Lipids & metabolic liver disease
A plasma metabolome‐derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank
Authors' conclusion
Integrating plasma metabolomics with routine indicators enhanced the predictive capacity for severe liver outcomes of NAFLD, which shows the potential benefits in disease risk stratification and precise interventions.
Study context
- Population
- UK Biobank participants with a positive fatty liver index (≥60) and plasma metabolomic profiles
- Participants
- 59,579 participants
- Comparison
- Metabolomics-integrated nomogram vs FIB-4, nonalcoholic fatty liver disease (NAFLD) fibrosis score and APRI
- Outcome
- Incident severe liver disease (cirrhosis, decompensated liver disease, hepatocellular carcinoma and/or liver transplantation)
- Follow-up
- 10-year
Methodological detailscohort, interpretable machine-learning framework, nomogram, Bonferroni correction
- Cohort
- Interpretable machine-learning framework
- Nomogram
- Bonferroni correction
Performance
As reported in the abstract
Prediction of 10-year SLD risk (AUC)
| Test or model | AUC |
|---|---|
| Nomogram | 0.841 (95% CI 0.800-0.881) |
| FIB-4 | 0.712 (0.662-0.763) |
| NFS | 0.659 (0.609-0.709) |
| APRI | 0.705 (0.652-0.759) |
AUC
Nomogram0.841 (95% CI 0.800-0.881)
FIB-40.712 (0.662-0.763)
NFS0.659 (0.609-0.709)
APRI0.705 (0.652-0.759)
Further findings
| Outcome | HR (95% CI) | |
|---|---|---|
| SLD risk, high-riskvs low-risk category by selected cutoffs | 25.71 (17.10–38.66) | |
| 0.050.21520Hazard ratio (log scale) |
Metabolites associated with incident severe liver disease (SLD) (Cox regression, after Bonferroni correction)
- Metabolites significantly associated with SLD risk
- 110 of 249
- Metabolites prioritised as predictors for metabolomic score
- 11
Original publication
A plasma metabolome‐derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank. Diabetes Obes Metab. Published 11 June 2025. doi:10.
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