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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.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Cardiovascular disease (CVD) remains the leading cause of death in maintenance hemodialysis (HD). In HD, the uremic and dialytic milieu likely creates a distinct circulating protein profile, yet its composition and removal/accumulation kinetics remain poorly defined; consequently, clinical risk models capture only part of the biology, motivating discovery of circulating protein signatures that improve prognosis and inform preventive trials, including the search for therapeutic targets. Leveraging the INFINITY biobank—almost 1,000 HD patients enrolled across two time-separated phases at seven typical dialysis clinics in Japan—we applied high-throughput proteomics to identify and validate blood-based predictors of incident CVD events.
We profiled pre-HD serum with Olink Explore HT (5,400 proteins) in two independent, identically processed nested case–control sets (Phase 1 and Phase 2, each n=85 with approximately equal numbers of incident CVD cases within 2 years and controls). Proteins were quantified on the NPX scale with standard QC. Associations with incident CVD (myocardial infarction, angina, stroke) within 2 years were tested using logistic models with multiple-testing control. Candidates were nominated in Phase 1 at false discovery rate (FDR) <0.10 and evaluated under the same analysis plan in Phase 2, designating proteins with concordant effect direction and P<0.05 as robust. From these, we derived a parsimonious multi-protein panel and compared its performance with a clinical-only model (discrimination, calibration, and risk reclassification).
We identified 167 proteins linked to CVD in the screening step (Figure), then confirmed a smaller subset in an independent validation set, with the same direction of effect after adjustment for covariates. The identified proteins clustered into coherent biological areas: chronic inflammation and immune regulation (cytokine/chemokine-like pathways of innate immunity and T-cell activation), vascular endothelial function and remodeling (endothelial injury, vascular remodeling, matrix metabolism), metabolism and mitochondrial function (responses to oxidative stress and altered energy metabolism), fibrosis and tissue repair (matrix turnover and repair processes relevant to heart failure), and cellular stress and apoptosis. A compact multi-protein signature built from the proteins improved discrimination over a clinical-only model, was well calibrated, and produced meaningful risk reclassification.
In a biobank-based study using case–control study design, large-scale proteomics identified circulating protein markers that predict incident CVD in hemodialysis patients. The resulting multi-protein panel improves clinical risk prediction and highlights shared disease pathways. To advance translation, future work should transfer the panel to a targeted assay for external multi-center evaluation and rigorously determine, for each prioritized protein, both its dialyzability and its therapeutic targetability.
