Abstract: SA-PO0304
Association of Circulating Protein Levels with Kidney Outcome and Effects of Dapagliflozin: Proteomics Analysis from DAPA-CKD
Session Information
- Diabetic Kidney Disease: Basic and Translational Science Advances - 2
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Authors
- De la Rambelje, Mark Andre, Universitair Medisch Centrum Groningen, Groningen, GR, Netherlands
- Jongs, Niels, Universitair Medisch Centrum Groningen, Groningen, GR, Netherlands
- Greasley, Peter J., AstraZeneca, Gothenburg, Sweden
- Ågren, Rasmus, AstraZeneca, Gothenburg, Sweden
- Hammarstedt, Ann, AstraZeneca, Gothenburg, Sweden
- Sjostrom, David, AstraZeneca, Gothenburg, Sweden
- Voors, Adriaan A., Universitair Medisch Centrum Groningen Afdeling Cardiologie, Groningen, GR, Netherlands
- Heerspink, Hiddo Jan L., Universitair Medisch Centrum Groningen, Groningen, GR, Netherlands
Group or Team Name
- DAPA-CKD Biomarker Committee.
Background
We studied the progression of CKD and the effects of dapagliflozin using plasma proteomics to identify proteins involved in the pathophysiology of CKD progression and dapagliflozin's underlying mechanism.
Methods
Circulating protein profiles (Olink 3072 panel) of participants from the DAPA-CKD trial, recruiting 4304 patients with CKD with and without type 2 diabetes, eGFR of 25 to 75 ml/min/1.73 m2 and a UACR of 200 to 5000 mg/g, were analyzed. Multivariable cox proportional hazard models determined the risk of baseline protein levels on the composite kidney outcome (50% eGFR decline, kidney failure, or renal death). Proteins affected by dapagliflozin compared to placebo were identified by analysis of covariance followed by Ingenuity pathway analysis.
Results
Baseline protein profiles were available in 2485 (57.7%) participants; 1982 (46.1%) had both baseline and year 1 protein profiles available. WFDC2, CD27, and TNFRSF7 were the most significant proteins associated with the composite kidney outcome (Fig. 1A); reflecting pathways related to immune system, inflammation, and fibrosis. Of the 216 proteins changed by 1-year treatment with dapagliflozin compared to placebo, 49 (23%) proteins were also associated with the composite kidney outcome (Fig. 1C). Among these 49 proteins, KIM-1, CTHRC1, and NT-proBNP, were decreased after 1 year of treatment with dapagliflozin (Fig. 1B). Pathways affected by dapagliflozin were involved in interleukin production & tyrosine signaling, extracellular matrix organization, and inflammation & wound healing (Fig. 1D).
Conclusion
Pathways of inflammation and fibrosis associated with kidney outcomes were targeted by dapagliflozin. These data confirm and provide new insights in the molecular effects of dapagliflozin in patients with CKD.