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Tuberculosis (TB) is the world's most prevalently infectious disease. Molecular mechanisms behind tuberculosis remain unknown. microRNA (miRNA) is involved in a wide variety of diseases. To validate the significant genes and miRNAs in the current sample, two messenger RNA (mRNA) expression profile datasets and three miRNA expression profile datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed (DE) genes (DEGs) and miRNAs (DE miRNAs) between healthy and TB patients were filtered out. Enrichment analysis was executed, and a protein-protein interaction (PPI) network was developed to understand the enrich pathways and hub genes of TB. Additionally, the target genes of miRNA were predicted and overlapping target genes were identified. We studied a total of 181 DEGs (135 downregulated and 46 upregulated genes) and two DE miRNAs (2 downregulated miRNAs) from two gene profile datasets and three miRNA profile datasets, respectively. 10 hub genes were defined based on high degree of connectivity. A PPI network's top module was constructed. The 23 DEGs identified have a significant relationship with miRNAs. 25 critically significant Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were discovered. The detailed study revealed that, in tuberculosis, the DE miRNA and DEGs form an interaction network. The identification of novel target genes and main pathways would aid with our understanding of miRNA's function in tuberculosis progression.

Selecting Hub Genes and Predicting Target Genes of microRNAs in Tuberculosis via the Bioinformatics Analysis