Arrhythmias & electrophysiologyCohort study
Utilization of Serum Metabolomics and Polygenic Risk Scores in a Novel Risk Stratification Tool for the Prediction of Incident Atrial Fibrillation
- Cohort study
- UK Biobank
- models trained on 80% of the cohort and validated on the remaining 20%
Authors' conclusion
The addition of metabolomics to clinical and genomic risk scores improves the prediction of 5-year incident AF. A risk stratification tool using age, sex, and serum metabolomics and AF-PRS provides excellent AF risk prediction. Mechanisms by which specific metabolites reflect AF risk require further exploration.
Study context
- Population
- UK Biobank participants with proton nuclear magnetic resonance spectroscopy measurements of 170 serum metabolites at enrollment
- Participants
- 240,628 UK Biobank participants
- Exposure
- The addition of metabolomics to the Cohorts for Heart and Aging Research in Genomic Epidemiology-AF (CHARGE-AF)+AF polygenic risk score (AF-PRS) model
Main finding
As reported in the abstract
Incident AF · During follow-up
participants developed atrial fibrillation (AF)
4174 (1.7%)
Observational data: associations, not effects.
Further findings
| Outcome | hazard ratio (per 1 SD log-transformed value) (95% CI) | P value | |
|---|---|---|---|
| Creatinine level and risk of AF · associated with increased risk | 1.01 (1.00–1.03) | ||
| 0.512Hazard ratio (log scale) |
Linoleic acid level and risk of AF
| Comparison | hazard ratio (CI) | P value | |
|---|---|---|---|
| linoleic acid level · associated with decreased risk of AF | 0.985 (0.979–0.994) | ||
| 0.512Hazard ratio (log scale) |
| Outcome | metabolomics | CHARGE-AF+AF-PRS model | A model using only age, sex, metabolomics, and AF-PRS | Estimate | P value |
|---|---|---|---|---|---|
| 5-year time-dependent area under the receiver operating characteristic curve · improved risk prediction | 0.789 (CI 0.776–0.802) | 0.755 (CI 0.738–0.772) | Not reported in the abstract | P < 0.05 | |
| 5-year time-dependent area under the receiver operating characteristic curve, validation set · fair risk prediction | Not reported in the abstract | Not reported in the abstract | 0.787 (CI 0.773–0.801) |
Stratification on the validation set
- NRI cases
- 11.1%
- NRI controls
- 3.1%
- IDI relative
- 11.6%
Original publication
Utilization of Serum Metabolomics and Polygenic Risk Scores in a Novel Risk Stratification Tool for the Prediction of Incident Atrial Fibrillation. Circ Arrhythm Electrophysiol. Published 19 February 2026. doi:10.1161/circep.125.013858
Summarised from the published abstract; every number is checked against it