#4152 CROSS-OMICS PROFILING OF PROTEOME, METABOLOME, AND TRANSCRIPTOME REVEALS MOLECULE AND CLEARANCE DYNAMICS AND ORIGIN IN PERITONEAL DIALYSIS Free

Peritoneal dialysis (PD) effluent is not only a rich source of markers for therapy monitoring and investigation of deregulated processes during PD it is also surprisingly underexplored and therefore poorly defined. Modern high performance mass spectrometry (MS) and sequencing methods allow monitoring of hundreds of analytes in parallel. For understanding PD transport dynamic and pathomechanisms and on a systems biology level, a multi-level omics approach is particularly attractive.

Samples were obtained from stable patients chronically treated with PD at different time-points of standard 4h peritoneal equilibration tests (PETs). Effluent was collected after the pre-PET (overnight) dwell and at 0h, 1h and 4h dwells. Plasma samples were taken at the 2h PET time point. Effluent was separated into a cellular and cell-free component. Soluble proteins and metabolites in the cell-free compartment were processed using material-specific protocols and standardized LC-MS workflows. The cellular material was subjected to RNA sequencing. The Plasma-Proteome database was used for referencing plasma proteins and estimating plasma concentration. A bioinformatic workflow conjoined information from the datasets to reveal novel insights into the “PD-effluentome”, especially unravelling the origin of proteins and metabolites in PD effluent.

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

Cross-omic profiling of PD effluent can be a valuable approach for revealing small molecule related changes during PD. The exploitation of PD effluent on multiple levels could improve the understanding of pathophysiological molecular processes and transport dynamics in the peritoneal cavity and their role in development of PD complications.