Chemical markers improved heart and lung disease prediction
Adding 250 chemical markers improved risk models beyond standard clinical measures in an observational study of 54,933 Kaiser Permanente biobank participants.
Our read
Biomarkers- Studied:
- Cohort study of 54,933 Kaiser Permanente Research Biobank participants
- What changed:
- NMR biomarkers improved prediction of incident cardiovascular and cardiopulmonary disease beyond standard clinical predictors
- The catch:
- Prediction models were evaluated; health outcomes from model-guided care were not measured
- Why it’s aging research:
- It bears on staying healthy in midlife and later life.
Editor of record: Boris Djordjevic · AgingResearch.News
54,933 Kaiser Permanente Research Biobank participants contributed data to an observational study of chemical markers and future disease risk. Researchers linked electronic health records to 250 markers measured using nuclear magnetic resonance, a method for analyzing chemical composition. They tested whether the markers improved prediction beyond factors including age, sex, blood pressure and disease-relevant clinical tests.
The markers improved predictions of heart and lung diseases. Gains were strongest for type 2 diabetes, metabolic liver disease and chronic kidney disease. The markers retained predictive value when inherited genetic risk was included. Models generally matched predicted risks to observed outcomes at one, three and five years.
Why it matters
For diseases common in later life, the authors suggest these measurements could help guide risk-based follow-up, confirmatory testing and monitoring.
Caveats
The work evaluated prediction models, not whether model-guided care improved health outcomes. The conference abstract did not quantify the predictive gains.
The paper
Weill Cornell Med College; Weill Cornell Medicine
AHA Scientific Sessions 2026 Abstract, Nov 2, 2026
Presented at AHA Scientific Sessions 2026, abstract 10575
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