Discovering common pathogenetic processes between tuberculosis and COVID-19 by bioinformatics and system biology approach

Xin Liu; Haoran Li; Yilin Wang; Shanshan Li; Weicong Ren; Jinfeng Yuan; Yu Pang

doi:10.1016/j.heliyon.2024.e28664

Discovering common pathogenetic processes between tuberculosis and COVID-19 by bioinformatics and system biology approach

Heliyon. 2024 Mar 27;10(7):e28664. doi: 10.1016/j.heliyon.2024.e28664. eCollection 2024 Apr 15.

Authors

Xin Liu¹, Haoran Li¹, Yilin Wang¹, Shanshan Li¹, Weicong Ren¹, Jinfeng Yuan¹, Yu Pang¹

Affiliation

¹ Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.

Abstract

Background: SARS-CoV-2, the cause of the COVID-19 pandemic, poses a significant threat to humanity. Individuals with pulmonary tuberculosis (PTB) are at increased risk of developing severe COVID-19, due to long-term lung damage that heightens their susceptibility to full-blown disease.

Methods: Three COVID-19 datasets (GSE157103, GSE166253, and GSE171110) and one PTB dataset (GSE83456) were obtained from the Gene Expression Omnibus databases. Subsequently, data were subjected to weighted gene co-expression network analysis(WGCNA)followed by functional enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. These analyses revealed two overlapping disease-specific modules, each comprising co-regulated genes with potentially related biological functions. Using Cytoscape, we visualised the interaction network containing common disease-related genes found within the intersection between modules and predicted transcription factors (TFs). Real-time qPCR was conducted to quantify expression levels of these genes in blood samples from COVID-19 and PTB patients. Finally, DisGeNET and the Drug Signatures database were employed to analyze these common genes, unveiling their connections to clinical disease features and potential drug treatments.

Results: Examination of the overlap between COVID-19 and PTB gene modules unveiled 11 common genes. Functional enrichment analyses using KEGG and GO shed light on potential functional relationships among these genes, providing insights into their potential roles in the heightened mortality of PTB patients due to SARS-CoV-2 infection. Furthermore, results of various bioinformatics-based analyses of common TFs and target genes led to identification of shared pathways and therapeutic targets for PTB patients with COVID-19, along with potential drug treatments for these patients.

Conclusion: Our results unveiled a potential biological connection between COVID-19 and PTB, as supported by results of functional enrichment analysis that highlighted potential biological processes and signaling pathways shared by both diseases. Building on these findings, we propose potential drug treatments for PTB patients with COVID-19, pending verification of drug safety and efficacy through laboratory and multicentre studies before clinical use.

Keywords: Common gene; Drug molecule; SARS-CoV-2; TF regulatory network; Tuberculosis.