GWAS summary-based pathway analysis correcting for the genetic confounding impact of environmental exposures
GWAS summary-based pathway analysis correcting for the genetic confounding impact of environmental exposures
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基于 GWAS 摘要的路径分析纠正了环境暴露的遗传混杂影响。
DOI：
10.1093/bib/bbx025
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发表时间：
2017
影响因子：
9.5
通讯作者：
Xiong Guo
中科院分区：
文献类型：
--
作者：
Fan Qianrui;Feng Zhang;Wenyu Wang;Jiawen Xu;Jincan Hao;Awen Xu;Yan Wen;Ping Li;Xiao Liang;Yanan Du;Li Liu;Cuiyan Wu;Sen Wang;Xi Wang;Yujie Ning;Xiong Guo
基于全基因组关联研究（GWAS）的通路关联分析是人类复杂疾病遗传学研究的有力手段。然而，环境胁迫相关基因的遗传混杂效应会降低基于GWAS的靶疾病通路关联分析的准确性。在这项研究中，我们开发了一种途径关联分析方法，命名为孟德尔随机化为基础的途径富集分析（MRPEA），这是能够纠正环境暴露的遗传混杂效应，使用GWAS环境暴露的汇总数据。在分析了心血管疾病和吸烟的真实的GWAS汇总数据后，我们观察到MRPEA的性能与传统的通路关联分析（TPAA）相比有显着提高，而无需调整环境暴露。此外，模拟研究发现，MRPEA一般优于TPAA在各种情况下。我们希望MRPEA可以帮助填补TPAA的差距，并确定复杂疾病的新的因果通路。
Genome-wide association study (GWAS)-based pathway association analysis is a powerful approach for the genetic studies of human complex diseases. However, the genetic confounding effects of environment exposure-related genes can decrease the accuracy of GWAS-based pathway association analysis of target diseases. In this study, we developed a pathway association analysis approach, named Mendelian randomization-based pathway enrichment analysis (MRPEA), which was capable of correcting the genetic confounding effects of environmental exposures, using the GWAS summary data of environmental exposures. After analyzing the real GWAS summary data of cardiovascular disease and cigarette smoking, we observed significantly improved performance of MRPEA compared with traditional pathway association analysis (TPAA) without adjusting for environmental exposures. Further, simulation studies found that MRPEA generally outperformed TPAA under various scenarios. We hope that MRPEA could help to fill the gap of TPAA and identify novel causal pathways for complex diseases.