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pmid:32987825

Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients.

Longxiang Xie · Xiaoyu Chao · Tieshan Teng · Qiming Li · Jianping Xie

International journal of environmental research and public health · 2020 doi:10.3390/ijerph17196993

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:32987825
kind
science-record
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sha256:81a7b506d5d7caeb6a03a2fcdcaa617f29c8680c58e5e68a1ee0459b5f44405e
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
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2026-11-01T15:41:11Z
updated_at
2026-11-01T22:02:15Z
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paper object · 10 fields
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title
Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients.
doi
10.3390/ijerph17196993
pmid
32987825
authors array · 5 items
[0]
Longxiang Xie
[1]
Xiaoyu Chao
[2]
Tieshan Teng
[3]
Qiming Li
[4]
Jianping Xie
journal
International journal of environmental research and public health
year
2020
abstract
Tuberculosis (TB), one major threat to humans, can infect one third of the worldwide population, and cause more than one million deaths each year. This study aimed to identify the effective diagnosis and therapy biomarkers of TB. Hence, we analyzed two microarray datasets (GSE54992 and GSE62525) derived from the Gene Expression Omnibus (GEO) database to find the differentially expressed genes (DEGs) of peripheral blood mononuclear cell (PBMC) between TB patients and healthy specimens. Functional and pathway enrichment of the DEGs were analyzed by Metascape database. Protein-protein interaction (PPI) network among the DEGs were constructed by STRING databases and visualized in Cytoscape software. The related transcription factors regulatory network of the DEGs was also constructed. A total of 190 DEGs including 36 up-regulated genes and 154 down-regulated genes were obtained in TB samples. Gene functional enrichment analysis showed that these DEGs were enriched in T cell activation, chemotaxis, leukocyte activation involved in immune response, cytokine secretion, head development, etc. The top six hub genes (namely, LRRK2, FYN, GART, CCR7, CXCR5, and FASLG) and two significant modules were got from PPI network of DEGs. Vital transcriptional factors, such as FoxC1 and GATA2, were discovered with close interaction with these six hub DEGs. By systemic bioinformatic analysis, many DEGs associated with TB were screened, and these identified hub DEGs may be potential biomarkers for diagnosis and treatment of TB in the future.
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The interactive web tool GEO2R was used to analyze the gene expression data of microarrays and find DEGs [17].
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sections[4] "2.2. Data Processing" paragraph 2
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The interactive web tool GEO2R was used to analyze the gene expression data of microarrays and find DEGs [17].
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sections[16] "ack" paragraph 1
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The data used to support the findings of this study are included within the article.
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Gene expression profiles of caseous human pulmonary TB granulomas derived from TB patients
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GSM1327564
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570
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Homo sapiens
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Expression data from peripheral blood
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2026-11-01T15:39:54Z
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GSM1378196
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GSM1378197
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GSM1378199
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GSM1378200
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GSM1378201
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GSM1378202
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GSM1378203
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GSM1378204
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GSM1378205
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6887
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Mus musculus
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Genome-wide analysis of gene expression in lung cells from metformin treated Mycobacterium tuberculosis infected mice
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2026-11-01T15:39:54Z
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GSM1528339
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GSM1528340
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GSM1528341
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GSM1528342
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GSM1528343
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GSM1528344
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GSM1528345
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GSM1528346
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GSM1528347
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GSM1528370
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GSM1528371
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GSM1528372
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GSM1528373
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GSM1528374
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GSM1528375
[40]
GSM1528376
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GSM1528377
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42
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16951
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Homo sapiens
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Gene expression profiling identifies candidate biomarkers for active and latent tuberculosis
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2026-11-01T15:39:55Z
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identifier_resolution_only_no_download_no_licence_read
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null
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The data used to support the findings of this study are included within the article.
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The data used to support the findings of this study are included within the article.
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10558
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Comparative analysis of monocytes from healthy donors, patients with metastatic breast cancer, sepsis or tuberculosis.
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2026-11-01T15:39:55Z
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apy biomarkers of TB. Hence, we analyzed two microarray datasets (GSE54992 and GSE62525) derived fro
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ication of DEGs in PBMC from TB Patients Two microarray datasets including GSE54992 and GSE62525 wer
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consumes_earlier_output
id
assay:2
Complete file
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This study aimed to identify the effective diagnosis and therapy biomarkers of TB. Hence, we analyzed two microarray datasets (GSE54992 and GSE62525) derived from the Gene Expression Omnibus (GEO) database to find the differentially expressed genes (DEGs) of peripheral blood mononuclear cell (PBMC) between TB patients and healthy specimens. Functional and pathway enrichment of the DEGs were analyzed by Metascape database. Protein-protein interaction (PPI) network among the DEGs were constructed by STRING databases and visualized in Cytoscape software. The related transcription factors regulatory network of the DEGs was also constructed. A total of 190 DEGs including 36 up-regulated genes and 154 down-regulated genes were obtained in TB samples. Gene functional enrichment analysis showed that these DEGs were enriched in T cell activation, chemotaxis, leukocyte activation involved in immune response, cytokine secretion, head development, etc. The top six hub genes (namely, LRRK2, FYN, GART, CCR7, CXCR5, and FASLG) and two significant modules were got from PPI network of DEGs. Vital transcriptional factors, such as FoxC1 and GATA2, were discovered with close interaction with these six hub DEGs. By systemic bioinformatic analysis, many DEGs associated with TB were screened, and these identified hub DEGs may be potential biomarkers for diagnosis and treatment of TB in the future.", "claims": [{"id": "claim-method", "statement": "The interactive web tool GEO2R was used to analyze the gene expression data of microarrays and find DEGs [17].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32987825", "locator": "sections[4] \"2.2. 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