A Novel Prognostic Biomarker with Potential of High Diagnostic Accuracy in Pulmonary Tuberculosis: An in silico Study
Background: Due to the fact that pulmonary tuberculosis (PTB) is a highly infectious disease characterized by high herd susceptibility and hard to be treated. Cytokines have a crucial role in eliciting protective and pathologic consequences in infectious diseases, including tuberculosis. This study aimed to investigate the gene expression dataset of tuberculosis patients to identify the novel cytokine biomarkers in pulmonary tuberculosis. Materials and Methods: The expression dataset (GSE19435) having comparative study of drug treatment at 0-month (control), 2-months and 12 months was retrieved from National Center for Biotechnology Information (NCBI) geo datasets for bioinformatic analysis. Differential gene expression (DEGs) analysis of immune-related genes with treatment progression was performed which was further followed by Protein-Protein Interaction (PPI) network construction. Further, functional enrichment and KEGG pathway enrichment analysis were also performed. Finally, Receiver-operating characteristic curves (ROC) analysis was performed for selected biomarkers. Results: A total of 210 differentially expressed genes (DEGs) were identified, out of which 59 were upregulated, while 151 were downregulated. Gene ontology results revealed that the deregulated genes were enriched in immune response-regulation, cytokine pathways, and response to the bacterium. Also, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that deregulated genes are involved in the fork head box transcription factors (FOXO) signaling pathway, oxidative phosphorylation, and osteoclast differentiation pathways. Based on the combined score and degree of connectedness, novel genes like amyloid-beta precursor protein (APP), Transmembrane Immune Signaling Adaptor (TYROBP), Annexin A2 (ANXA2), Proteasome 20S Subunit Beta 2 (PSMB2), CD58 Molecule (CD58) (upregulated genes), and Thyroid Hormone Receptor Interactor 12 (TRIP12), RNA Polymerase III Subunit A (POLR3A), Nuclear Factor of Activated T Cells 5 (NFAT5), DEADBox Helicase 17 (DDX17), DNA Topoisomerase III (TOP3A) (downregulated genes) were identified as hub genes of which TRIP12 and POLR3A are cytokines (type1) biomarkers. Further analysis through ROC divulged TRIP12 as a potential diagnostic biomarker. Conclusion: Overall findings revealed that TRIP12 is a novel cytokine biomarker in Mycobacterium tuberculosis-infected patients with the highest diagnostic accuracy.