Abstract
Type 2 diabetes (T2DM) and tuberculosis (TB) both regulate inflammation and may exert synergistic or antagonistic effects through shared immune pathways. Previous studies have demonstrated that T2DM is a risk factor for TB. However, at the level of gene regulatory networks, it remains unclear whether there are key interaction nodes linking these two diseases. In this study, we integrated bioinformatic analysis from the Gene Expression Omnibus (GEO) database and performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA). Furthermore, we applied machine learning techniques to identify key genes among the commonly differentially expressed genes (DEGs). In addition, this study employed siRNA in THP-1 cells to validate the cross-talk genes selected through bioinformatic analysis. The THP-1 cells were treated with high-concentration glucose (15.5 μM, Glu), Mycobacterium tuberculosis ESAT-6, or Glu+ESAT-6. We identified a total of 23 common genes between TB and T2DM using DEGs and WGCNA. Furthermore, expression patterns from external datasets revealed three key cross-talk genes linking TB-T2DM: CYP1B1, SERPING1, and CHPT1. Notably, only CYP1B1 was significantly upregulated in the THP-1 detection test, compared to the unstimulated (control) group (P < 0.05). Moreover, CYP1B1 significantly reduced the expression of pro-inflammatory cytokines (TNF-α, IL-6, IL-1β, IL-10), M2 macrophage polarization markers (CD163, Arg-1), and chemokines (CXCL-10), and was associated with the NOD2 and TRAF6 signaling pathways (P < 0.05). These findings elucidate the regulatory mechanisms underlying the comorbidity of TB and T2DM, providing a theoretical basis for the development of precise combination therapies and novel therapeutic targets.