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September 12, 2025Circulation Genomic and Precision Medicine

Large-Scale Proteomics-Based Risk Score for the Prediction of Incident Cardio-Kidney-Metabolic Disease Risk

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Authors

AYAdithya K. YadalamCLChang LiuQHQin Hui

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Overview

Analysis shows that a novel risk score improves CKM disease prediction in a large cohort, indicating its potential clinical utility.

Key Points

  • A proteomics-based risk score significantly predicted incident CKM disease risk in a large population.
  • Over 13.5 years, 3235 CKM disease events occurred, highlighting the clinical relevance of the findings.
  • Methods employed included a Cox regression model using 2913 proteins from the UK Biobank to develop the risk score.
  • The risk score improved CKM disease prediction accuracy beyond traditional factors, potentially aiding clinical decisions.

Cite This Study

Yadalam et al. (2025) studied this question.

synapsesocial.com/papers/68d43b09713b0b5dfea7b2a3https://doi.org/10.1161/circgen.124.005125
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Protein risk scores enable precise prediction of cardiovascular events in chronic kidney disease patients2025 · 1 citations
  2. 22247-P: Uncertainty-Calibrated Prediction of Cardiovascular–Kidney–Liver–Metabolic Disease Using Clinical Biomarkers and Plasma Proteomics2026
  3. 3Multi-omics integration predicts 17 disease incidences in the UK Biobank2025
  4. 4Circulating inflammation-related proteome improves cardiovascular risk prediction. Results from two large European cohort studies2025
  5. 5A retrospective study on development and internal validation of cardiovascular disease risk prediction model for patients with chronic kidney disease stage 3–5 within 5 years2026