Tuberculosis (TB) is one of the deadliest diseases since ancient times and is still a global health problem. So, there is a need to develop new approaches for early detection of TB and understand the host-pathogen relationship. In the present study, we have analyzed microarray data sets and compared the transcriptome profiling of the healthy individual with latent infection (LTBI) and active TB (TB) patients, and identified the differentially expressed genes (DEGs). Next, we performed the systematic network meta-analysis of the DEGs, which identified the seven most influencing hub genes (IL6, IL1B, TNF, NFKB1, STAT1, JAK2, and MAPK8) as the potential therapeutic target in the tuberculosis disease. These target genes are involved in many biological processes like cell cycle control, apoptosis, complement signalling, enhanced cytokine & chemokine signalling, pro-inflammatory responses, and host immune responses. Additionally, we also identified 22 inferred genes that are mainly engaged in the induction of innate immune response, cellular response to interleukin-6, inflammatory response, apoptotic process, I-kappaB-phosphorylation, JAK-STAT signalling pathway, macrophage activation, cell growth, and cell signalling. The proper attention of these inferred genes may open up a new horizon to understand the defensive mechanisms of TB disease. The transcriptome profiling and network approach can enhance the understanding of the molecular pathogenesis of tuberculosis infection and have implications for the plan and execution of mRNA expression tools to support early diagnostics and treatment of Mycobacterium tuberculosis (M.tb).
Keywords: Differentially expressed genes (DEGs); Gene-interaction network; KEGG pathway; Mycobacterium tuberculosis; Network centrality.
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