Identification potential biomarkers in pulmonary tuberculosis and latent infection based on bioinformatics analysis

BMC Infectious Diseases

Research Article

Wei-Jue Zhang¹  Lin Zou²  Xue-Bing Qin³  Bao-Jun Sun³  Pei-Jia Huang³ 

[1] Department of Respiratory, Chinese PLA General Hospital, 100853, Beijing, China;Medical College, Nankai University, 300071, Tianjin, China;Nanlou Health Care Department, Chinese PLA General Hospital, 100853, Beijing, China;Nanlou Respiratory Diseases Department, Chinese PLA General Hospital, No. 28, Fuxing Road, 100853, Beijing, China;

关键词: Pulmonary tuberculosis;    Mycobacterium tuberculosis;    Bioinformatics analysis;    Differentially expressed genes;    Biomarker;   

DOI  :  10.1186/s12879-016-1822-6

 received in 2015-07-08, accepted in 2016-09-09,  发布年份 2016

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© The Author(s). 2016