Abstract: FR-PO0287
Genetic Regulators of Circulating Proteins Predicting Risk of ESKD and Their Potential Role in Diabetic Kidney Disease Progression
Session Information
- Diabetic Kidney Disease: Basic and Translational Science Advances - 1
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Authors
- Price, Tara R, University of Utah Health, Salt Lake City, Utah, United States
- Stucki, Devorah Olivia, University of Utah Health, Salt Lake City, Utah, United States
- Md Dom, Zaipul, Joslin Diabetes Center, Boston, Massachusetts, United States
- Satake, Eiichiro, Joslin Diabetes Center, Boston, Massachusetts, United States
- Krolewski, Andrzej S., Joslin Diabetes Center, Boston, Massachusetts, United States
- Pezzolesi, Marcus G., University of Utah Health, Salt Lake City, Utah, United States
Background
Over the past decade, major progress has been made in identifying predictors (i.e., biomarkers) of kidney disease progression in patients with diabetes mellitus. Despite this progress, the contribution of genetic factors on the levels of these biomarkers remains largely unknown. To advance this area, we set out to define the genetic drivers of circulating proteins associated with end-stage kidney disease (ESKD) risk in individuals with diabetes.
Methods
Leveraging genetic and proteomic data from 3,171 participants with diabetes from the UK Biobank Pharma Proteomics Project (UKB-PPP), we performed genome-wide association analyses for 21 Joslin Kidney Panel (JKP) circulating proteins previously shown to be associated with ESKD risk and measured on the OLINK Explore 3072 platform. We further utilized the fine-mapping model, Sum of Single Effects (SuSiE), model with GWAS summary data to identify credible sets of candidate causative single nucleotide polymorphisms (SNPs). Candidate causative SNPs were included in Cox proportional hazards regression models to determine mediation of ESKD risk.
Results
We identified genome-wide significant (p-value <5x10-8) cis protein quantitative trait loci (pQTLs) for 14 of the 21 JKP proteins (67%). In total, 948 variants achieved genome-wide significance across these cis-pQTLs. We also identified 368 variants reaching genome-wide significance for trans-pQTLs of 2 JKP proteins. SuSiE fine-mapping identified 69 credible sets of candidate causative variants across the 14 proteins with GWAS significant pQTL. Mediation analysis with candidate variants for JKP proteins suggests improved risk prediction of DKD progression to ESKD.
Conclusion
Together, these data provide new insights on the genetic regulators of kidney disease progression predictors, advancing our understanding of the pathogenesis of kidney disease progression in diabetes and potentially strengthening prognostic models for improve DKD risk stratification.
Funding
- NIDDK Support