GWAS summary-based pathway analysis correcting for the genetic confounding impact of environmental exposures

Abstract 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 analys...

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Veröffentlicht in:Briefings in bioinformatics 2018-09, Vol.19 (5), p.725-730
Hauptverfasser: Fan, Qianrui, Zhang, Feng, Wang, Wenyu, Xu, Jiawen, Hao, Jingcan, He, Awen, Wen, Yan, Li, Ping, Liang, Xiao, Du, Yanan, Liu, Li, Wu, Cuiyan, Wang, Sen, Wang, Xi, Ning, Yujie, Guo, Xiong
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Sprache:eng
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Zusammenfassung:Abstract 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.
ISSN:1467-5463
1477-4054
DOI:10.1093/bib/bbx025