IRF1 as a potential biomarker in Mycobacterium tuberculosis infection

Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456, GSE19491...

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Published inJournal of cellular and molecular medicine Vol. 25; no. 15; pp. 7270 - 7279
Main Authors Wu, Liwei, Cheng, Qiliang, Wen, Zilu, Song, Yanzheng, Zhu, Yijun, Wang, Lin
Format Journal Article
LanguageEnglish
Published England John Wiley & Sons, Inc 01.08.2021
John Wiley and Sons Inc
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Abstract Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456, GSE19491 and GSE50834 are blood microarray. The differential genes of GSE139825 and GSE83456 were 68 and 226, and intersection genes were 11. Gene ontology (GO) analyses of 11 intersection genes revealed that the changes were mostly enriched in regulation of leucocyte cell‐cell adhesion and regulation of T‐cell activation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs revealed that the host response in TB strongly involves cytokine‐cytokine receptor interactions and folate biosynthesis. In order to further narrow the range of biomarkers, we used protein‐protein interaction to establish a hub gene network of two data sets and a network of 11 candidate genes. Eventually, IRF1 was selected as a biomarker. As validation, IRF1 levels were shown to be up‐regulated in patients with TB relative to healthy controls in data sets GSE19491 and GSE50834. Additionally, IRF1 levels were measured in the new patient samples using ELISA. IRF1 was seen to be significantly up‐regulated in patients with TB compared with healthy controls with an AUC of 0.801. These results collectively indicate that IRF1 could serve as a new biomarker for the diagnosis of pulmonary tuberculosis.
AbstractList Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456 , GSE19491 and GSE50834 are blood microarray. The differential genes of GSE139825 and GSE83456 were 68 and 226, and intersection genes were 11. Gene ontology (GO) analyses of 11 intersection genes revealed that the changes were mostly enriched in regulation of leucocyte cell‐cell adhesion and regulation of T‐cell activation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs revealed that the host response in TB strongly involves cytokine‐cytokine receptor interactions and folate biosynthesis. In order to further narrow the range of biomarkers, we used protein‐protein interaction to establish a hub gene network of two data sets and a network of 11 candidate genes. Eventually, IRF1 was selected as a biomarker. As validation, IRF1 levels were shown to be up‐regulated in patients with TB relative to healthy controls in data sets GSE19491 and GSE50834 . Additionally, IRF1 levels were measured in the new patient samples using ELISA. IRF1 was seen to be significantly up‐regulated in patients with TB compared with healthy controls with an AUC of 0.801. These results collectively indicate that IRF1 could serve as a new biomarker for the diagnosis of pulmonary tuberculosis.
Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456, GSE19491 and GSE50834 are blood microarray. The differential genes of GSE139825 and GSE83456 were 68 and 226, and intersection genes were 11. Gene ontology (GO) analyses of 11 intersection genes revealed that the changes were mostly enriched in regulation of leucocyte cell‐cell adhesion and regulation of T‐cell activation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs revealed that the host response in TB strongly involves cytokine‐cytokine receptor interactions and folate biosynthesis. In order to further narrow the range of biomarkers, we used protein‐protein interaction to establish a hub gene network of two data sets and a network of 11 candidate genes. Eventually, IRF1 was selected as a biomarker. As validation, IRF1 levels were shown to be up‐regulated in patients with TB relative to healthy controls in data sets GSE19491 and GSE50834. Additionally, IRF1 levels were measured in the new patient samples using ELISA. IRF1 was seen to be significantly up‐regulated in patients with TB compared with healthy controls with an AUC of 0.801. These results collectively indicate that IRF1 could serve as a new biomarker for the diagnosis of pulmonary tuberculosis.
Author Wang, Lin
Song, Yanzheng
Wu, Liwei
Wen, Zilu
Zhu, Yijun
Cheng, Qiliang
AuthorAffiliation 3 Department of Scientific Research Shanghai Public Health Clinical Center Fudan University Shanghai China
4 TB Center Shanghai Emerging & Re‐emerging Infectious Diseases Institute Shanghai China
2 Department of Thoracic Surgery Tuberculosis Hospital of Shaanxi Province Xi’an China
1 Department of Thoracic Surgery Shanghai Public Health Clinical Center Fudan University Shanghai China
AuthorAffiliation_xml – name: 3 Department of Scientific Research Shanghai Public Health Clinical Center Fudan University Shanghai China
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CitedBy_id crossref_primary_10_1186_s13568_024_01691_7
crossref_primary_10_1021_acsinfecdis_4c00374
crossref_primary_10_3389_fcimb_2023_1255905
crossref_primary_10_3390_ijms25116255
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Issue 15
Keywords differentially expressed gene (DEG)
network analysis
protein interaction
biomarker
tuberculosis (TB)
protein
Language English
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Notes Funding information
This research was supported by a grant from the Thirteen‐Fifth Mega‐Scientific Project on “prevention and treatment of AIDS, viral hepatitis and other infectious diseases” (grant no. 2017ZX10201301‐003‐002)
Liwei Wu, Qiliang Chen and Zilu Wen are co‐first authors
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  doi: 10.1093/bioinformatics/btq675
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Snippet Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose...
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SubjectTerms biomarker
Biomarkers
Biomarkers - metabolism
Cell activation
Cell adhesion
Cell adhesion & migration
Cytokines
Cytokines - metabolism
differentially expressed gene (DEG)
DNA microarrays
Folic acid
Gene expression
Gene Regulatory Networks
Genomes
Health care
HIV
Human immunodeficiency virus
Humans
Infections
Interferon regulatory factor 1
Interferon Regulatory Factor-1 - genetics
Interferon Regulatory Factor-1 - metabolism
network analysis
Online data bases
Open source software
Original
protein
protein interaction
Protein Interaction Maps
Proteins
Public health
Statistical analysis
Transcription activation
Transcriptome
Tuberculosis
tuberculosis (TB)
Tuberculosis, Pulmonary - genetics
Tuberculosis, Pulmonary - metabolism
Tuberculosis, Pulmonary - pathology
Up-Regulation
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Title IRF1 as a potential biomarker in Mycobacterium tuberculosis infection
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fjcmm.16756
https://www.ncbi.nlm.nih.gov/pubmed/34213077
https://www.proquest.com/docview/2557758228
https://search.proquest.com/docview/2548416346
https://pubmed.ncbi.nlm.nih.gov/PMC8335664
Volume 25
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