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Abstract: SA-PO958

Cross-Omics Analysis of Transcriptome, Proteome, and Metabolome Dynamics During Peritoneal Dialysis

Session Information

Category: Dialysis

  • 703 Dialysis: Peritoneal Dialysis

Authors

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

Peritoneal dialysis effluent (PDE) represents a rich but underexplored source of molecular markers for the prediction of clinical outcome, therapy monitoring and investigation of deregulated molecular and cellular processes during PD. Novel PD-fluids (PDF) may enable patient-tailored interventions, such as peritoneal immunomodulation. Alanyl-glutamine (AlaGln) has recently been shown to have beneficial effects in experimental and clinical PD. Modern high performance methods allow monitoring of hundreds of analytes in parallel. In this study, we investigate the transcriptome, proteome and metabolome of PDE samples with or without AlaGln-addition to PDF.

Methods

Samples from a cross-over RCT, investigating AlaGln supplementation of PDF, were analyzed in a cross-omics analysis of effluent cells (RNAseq), soluble proteins (LC-MS) and metabolites in the PDE and plasma (targeted MS) to investigate the effect of AlaGln on the interplay of peritoneal cell populations and fluid transport. Peritoneal immune-competence was analyzed by functional ex-vivo stimulated cytokine release of effluent cells. From each PD dwell, PDE was analyzed at multiple time-points. Bioinformatic analysis results and pathway analysis results from the different datasets were conjoined to reveal novel insights into the “PD-effluentome”.

Results

We were able to quantify ~10,000 cellular transcripts, and 2,700 proteins and 300 metabolites in the PDE. Changes in the proteome could in part be explained by co-regulated biological processes observed on the transcript level. The remaining effects on the proteome are likely due to changes in transport characteristics, supported by clinical findings in patients treated with AlaGln. These results correlated with restoration of suppressed peritoneal immune responses by AlaGln. Bioinformatic analysis of proteome-metabolome interference was employed to discriminate local and systemic regulation and transport.

Conclusion

This combined investigation of proteomic and metabolomic properties of PDE represents the first cross-omics analysis of poorly understood molecular processes during PD and the obtained results enable a further step to unravel the beneficial effects of AlaGln-supplementation. Our data also suggest feasibility of multi-omics approaches to investigate pathomechanisms and interventions relevant in PD.