Transcriptomic analysis reveals molecular alterations and candidate transcriptomic features associated with dapagliflozin treatment in patients with type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance, chronic inflammation, and metabolic imbalance. Although dapagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, enhances glycemic control and provides cardio-renal benefits, the transcriptional alterations associated with its treatment remain insufficiently understood. Paired transcriptomic profiles from patients with T2DM before and after dapagliflozin treatment were analyzed to identify differentially expressed genes (DEGs). Candidate genes were screened using three machine-learning approaches: least absolute shrinkage and selection operator (LASSO) regression, random forest, and Boruta, followed by expression validation. Subsequent analysis included functional enrichment, immune-cell infiltration assessment, transcription factor (TF)-mRNA-miRNA network construction, molecular docking, and reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR). A total of 137 DEGs associated with dapagliflozin treatment were identified. Integrated machine-learning analysis pinpointed TAS2R60, GPLD1, and GPR42 as three candidate transcriptomic feature genes, all upregulated post-treatment. In the predicted regulatory network, GPR42 exhibited the highest connectivity. Estimations of immune-cell abundance via single-sample gene set enrichment analysis (ssGSEA) revealed differences in scores for regulatory T cells, memory B cells, natural killer T cells, and central memory CD4+ T cells, with GPR42 expression positively correlating with abundance scores of central memory CD4+ T cells and memory B cells. Molecular docking predicted binding conformations between dapagliflozin and the three candidate proteins; however, these results do not constitute evidence of direct interactions. Preliminary RT-qPCR results supported increased expression of GPLD1 and GPR42, whereas TAS2R60 demonstrated only a nonsignificant upward trend. TAS2R60, GPLD1, and GPR42 emerge as potential transcriptomic features associated with dapagliflozin treatment. Their biological significance and relationship with drug response necessitate validation in larger independent cohorts and functional experiments. Trial registration: ChiCTR2600127234 (registered 2026-06-26). We would like to express our sincere gratitude to all individuals and organizations who supported and assisted us throughout this research. Special thanks to the following authors: Ren Tingting and Jiang ZhaoHui. In conclusion, we extend our thanks t... [2567 chars]