Identification of Common Molecular Signatures in Chronic Obstructive Pulmonary Disease and Pulmonary Tuberculosis

Chronic obstructive pulmonary disease (COPD) and pulmonary tuberculosis (TB) are major causes of morbidity and mortality worldwide. Epidemiologic studies indicate an increased risk of tuberculosis in patients with COPD; however, the shared molecular mechanisms underlying the pathogenesis of these two diseases remain insufficiently understood. Objective. Based on a comparative bioinformatics analysis of peripheral blood transcriptomic profiles in patients with COPD and pulmonary tuberculosis, to identify common systemic immune mechanisms associated with the pathogenesis of both diseases. Gene expression data from the NCBI GEO public database were analyzed. GSE34608 included blood samples from 8 patients with tuberculosis and 18 healthy controls. The GSE76705 dataset contained peripheral-blood samples from 364 former smokers (225 with COPD and 139 without). Functional enrichment (GO Biological Process and KEGG) was run in ShinyGO; protein-protein interaction networks were built in STRING, and the top-15 hub genes were ranked by the MCC algorithm in CytoHubba. In tuberculosis, 892 up-regulated and 1448 down-regulated genes were identified; in COPD, 520 up-regulated and 1329 down-regulated. Common upregulated DEGs are involved in toll-like receptor signaling pathways, NOD-like receptor signaling pathways, neutrophil extracellular trap (NET) formation, phagosomes, and tuberculosis. Downregulated genes in each of the diseases were associated with processes of transcriptional regulation and RNA metabolism, which may indicate common transcriptional abnormalities in COPD and tuberculosis. COPD and tuberculosis share common pathogenic mechanisms, including the activation of innate immune signaling pathways (TLR, NOD), neutrophilic inflammation, the formation of neutrophil extracellular traps (NETosis), and phagocyte dysfunction. The identified common genes and signaling pathways may serve as a basis for the development of biomarkers and therapeutic targets; however, they require further validation in independent cohorts.