Identification of overlapping molecular mechanisms in tuberculosis and sarcoidosis: A bioinformatics approach

Abstract

Background

Tuberculosis (TB) and sarcoidosis are chronic granulomatous diseases sharing similar symptoms, immune responses, and radiological characteristics. Transcriptome analysis offers insights into gene expression, regulation, and cellular processes, facilitating the understanding of shared molecular mechanisms.

Methods

Microarray datasets from the NCBI Gene Expression Omnibus (NCBI-GEO) were analysed to identify differentially expressed genes (DEGs) in TB and sarcoidosis compared to controls. DEGs were identified using the GEO2R tool, and subsequent functional enrichment analysis was conducted using EnrichR. Protein-protein interaction (PPI) networks, as well as gene-miRNA and transcription factor-DEG interaction networks, were constructed. In addition, pathway analysis and molecular docking of target proteins were conducted to further elucidate the biological mechanisms involved in both diseases.

Results

Fifteen genes, including ANKRD22, BATF2, DHRS9, EPSTI1, ETV7, FCGR1A, FCGR1B, GBP1, GBP5, SERPING1, NELL2, CCR7, PASK, LRRN3, and SLC16A10, were commonly altered in TB and sarcoidosis as compared to controls. Gene network analysis revealed 48.89% co-expression and 26.10% physical interaction between these overlapping genes. PPI networks showed a total of 15 nodes and 28 edges present between the connected proteins (PPI enrichment p-value:<1.0e−16). MiRNAs and transcription factors that exhibited the highest interaction with DEGs included hsa-miR-26a-5p, hsa-miR-16-5p, hsa-miR-335-5p, and EPAS1, HIF1A, KLF2, respectively. Pathway analysis indicated enrichment of IFN gamma signaling in both diseases. Molecular docking revealed weighted scores of −884.4, −851.9, and − 637.1 between three key proteins (PASK-GBP1, PASK-GBP5, and GBP1-GBP5).

Conclusion

The shared dysregulated genes in TB and sarcoidosis demonstrate notable co-expression and physical interaction, constituting a PPI network enriched in the IFN-gamma signaling pathway.