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INTRODUCTION: Dapagliflozin improves kidney outcomes in patients with chronic kidney disease (CKD), yet the underlying mechanisms by which it exerts protective effects are not fully elucidated. Here, we applied plasma proteomics to identify proteins and pathways linked to CKD progression and examined which of these are modulated by dapagliflozin. METHODS: and urinary albumin-to-creatinine ratio 200-5000 mg/g). Proteins associated with the composite kidney outcome (50% eGFR decline, kidney failure, and kidney death) and with dapagliflozin treatment were respectively identified by multivariable Cox proportional hazard regression and ANCOVA. Ingenuity pathway analysis was used to identify relevant molecular pathways and upstream regulators. RESULTS: Pathways that had the strongest association with the composite kidney outcome were hepatic fibrosis, insulin-like growth factor transport regulation, and tumor necrosis factor signaling. These pathways were generally related to fibrosis and inflammation. After 12 months, dapagliflozin treatment showed a (placebo-corrected) modification of 216 proteins, of which kidney injury molecule-1 showed the strongest reduction (-14.9%; 95% confidence interval: -17.9, -11.7). Of the 137 pathways associated with the kidney outcome, 35 (25%) were modified by dapagliflozin. Among these, activity of 11 (31% of 35) pathways decreased, and 10 (29% of 35) pathways were increased. Pathways associated with kidney outcome and modulated by dapagliflozin were related to extracellular matrix remodeling, inflammation and fibrosis, and immune-vascular interactions. CONCLUSIONS: This proteomic analysis reveals mechanisms underlying dapagliflozin's beneficial effects in CKD progression and shows that key pathways associated with CKD progression are modified by dapagliflozin, supporting its anti-inflammatory and antifibrotic potential.
Rambelje et al. (2026) studied this question.