A novel method to test associations between a weighted combination of phenotypes and genetic variants.
A novel method to test associations between a weighted combination of phenotypes and genetic variants.
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DOI：
10.1371/journal.pone.0190788
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Sha Q
中科院分区：
文献类型：
--
作者：
Zhu H;Zhang S;Sha Q
许多复杂的疾病，如糖尿病、高血压、代谢综合征等，都是通过多种相关表型来衡量的。然而，大多数全基因组关联研究（GWAS）集中于一种感兴趣的表型或单独研究多种表型，以识别与复杂疾病相关的遗传变异。单独分析一种表型或相关表型可能会因为忽略了通过组合表型获得的信息（例如表型之间的相关性）而失去功效。为了提高检测与复杂疾病相关的遗传变异的统计能力，我们开发了一种新方法来测试多种表型的加权组合（WCmulP）。我们进行了广泛的模拟研究以及真实数据（COPDGene）分析来评估所提出方法的性能。我们的模拟结果表明，WCmulP 具有正确的 I 类错误率，并且是我们比较的方法中最强大的测试或可与最强大的测试相媲美的。 WCmulP 在识别与 COPD 相关表型相关的单核苷酸多态性 (SNP) 方面也具有出色的性能。
Many complex diseases like diabetes, hypertension, metabolic syndrome, et cetera, are measured by multiple correlated phenotypes. However, most genome-wide association studies (GWAS) focus on one phenotype of interest or study multiple phenotypes separately for identifying genetic variants associated with complex diseases. Analyzing one phenotype or the related phenotypes separately may lose power due to ignoring the information obtained by combining phenotypes, such as the correlation between phenotypes. In order to increase statistical power to detect genetic variants associated with complex diseases, we develop a novel method to test a weighted combination of multiple phenotypes (WCmulP). We perform extensive simulation studies as well as real data (COPDGene) analysis to evaluate the performance of the proposed method. Our simulation results show that WCmulP has correct type I error rates and is either the most powerful test or comparable to the most powerful test among the methods we compared. WCmulP also has an outstanding performance for identifying single-nucleotide polymorphisms (SNPs) associated with COPD-related phenotypes.
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