Blood protein patterns linked to differing heart failure risk
A four-protein panel improved prediction beyond clinical factors and an existing blood marker, raising a measure of how well the model ranked risk by 0.021.
Paper by Jiayu Lv, Shucheng Si, zhaoyu wang et al.
Limit: The prediction panel lacks external validation in an independent cohort
Edited by Boris Djordjevic · AgingResearch.News
Researchers followed 42,324 metabolically unhealthy UK Biobank participants without heart failure at enrollment in an observational study. During a median follow-up of 13.65 years, 2,178 developed heart failure, a condition in which the heart cannot pump blood effectively. The researchers examined associations between 2,923 blood proteins, body fat measures and later heart failure.
They identified 76 proteins whose associations with heart failure varied with body fat measures. Protein patterns also differed in their links to the development of cardiometabolic diseases and subsequent heart failure. Adding four selected proteins improved prediction beyond clinical factors and an existing blood marker. The C-index, which measures how well a model ranks people by risk, rose by 0.021.
Why it matters
For heart failure, an age-related disease, a key question is whether molecular measurements can capture risk differences that standard clinical assessments miss.
Caveats
This observational analysis cannot establish that the proteins cause heart failure. The prediction panel needs external validation, and its performance beyond metabolically unhealthy UK Biobank participants remains unestablished.
- Machine learning
- Extracellular matrix remodeling
- Immune response
- Heart failure
- Cardiometabolic disease
- Humans
The paper
Jiayu Lv, Shucheng Si, zhaoyu wang et al.
Frontiers in Endocrinology, Oct 30, 2026, CC BY, Accepted, not yet published
Comments
Be the first to comment.