Exploring potential diagnostic markers and therapeutic targets for type 2 diabetes mellitus with major depressive disorder through bioinformatics and in vivo experiments.

Type 2 diabetes mellitus (T2DM) and Major depressive disorder (MDD) act as risk factors for each other, and the comorbidity of both significantly increases the all-cause mortality rate. Therefore, studying the diagnosis and treatment of diabetes with depression (DD) is of great significance. In this study, we progressively identified hub genes associated with T2DM and depression through WGCNA analysis, PPI networks, and machine learning, and constructed ROC and nomogram to assess their diagnostic efficacy. Additionally, we validated these genes using qRT-PCR in the hippocampus of DD model mice. The results indicate that UBTD1, ANKRD9, CNN2, AKT1, and CAPZA2 are shared hub genes associated with diabetes and depression, with ANKRD9, CNN2 and UBTD1 demonstrating favorable diagnostic predictive efficacy. In the DD model, UBTD1 (p > 0.05) and ANKRD9 (p < 0.01) were downregulated, while CNN2 (p < 0.001), AKT1 (p < 0.05), and CAPZA2 (p < 0.01) were upregulated. We have discussed their mechanisms of action in the pathogenesis and therapy of DD, suggesting their therapeutic potential, and propose that these genes may serve as prospective diagnostic candidates for DD. In conclusion, this work offers new insights for future research on DD.