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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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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. |
format | Online Article Text |
id | pubmed-7732298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
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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