Abstract: TH-OR100
Decoding the Kidney Allograft: Single-Nucleus Transcriptomics of Serial Biopsies Uncovers Cell States Linked to Kidney Function
Session Information
- The Next Frontier in Kidney Transplantation: Omics, Gene Editing, and Precision Medicine
October 22, 2026 | Location: Mile High Ballroom 4A, Convention Center
Abstract Time: 04:30 PM - 04:40 PM
Category: Transplantation
- 2001 Transplantation: Basic
Authors
- Gerhardt, Louisa Maria Sophie, Universitatsklinikum Mannheim, Mannheim, BW, Germany
- Gauthier, Patrick T., University of Alberta Alberta Transplant Applied Genomics Centre, Edmonton, Alberta, Canada
- Hoeft, Konrad, Rheinisch-Westfalische Technische Hochschule Aachen, Aachen, NRW, Germany
- Tossidou-Schaefer, Irini, Medizinische Hochschule Hannover, Hanover, NDS, Germany
- Scheffner, Irina, Medizinische Hochschule Hannover, Hanover, NDS, Germany
- Schmidt-Ott, Kai M., Medizinische Hochschule Hannover, Hanover, NDS, Germany
- Krämer, Bernhard K., Universitatsklinikum Mannheim, Mannheim, BW, Germany
- Gwinner, Wilfried, Medizinische Hochschule Hannover, Hanover, NDS, Germany
- Kramann, Rafael, Rheinisch-Westfalische Technische Hochschule Aachen, Aachen, NRW, Germany
- Hinze, Christian, Medizinische Hochschule Hannover, Hanover, NDS, Germany
Background
Transplantation-associated acute kidney injury is a major determinant of kidney allograft outcome. Protocol biopsies of non-rejecting allografts enable longitudinal assessment of cellular and molecular changes following transplantation-associated injury and their relationship to renal function.
Methods
Single-nucleus RNA-sequencing (snRNA-seq) was performed on non-rejecting protocol kidney allograft biopsies at 1, 3, and 6 months after transplantation. In total 44 biopsies from 21 patients were analyzed (14 deceased-donor transplants, 8 with delayed graft function [DGF], 6 without; 7 living-donor transplants without DGF) and integrated with published snRNA-seq data from 4 non-injury controls. Associations between identified cell types/states and kidney function were evaluated using genome-wide microarray data from 950 non-rejecting transplant biopsies obtained within 6 months after transplantation (848 patients).
Results
Analysis of 439,051 nuclei identified 70 cell types and states. Compared with controls, allograft biopsies showed increased proportions of injured epithelial cells, immune cells, myofibroblasts, and altered endothelial cells. Cell-type abundance was similar between living- and deceased-donor transplants and between patients with and without DGF, with substantial inter-individual variability. Tubular injury occurred throughout the nephron and persisted for at least 6 months. Correlation of cell-type marker signatures with eGFR in the large transplant biopsy cohort revealed both expected and novel associations. Proinflammatory and profibrotic injured tubular cells were negatively, and non-injured tubular cells and less severely injured proximal tubule cells with predominant metabolic alteration positively correlated with eGFR. In contrast, parietal epithelial and descending thin limb cells, altered and activated endothelial cells, and several immune and interstitial cell populations were negatively correlated with allograft function. Most associations also predicted graft survival and key genes driving these associations were identified as candidate markers.
Conclusion
Longitudinal snRNA-seq of protocol kidney allograft biopsies demonstrates persistent tubular injury and transplantation-associated remodeling of the renal cellular landscape, identifying cell types and states linked to preserved or impaired graft function.
Acknowledgment
L.M.S.G. was funded by a clinician scientist grant from the German Society of Internal Medicine (Deutsche Gesellschaft für Innere Medizin– DGIM).
Funding
- Private Foundation Support