Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks

Abstract Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be bi...

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Main Authors: Huiying Zhao, Dale R. Nyholt, Yuanhao Yang, Jihua Wang, Yuedong Yang
Format: Article
Language:English
Published: Nature Portfolio 2017-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-017-03826-2
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author Huiying Zhao
Dale R. Nyholt
Yuanhao Yang
Jihua Wang
Yuedong Yang
author_facet Huiying Zhao
Dale R. Nyholt
Yuanhao Yang
Jihua Wang
Yuedong Yang
author_sort Huiying Zhao
collection DOAJ
description Abstract Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path .
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spelling doaj.art-fcd910eb80374dde9d35755bc772fbc62022-12-21T20:35:44ZengNature PortfolioScientific Reports2045-23222017-06-01711810.1038/s41598-017-03826-2Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocksHuiying Zhao0Dale R. Nyholt1Yuanhao Yang2Jihua Wang3Yuedong Yang4Institute of Health and Biomedical Innovation, Queensland University of TechnologyInstitute of Health and Biomedical Innovation, Queensland University of TechnologyInstitute of Health and Biomedical Innovation, Queensland University of TechnologyShandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Dezhou UniversityInstitute for Glycomics, Griffith University, Parkland DrAbstract Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path .https://doi.org/10.1038/s41598-017-03826-2
spellingShingle Huiying Zhao
Dale R. Nyholt
Yuanhao Yang
Jihua Wang
Yuedong Yang
Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks
Scientific Reports
title Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks
title_full Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks
title_fullStr Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks
title_full_unstemmed Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks
title_short Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks
title_sort improving the detection of pathways in genome wide association studies by combined effects of snps from linkage disequilibrium blocks
url https://doi.org/10.1038/s41598-017-03826-2
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AT yuanhaoyang improvingthedetectionofpathwaysingenomewideassociationstudiesbycombinedeffectsofsnpsfromlinkagedisequilibriumblocks
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