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Comprehensive analyses of potential key genes in active tuberculosis: A systematic review
BACKGROUND: Tuberculosis (TB) is a global health problem that brings us numerous difficulties. Diverse genetic factors play a significant role in the progress of TB disease. However, still no key genes for TB susceptibility have been reported. This study aimed to identify the key genes of TB through...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322549/ https://www.ncbi.nlm.nih.gov/pubmed/34397688 http://dx.doi.org/10.1097/MD.0000000000026582 |
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author | Chen, Jiarui Liu, Chong Liang, Tuo Xu, Guoyong Zhang, Zide Lu, Zhaojun Jiang, Jie Chen, Tianyou Li, Hao Huang, Shengsheng Chen, Liyi Sun, Xihua Cen, Jiemei Zhan, Xinli |
author_facet | Chen, Jiarui Liu, Chong Liang, Tuo Xu, Guoyong Zhang, Zide Lu, Zhaojun Jiang, Jie Chen, Tianyou Li, Hao Huang, Shengsheng Chen, Liyi Sun, Xihua Cen, Jiemei Zhan, Xinli |
author_sort | Chen, Jiarui |
collection | PubMed |
description | BACKGROUND: Tuberculosis (TB) is a global health problem that brings us numerous difficulties. Diverse genetic factors play a significant role in the progress of TB disease. However, still no key genes for TB susceptibility have been reported. This study aimed to identify the key genes of TB through comprehensive bioinformatics analysis. METHODS: The series microarray datasets from the gene expression omnibus (GEO) database were analyzed. We used the online tool GEO2R to filtrate differentially expressed genes (DEGs) between TB and health control. Database for annotation can complete gene ontology function analysis as well as Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein-protein interaction (PPI) networks of DEGs were established by STRING online tool and visualized by Cytoscape software. Molecular Complex Detection can complete the analysis of modules in the PPI networks. Finally, the significant hub genes were confirmed by plug-in Genemania of Cytoscape, and verified by the verification cohort and protein test. RESULTS: There are a total of 143 genes were confirmed as DEGs, containing 48 up-regulated genes and 50 down-regulated genes. The gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis show that upregulated DEGs were associated with cancer and phylogenetic, whereas downregulated DEGs mainly concentrate on inflammatory immunity. PPI networks show that signal transducer and activator of transcription 1 (STAT1), guanylate binding protein 5 (GBP5), 2′-5′-oligoadenylate synthetase 1 (OAS1), catenin beta 1 (CTNNB1), and guanylate binding protein 1 (GBP1) were identified as significantly different hub genes. CONCLUSION: We conclude that these genes, including TAT1, GBP5, OAS1, CTNNB1, GBP1 are a candidate as potential core genes in TB and treatment of TB in the future. |
format | Online Article Text |
id | pubmed-8322549 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-83225492021-08-02 Comprehensive analyses of potential key genes in active tuberculosis: A systematic review Chen, Jiarui Liu, Chong Liang, Tuo Xu, Guoyong Zhang, Zide Lu, Zhaojun Jiang, Jie Chen, Tianyou Li, Hao Huang, Shengsheng Chen, Liyi Sun, Xihua Cen, Jiemei Zhan, Xinli Medicine (Baltimore) 3500 BACKGROUND: Tuberculosis (TB) is a global health problem that brings us numerous difficulties. Diverse genetic factors play a significant role in the progress of TB disease. However, still no key genes for TB susceptibility have been reported. This study aimed to identify the key genes of TB through comprehensive bioinformatics analysis. METHODS: The series microarray datasets from the gene expression omnibus (GEO) database were analyzed. We used the online tool GEO2R to filtrate differentially expressed genes (DEGs) between TB and health control. Database for annotation can complete gene ontology function analysis as well as Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein-protein interaction (PPI) networks of DEGs were established by STRING online tool and visualized by Cytoscape software. Molecular Complex Detection can complete the analysis of modules in the PPI networks. Finally, the significant hub genes were confirmed by plug-in Genemania of Cytoscape, and verified by the verification cohort and protein test. RESULTS: There are a total of 143 genes were confirmed as DEGs, containing 48 up-regulated genes and 50 down-regulated genes. The gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis show that upregulated DEGs were associated with cancer and phylogenetic, whereas downregulated DEGs mainly concentrate on inflammatory immunity. PPI networks show that signal transducer and activator of transcription 1 (STAT1), guanylate binding protein 5 (GBP5), 2′-5′-oligoadenylate synthetase 1 (OAS1), catenin beta 1 (CTNNB1), and guanylate binding protein 1 (GBP1) were identified as significantly different hub genes. CONCLUSION: We conclude that these genes, including TAT1, GBP5, OAS1, CTNNB1, GBP1 are a candidate as potential core genes in TB and treatment of TB in the future. Lippincott Williams & Wilkins 2021-07-30 /pmc/articles/PMC8322549/ /pubmed/34397688 http://dx.doi.org/10.1097/MD.0000000000026582 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | 3500 Chen, Jiarui Liu, Chong Liang, Tuo Xu, Guoyong Zhang, Zide Lu, Zhaojun Jiang, Jie Chen, Tianyou Li, Hao Huang, Shengsheng Chen, Liyi Sun, Xihua Cen, Jiemei Zhan, Xinli Comprehensive analyses of potential key genes in active tuberculosis: A systematic review |
title | Comprehensive analyses of potential key genes in active tuberculosis: A systematic review |
title_full | Comprehensive analyses of potential key genes in active tuberculosis: A systematic review |
title_fullStr | Comprehensive analyses of potential key genes in active tuberculosis: A systematic review |
title_full_unstemmed | Comprehensive analyses of potential key genes in active tuberculosis: A systematic review |
title_short | Comprehensive analyses of potential key genes in active tuberculosis: A systematic review |
title_sort | comprehensive analyses of potential key genes in active tuberculosis: a systematic review |
topic | 3500 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322549/ https://www.ncbi.nlm.nih.gov/pubmed/34397688 http://dx.doi.org/10.1097/MD.0000000000026582 |
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