Abstract: TH-PO1010

Urinary Microvesicles in Kidney Transplantation: A Source for Novel Early Biomarkers for Delayed Graft Function and Overall Outcome

Session Information

Category: Transplantation

  • 1702 Transplantation: Clinical and Translational

Authors

  • Braun, Fabian, University Hospital Cologne, Cologne, NW, Germany
  • Benzing, Thomas, University Hospital Cologne, Cologne, NW, Germany
  • Mueller, Roman-Ulrich, University Hospital Cologne, Cologne, NW, Germany
  • Rinschen, Markus M., University Hospital Cologne, Cologne, NW, Germany
  • Klein, Corinna, University of Cologne, Cologne, NW, Germany
  • Buchner, Denise, University Hospital of Cologne, Cologne, NW, Germany
  • Wahba, Roger, University Hospital of Cologne, Cologne, NW, Germany
  • Stippel, Dirk L, University Hospital of Cologne, Cologne, NW, Germany
  • Kurschat, Christine E., University Hospital Cologne, Cologne, NW, Germany
  • Schermer, Bernhard, University Hospital Cologne, Cologne, NW, Germany
  • Beyer, Andreas, University of Cologne, Cologne, NW, Germany
Background

Microvesicles (MVs) are a promising source for cellular material comprising specific proteins and nucleic acids that can be isolated easily from most body fluids. This is especially true for urinary microvesicles, yet their implementation in routine diagnostics is still subject to investigation. We hypothesize that the diagnosis of kidney transplant failure by kidney biopsy could in particular benefit from the addition of novel noninvasive biomarkers for the prediction of graft survival.

Methods

We established a protocol of differential centrifugation, to isolate MVs from urine collected from living kidney transplant recipients and their corresponding donors over the course of 20 kidney transplantations. We collected whole urine samples on day -1 (donor sample), 0, 1 and 3 months after transplantation (recipient sample). MV pellets were analyzed using quantitative mass spectrometry based proteomics. We used linear regression models to find proteins which linearly change their abundance in correspondence to clinical parameters, e.g. GFR measured at 6 and 12 Months after transplantation.

Results

With our approach we were able to identify >1500 proteins present in at least 50% of the collected samples. Strikingly, using hierarchical cluster analysis we detected a clear clustering of the sample proteomes by time point of urine collection. Furthermore we detected specific proteomic time course patterns over the course of transplantation, with complement and serum-bourne proteins peaking shortly after transplantation. Also, MV proteins of glomerular or tubular origin were regulated distinctly over the course of transplantation. We chose 64 candidate proteins that showed low statistical error and high stability in the leave-one-out cross-validation of the linear models with GFR values measured after 6 and 12 months or that were either only or not detected in samples depicting delayed graft function.

Conclusion

Our analysis represents the first concise data set depicting the changes in the human urinary MV proteome over the course of kidney transplantation. Ongoing experiments will focus on the validation of candidate proteins correlating with long term outcomes and the analysis of their clinical implementation.

Funding

  • Government Support - Non-U.S.