Glucose-Independent Metabolic Signatures of SGLT2 Inhibition in Diabetic Kidney Disease: Integrated Insights from Mendelian Randomization and Transcriptomics.

BACKGROUND

Diabetic kidney disease (DKD) remains a major cause of terminal renal failure, with residual risk remaining unacceptably high despite standard glucose control. Although the sodium-glucose co-transporter 2 (SGLT2) inhibitors have proven reno-protective properties extending beyond that explained by glucose lowering alone, unique glucose-independent molecular mechanisms are still incompletely defined. Unveiling these non-glycemic metabolic pathways is of paramount importance for new therapeutic targets and optimized clinical management.

METHODS

A systematic multi-omics triangulation framework integrating Mendelian randomization (MR) with tissue-specific transcriptomics was conducted. Two-sample MR and multivariable Mendelian randomization (MVMR) adjusted for fasting blood glucose were leveraged as a screening tool to detect glucose-independent serum metabolites in humans using large-scale genome-wide association study data. These findings were validated with transcriptomic signatures from both diabetic and non-diabetic mouse kidney models to identify conserved core genes and convergent metabolic pathways.

RESULTS

Genetically proxied SGLT2 inhibition associated with a reduced risk of DKD, with an odds ratio of 0.58, and improved renal function markers. MVMR highlighted 259 glucose-independent metabolites, covering systemic alterations in lipid and amino acid metabolism. A cross-model transcriptomic comparison revealed seven key genes functionally enriched in fatty acid oxidation and ketone body utilization. This convergence supports the concept of a fasting-like metabolic switch and coordinated downregulation of fibrosis-related extracellular matrix pathways irrespective of diabetic status.

CONCLUSION

This study delineates a systemic-renal metabolic axis whereby SGLT2 inhibition drives renoprotection via metabolic reprogramming and anti-fibrotic mechanisms distinct from blood glucose lowering. These findings provide genetic evidence for specific non-glycemic targets and represent a novel mechanistic insight for precision therapeutic intervention in kidney disease.