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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
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Abstract titles should be brief and reflect the content of the abstract.
Proteinuria is a major predictor of CKD progression, yet conventional indices (eGFR, UPCR) incompletely capture risk. We tested whether plasma metabolomics can delineate proteinuria-associated biomarkers and pathways partly independent of filtration to refine phenotyping and risk stratification.
We analyzed 532 adults with CKD (eGFR <60 mL/min/1.73 m²) from the J-Kidney Biobank. Wide-targeted LC-MS quantified plasma metabolites; after quality control, 251 metabolites proceeded to analysis. Participants were classified as proteinuria-positive vs negative. Discrimination was evaluated using sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) with 5-fold cross-validation; performance was summarized by AUC. Logistic/linear models estimated associations (BH-FDR). To isolate filtration-independent signals, analyses were repeated with eGFR adjustment; sensitivity analyses modeled albuminuria continuously. Pathways were assessed by Metabolite Set Enrichment Analysis (MSEA).
Global profiles separated proteinuria-positive from negative CKD with excellent performance (AUC 0.87, 95% CI 0.82–0.91). Discrimination remained good after eGFR adjustment (AUC 0.77, 0.72–0.82), indicating biology beyond reduced clearance. t-SNE and sPLS-DA still showed group separation after eGFR adjustment. Choline, trigonelline, and p-cresol sulfate were top discriminators and remained significant after eGFR adjustment, alongside select lipid species. For the binary outcome, MSEA highlighted phospholipid and phosphatidylcholine biosynthesis as the most enriched programs in proteinuric CKD. With albuminuria modeled continuously, taurine/hypotaurine metabolism showed the highest enrichment, with other lipid-related signals (e.g., arachidonic and linoleic acid metabolism). Findings supported lipid-centric remodeling and osmolyte handling.
In a large Japanese CKD cohort, integrative plasma metabolomics identified a compact, coherent signature of proteinuria that is partly independent of filtration. Lipid remodeling—particularly phosphatidylcholine biosynthesis—and osmolyte pathways emerged as reproducible features, while choline, trigonelline, and p-cresol sulfate stood out as candidate biomarkers. These findings refine the biochemical landscape of proteinuric vs non-proteinuric CKD, yield testable hypotheses linking membrane lipid homeostasis and osmoprotection to glomerulotubular injury, and motivate prospective validation to test incremental value beyond eGFR/UACR for earlier detection and better risk stratification.
We thank all participants and cohorts. The following institutions contributed to establishing the J-Kidney Biobank: Kawasaki Medical School; The Jikei University; Kanazawa University; Kyoto University; Kyushu University; Nagoya University; Nara Medical University; Niigata University; Okayama University; Saitama Medical University; Tohoku Medical Megabank Organization; The University of Tokyo; Yokohama City University.
