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

Xue-Bing Qin,Lin Zou,Pei-Jia Huang,Bao-Jun Sun,Wei-Jue Zhang

doi:10.1186/s12879-016-1822-6

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.

Highlights

The study aimed to identify the potential biomarkers in pulmonary tuberculosis (TB) and TB latent infection based on bioinformatics analysis
Pollock et al [8] suggested that M. tuberculosis Rv1681 protein was a diagnostic marker of active pulmonary TB
Identification of differentially expressed genes (DEGs) Based on the thresholds of |log2-fold change (log2FC)| > 1.0 and FDR < 0.05, a total of 1084 DEGs were identified between pulmonary TB and TB latent infection samples, including 565 down-regulated genes and 519 up-regulated genes

Summary

Introduction

The study aimed to identify the potential biomarkers in pulmonary tuberculosis (TB) and TB latent infection based on bioinformatics analysis. Pulmonary tuberculosis (TB) is a widespread and fatal infectious disease. It is caused by various strains of mycobacteria, usually Mycobacterium tuberculosis [1]. Numerous studies have been done to investigate the potential biomarkers for the treatment of pulmonary TB. Pollock et al [8] suggested that M. tuberculosis Rv1681 protein was a diagnostic marker of active pulmonary TB. Chowdhury et al [9] reported that the serum interleukin (IL)-6 level of the active pulmonary TB patients following anti-tuberculosis drug therapy played an important role in immuneprotection of the host against M. tuberculosis infection. It is necessary to identify novel potential therapeutic biomarkers in pulmonary TB

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