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Abstract: FR-PO467

Origin of Proteins and Metabolites in Peritoneal Dialysis Explained by a Multi-Omic Approach

Session Information

Category: Dialysis

  • 702 Dialysis: Home Dialysis and Peritoneal Dialysis


  • Kratochwill, Klaus, Medical University of Vienna, Vienna, Austria
  • Herzog, Rebecca, Medical University of Vienna, Vienna, Austria
  • Vychytil, Andreas, Medical University of Vienna, Vienna, Austria
  • Aufricht, Christoph, Medical University of Vienna, Vienna, Austria

Peritoneal dialysis effluent (PDE) is a rich but underexplored source for therapy monitoring and investigation of deregulated processes during PD. Modern high performance mass spectrometry (MS) and sequencing methods allow monitoring of hundreds of analytes in parallel. For understanding PD related processes on a systems biology level, a multi-level omics approach is particularly attractive. Here, we investigate the cellular transcriptome and cell-free proteome of PDE samples to investigate the origin of proteins found in PDE.


The effluent material from stable patients was separated into a cellular and cell-free component. Proteins in the cell-free compartment were processed using our equalizing and TMT-labelling workflow followed by LC-MS. The cellular material was subjected to RNA sequencing. A bioinformatic workflow conjoined information from the datasets to reveal novel insights into the “PD effluentome”, especially clarifying the source of proteins found in PDE.


Metabolomics methods enabled detecting 207 unique metabolites in cell-free PDE. A mixed-effect ANOVA of all metabolites demonstrated dwell time-dependent concentration changes of 173. Post-hoc testing revealed most metabolites to be changed between 1h and 16h of fluid dwell, followed by 114 and 46 differently concentrated metabolites between 4h and 16h and 1h and 4 h of dwell respectively. We quantified 9,797 transcripts in PD-effluent cells and 2,729 proteins in PDE. 342 proteins were filtered from plasma, while 800 proteins were attributable to local production. A quantitative analysis of the interaction proteome and cellular transcripts of roughly 1700 protein-transcript pairs showed clusters of proteins explained by over-expression in peritoneal cells compared to plasma concentrations.


The exploitation of PD effluent information on multiple omics levels as identified by our bioinformatic approach will improve our understanding of the molecular processes in the peritoneal cavity and their role in development of complications for ultimately improving PD therapy. Our work suggests feasibility of multi-omics approaches to investigate cell derived biomarkers for their involvement in pathomechanisms relevant in PD.