Identification of mitochondrial metabolism-associated tuberculosis key genes and construction of a diagnostic model based on WGCNA.

Despite recent advances, tuberculosis (TB) remains a complex global health challenge, with its causative bacterium, Mtb, actively manipulating host cellular metabolism to survive. Therefore, studying mitochondrial metabolism-related genes is crucial, as they offer a promising avenue for identifying diagnostic biomarkers and developing new host-directed therapies to combat the disease. This study integrated transcriptomic datasets from three TB cohorts in the Gene Expression Omnibus (GEO) database (training set: GSE83456; validation sets: GSE42826 and GSE19444). Differential analysis was performed using the "limma" package (with |logFC| > 1 and adjusted p-value < 0.05) to identify mitochondrial metabolism-related differentially expressed genes. Diagnostic biomarkers were determined by combining weighted gene co-expression network analysis (WGCNA), and the effectiveness of the model was evaluated using receiver operating characteristic (ROC) curve analysis. Immune infiltration characteristics were assessed via single-sample gene set enrichment analysis (ssGSEA) and Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), pathway enrichment analysis was conducted through GSEA, molecular subtypes were classified using the non-negative matrix factorization (NMF) algorithm, and MicroRNA (miRNA) and transcription factor (TF) regulatory networks were predicted using "miRNet" and "NetworkAnalyst". We identified 3 mitochondrial metabolism-related biomarkers (TYMP, SCO2, GK) with remarkable diagnostic performance (area under the curve [AUC] = 0.973 across cohorts). These genes were closely associated with altered immune infiltration patterns, characterized by enhanced inflammatory responses in macrophages and monocytes, along with a reduction in T-cell subsets. These genes are associated with ribosome and innate immune pathways. Furthermore, tuberculosis patients were stratified into two distinct molecular subtypes exhibiting specific immune microenvironment features. Regulatory network analysis revealed hsa-miR-10b-5p and transcription factor hubs (SP3/SP1) as potential master regulators. This study identifies a mitochondrial metabolism-based gene signature for TB diagnosis, revealing novel host-pathogen mechanisms and enabling potential targeted therapies for precision medicine.