Kidney Week

Abstract: TH-PO0901

Urine Proteomics as a Source of Biological Information and an Outcome Predictor in Living-Donor Kidney Transplantation

Session Information

• Transplantation: Basic Research
  November 06, 2025 | Location: Exhibit Hall, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Transplantation

• 2101 Transplantation: Basic

Authors

• Hoyer-Allo, Karla Johanna Ruth, Universitatsklinikum Koln, Cologne, NRW, Germany

Karla Johanna Ruth Hoyer-Allo, MD

• Affeldt, Patrick, Universitatsklinikum Koln, Cologne, NRW, Germany

Patrick Affeldt, MD

• Lackmann, Jan-Wilm, Exzellenzcluster CECAD in der Universitat zu Koln, Cologne, NRW, Germany

Jan-Wilm Lackmann, PhD

• Mueller, Stefan, Exzellenzcluster CECAD in der Universitat zu Koln, Cologne, NRW, Germany

Stefan Mueller, PhD

• Buchner, Denise, Universitatsklinikum Koln, Cologne, NRW, Germany

Denise Buchner

• Braun, Fabian, Universitatsklinikum Hamburg-Eppendorf, Hamburg, HH, Germany

Fabian Braun, MD

• Kurschat, Christine E., Universitatsklinikum Koln, Cologne, NRW, Germany

Christine E. Kurschat, MD

• Stippel, Dirk L., Universitatsklinikum Koln, Cologne, NRW, Germany

Dirk L. Stippel, DrMed, MBA

• Bohl, Katrin, Universitatsklinikum Koln, Cologne, NRW, Germany

Katrin Bohl, PhD

• Mueller, Roman-Ulrich, Universitatsklinikum Koln, Cologne, NRW, Germany

Roman-Ulrich Mueller, MD

Background

Kidney transplantation (KTx) is the preferred treatment for kidney failure, offering improved survival, quality of life, and cost-effectiveness compared to dialysis. However, post-transplant management is challenging due to the limited lifespan of transplanted organs, often requiring repeat transplants. Current methods for monitoring post-transplant issues are invasive and have limitations. Therefore, there is urgent need for novel non-invasive biomarkers. This study investigates the proteomic composition of urine to understand kidney biology during transplantation and to identify potential markers for outcome prediction.

Methods

Urine samples were collected from donors before and from recipients 4 weeks and 1 year after transplantation from the Transplant Center of the University Hospital Cologne. Proteomic analysis was performed using mass spectrometry and label-free quantification. Statistical analyses included principal component analysis(PCA), enrichment analysis, and correlative regression models to evaluate the relationship between protein abundance and clinical outcomes in the further course after transplantation.

Results

106 urine samples in the setting of 70 kidney transplantations were analyzed. PCA revealed distinct clustering of donor and recipient samples, indicating significant proteomic changes after transplantation. Hierarchical clustering and gene ontology analysis identified molecular changes as a response to transplantation and showed overrepresentation of relevant pathways related to inflammation, cell death and survival. Multivariate regression analysis, including linear and logistic regression, identified 11 potential protein biomarkers including IL1RAP, APP and FABP4 as predictors of eGFR 12 months after and HP as predictor of infections within the first year after transplantation, respectively.

Conclusion

This study underlines the potential of non-invasive urine proteomics for identifying biological processes involved in kidney transplantation and for enhancing post-transplant monitoring and outcome prediction. We identified 12 potential biomarkers with added value to standard clinical parameters linked to transplant outcomes, which will be promising candidates for future outcome monitoring after KTx.

Digital Object Identifier (DOI)

• doi: 10.1681/ASN.2025qgt0yyp7