (GRS) can improve the ability to predict the risk of disease in a clinically relevant way. We calculated the ability of a simple count GRS to predict the risk of a dichotomous outcome under both multiplicative and additive models of combined effects. We then compared the results of these simulations with the observed results of published GRS measured within multiple epidemiologic cohorts. If the combined effect of each disease-associated SNP included in a GRS is multiplicative on the risk scale, then a count GRS score should be useful for risk prediction with as few as 10-20 SNPs. Adding additional SNPs to the GRS under this model dramatically improves risk prediction. By contrast, if the combined effect of each SNP included in a GRS is linearly additive on the risk scale, a simple count GRS is unlikely to provide clinically useful risk prediction. Adding additional SNPs to the GRS under this model does not improve risk prediction. The combined effect of SNPs included in several published GRS measured in several well-phenotyped epidemiologic cohort studies appears to be more consistent with a linearly additive effect. A simple count GRS is unlikely to be clinically useful for predicting the risk of a dichotomous outcome. Alternative methods for constructing GRS that attempt to identify and include SNPs that demonstrate multiplicative gene-gene or gene-environment interactive effects are needed.
机译：关于将多种疾病相关的单核苷酸多态性（SNP）组合到基因型风险评分（GRS）中是否可以提高以临床相关方式预测疾病风险的能力，存在很大的不确定性。我们计算了简单计数GRS在组合效应的相乘模型和相加模型下预测二分结果风险的能力。然后，我们将这些模拟结果与已在多个流行病学队列中测量的已发表GRS的观察结果进行了比较。如果GRS中包含的每种与疾病相关的SNP的综合作用在风险量表上成倍增加，则GRS计数计数对于少至10-20个SNP的风险预测应该是有用的。在此模型下，向GRS添加其他SNP可以大大改善风险预测。相比之下，如果GRS中包含的每个SNP的综合作用在风险量表上呈线性加和，则简单计数的GRS不太可能提供临床上有用的风险预测。在此模型下，向GRS添加其他SNP不会改善风险预测。在几项表型良好的流行病学队列研究中测得的几项已发表的GRS中所包含的SNP的综合作用似乎与线性加和效应更为一致。简单计数的GRS不太可能在临床上预测二分结果的风险。需要构建GRS的替代方法，该方法试图鉴定并包括SNP，这些SNP表现出倍增的基因-基因或基因-环境相互作用效应。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号