The PD Effluentome—A Multi-Omics Atlas Defining the Composition, Transport Dynamics, and Molecular Origin of Peritoneal Dialysis Effluent

Background: Peritoneal dialysis (PD) effluent of kidney failure patients represents an accessible liquid biopsy of the peritoneal cavity, yet the mechanisms determining its molecular composition remain poorly understood. We applied an integrative multi-omics approach to characterize the composition, transport dynamics, and molecular origin of the PD effluentome. Methods: Cell-free effluent, effluent cells, and plasma were collected from stable PD patients during standardized peritoneal equilibration tests in a randomized clinical trial. Targeted metabolomics, proteomics, and transcriptomic profiling were integrated with a reference human plasma proteome to investigate temporal molecular changes, peritoneal transport characteristics, and protein origin. Results: A total of 207 metabolites and 2970 proteins were identified in PD effluent. Metabolites exhibited distinct class-specific transport kinetics, with rapid equilibration of amino acids and biogenic amines, whereas lipids remained markedly underrepresented despite prolonged dwell times, indicating that transport is governed by physicochemical properties beyond molecular size alone. The effluent proteome underwent concordant alteration, with dwell time-dependent enrichment of pathways related to extracellular matrix organization, angiogenesis, coagulation, and tissue repair. Integrative analysis of the effluent proteome, effluent-cell transcriptome, and human plasma proteome resolved distinct plasma-associated, effluent cell-associated, resident peritoneal tissue-associated, and mixed-origin protein populations. Conclusions: This study establishes the first systems-level approach describing the composition, transport dynamics, and molecular origin of the PD effluentome. By transforming PD effluent into a biologically interpretable molecular readout of peritoneal membrane biology, this work provides a reference for the mechanistic interpretation of effluent-derived biomarkers and supports future therapeutic monitoring and precision medicine in PD.