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

Author

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  • Longxiang Xie

    (Cell Signal Transduction Laboratory, Bioinformatics Center, Department of Pathology, Institute of Biomedical Informatics, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China)

  • Xiaoyu Chao

    (Cell Signal Transduction Laboratory, Bioinformatics Center, Department of Pathology, Institute of Biomedical Informatics, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China)

  • Tieshan Teng

    (Cell Signal Transduction Laboratory, Bioinformatics Center, Department of Pathology, Institute of Biomedical Informatics, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China)

  • Qiming Li

    (Cell Signal Transduction Laboratory, Bioinformatics Center, Department of Pathology, Institute of Biomedical Informatics, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China)

  • Jianping Xie

    (State Key Laboratory Breeding Base of Eco-Environment and Bio-Resource of the Three Gorges Area, Key Laboratory of Eco-Environments in Three Gorges Reservoir Region, Institute of Modern Biopharmaceuticals, Ministry of Education, School of Life Sciences, Southwest University, Beibei, Chongqing 400715, China)

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.

Suggested Citation

  • Longxiang Xie & Xiaoyu Chao & Tieshan Teng & Qiming Li & Jianping Xie, 2020. "Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients," IJERPH, MDPI, vol. 17(19), pages 1-11, September.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:19:p:6993-:d:418756
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    References listed on IDEAS

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    1. Yingyao Zhou & Bin Zhou & Lars Pache & Max Chang & Alireza Hadj Khodabakhshi & Olga Tanaseichuk & Christopher Benner & Sumit K. Chanda, 2019. "Metascape provides a biologist-oriented resource for the analysis of systems-level datasets," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
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