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Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets

More than 10 GWASs have reported numerous genetic loci associated with tuberculosis (TB). However, the functional effects of genetic variants on TB remains largely unknown. In the present study, by combining a reported GWAS summary dataset (N = 452,264) with 3 independent eQTL datasets (N = 2,242) a...

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Autores principales: Xu, Mengqiu, Li, Jingjing, Xiao, Zhaoying, Lou, Jiongpo, Pan, Xinrong, Ma, Yunlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732298/
https://www.ncbi.nlm.nih.gov/pubmed/33051402
http://dx.doi.org/10.18632/aging.103744
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author Xu, Mengqiu
Li, Jingjing
Xiao, Zhaoying
Lou, Jiongpo
Pan, Xinrong
Ma, Yunlong
author_facet Xu, Mengqiu
Li, Jingjing
Xiao, Zhaoying
Lou, Jiongpo
Pan, Xinrong
Ma, Yunlong
author_sort Xu, Mengqiu
collection PubMed
description More than 10 GWASs have reported numerous genetic loci associated with tuberculosis (TB). However, the functional effects of genetic variants on TB remains largely unknown. In the present study, by combining a reported GWAS summary dataset (N = 452,264) with 3 independent eQTL datasets (N = 2,242) and other omics datasets downloaded from public databases, we conducted an integrative genomics analysis to highlight SNPs and genes implicated in TB risk. Based on independent biological and technical validations, we prioritized 26 candidate genes with eSNPs significantly associated with gene expression and TB susceptibility simultaneously; such as, CDC16 (rs7987202, rs9590408, and rs948182) and RCN3 (rs2946863, rs2878342, and rs3810194). Based on the network-based enrichment analysis, we found these 26 highlighted genes were jointly connected to exert effects on TB susceptibility. The co-expression patterns among these 26 genes were remarkably changed according to Mycobacterium tuberculosis (MTB) infection status. Based on 4 independent gene expression datasets, 21 of 26 genes (80.77%) showed significantly differential expressions between TB group and control group in mesenchymal stem cells, mice blood and lung tissues, as well as human alveolar macrophages. Together, we provide robust evidence to support 26 highlighted genes as important candidates for TB.
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spelling pubmed-77322982020-12-18 Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets Xu, Mengqiu Li, Jingjing Xiao, Zhaoying Lou, Jiongpo Pan, Xinrong Ma, Yunlong Aging (Albany NY) Research Paper More than 10 GWASs have reported numerous genetic loci associated with tuberculosis (TB). However, the functional effects of genetic variants on TB remains largely unknown. In the present study, by combining a reported GWAS summary dataset (N = 452,264) with 3 independent eQTL datasets (N = 2,242) and other omics datasets downloaded from public databases, we conducted an integrative genomics analysis to highlight SNPs and genes implicated in TB risk. Based on independent biological and technical validations, we prioritized 26 candidate genes with eSNPs significantly associated with gene expression and TB susceptibility simultaneously; such as, CDC16 (rs7987202, rs9590408, and rs948182) and RCN3 (rs2946863, rs2878342, and rs3810194). Based on the network-based enrichment analysis, we found these 26 highlighted genes were jointly connected to exert effects on TB susceptibility. The co-expression patterns among these 26 genes were remarkably changed according to Mycobacterium tuberculosis (MTB) infection status. Based on 4 independent gene expression datasets, 21 of 26 genes (80.77%) showed significantly differential expressions between TB group and control group in mesenchymal stem cells, mice blood and lung tissues, as well as human alveolar macrophages. Together, we provide robust evidence to support 26 highlighted genes as important candidates for TB. Impact Journals 2020-10-13 /pmc/articles/PMC7732298/ /pubmed/33051402 http://dx.doi.org/10.18632/aging.103744 Text en Copyright: © 2020 Xu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Xu, Mengqiu
Li, Jingjing
Xiao, Zhaoying
Lou, Jiongpo
Pan, Xinrong
Ma, Yunlong
Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets
title Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets
title_full Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets
title_fullStr Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets
title_full_unstemmed Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets
title_short Integrative genomics analysis identifies promising SNPs and genes implicated in tuberculosis risk based on multiple omics datasets
title_sort integrative genomics analysis identifies promising snps and genes implicated in tuberculosis risk based on multiple omics datasets
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732298/
https://www.ncbi.nlm.nih.gov/pubmed/33051402
http://dx.doi.org/10.18632/aging.103744
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