ArticleBMC infectious diseases2016
Identification potential biomarkers in pulmonary tuberculosis and latent infection based on bioinformatics analysis.
Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 24 citations in OpenAlex.
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- Comprehensive Analysis Identifies COL1A1, COL3A1, and POSTN as Key Genes Associated with Brain Metastasis in Patients with Breast Cancer.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Identification of potential genes related to breast cancer brain metastasis in breast cancer patients.Bioscience reports · 2021Article
- Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients.International journal of environmental research and public health · 2020Article
- Gene network in pulmonary tuberculosis based on bioinformatic analysis.BMC infectious diseases · 2020Article
- BATF Potentially Mediates Negative Regulation of PD-1/PD-Ls Pathway on T Cell Functions inFrontiers in immunology · 2019Article
- The MICALs are a Family of F-actin Dismantling Oxidoreductases Conserved from Drosophila to Humans.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe study aimed to identify the potential biomarkers in pulmonary tuberculosis (TB) and TB latent infection based on bioinformatics analysis.
methodsThe microarray data of GSE57736 were downloaded from Gene Expression Omnibus database. A total of 7 pulmonary TB and 8 latent infection samples were used to identify the differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was constructed by Cytoscape software. Then network-based neighborhood scoring analysis was performed to identify the important genes. Furthermore, the functional enrichment analysis, correlation analysis and logistic regression analysis for the identified important genes were performed.
resultsA total of 1084 DEGs were identified, including 565 down- and 519 up-regulated genes. The PPI network was constructed with 446 nodes and 768 edges. Down-regulated genes RIC8 guanine nucleotide exchange factor A (RIC8A), basic leucine zipper transcription factor, ATF-like (BATF) and microtubule associated monooxygenase, calponin LIM domain containing 1 (MICAL1) and up-regulated genes ATPase, Na+/K+ transporting, alpha 4 polypeptide (ATP1A4), histone cluster 1, H3c (HIST1H3C), histone cluster 2, H3d (HIST2H3D), histone cluster 1, H3e (HIST1H3E) and tyrosine kinase 2 (TYK2) were selected as important genes in network-based neighborhood scoring analysis. The functional enrichment analysis results showed that these important DEGs were mainly enriched in regulation of osteoblast differentiation and nucleoside triphosphate biosynthetic process. The gene pairs RIC8A-ATP1A4, HIST1H3C-HIST2H3D, HIST1H3E-BATF and MICAL1-TYK2 were identified with high positive correlations. Besides, these genes were selected as significant feature genes in logistic regression analysis.
conclusionsThe genes such as RIC8A, ATP1A4, HIST1H3C, HIST2H3D, HIST1H3E, BATF, MICAL1 and TYK2 may be potential biomarkers in pulmonary TB or TB latent infection.
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