Lipids & metabolic liver disease
Identification of growth differentiation factor 15 as an early predictive biomarker for metabolic dysfunction‐associated steatohepatitis: A nested case–control study of UK Biobank proteomic data
Authors' conclusion
GDF15 at baseline levels outperformed other individual circulating protein biomarkers for the early prediction of MASH. Our data suggest that GDF15 and the GDF15-based model may be used as easy-to-implement tools to identify patients with high risks of developing MASH at a mean lag time of over 10 years.
Study context
- Population
- UK Biobank participants with Olink proteomic, anthropometric and biochemical baseline data; MASH cases and age- and sex-matched controls
- Comparison
- Baseline circulating protein biomarkers for prediction of MASH
- Outcome
- Predictive accuracy of baseline CDCP1, FABP4, FGF21, GDF15, IL-6 and THBS2 for subsequent MASH diagnosis
- Follow-up
- Mean lag time of over 10 years
Methodological detailsage- and sex-matched controls, UK Biobank proteomic data, prospective analysis of baseline biomarkers
- Age- and sex-matched controls
- UK Biobank proteomic data
- Prospective analysis of baseline biomarkers
Main finding
As reported in the abstract
Prediction of MASH occurrence by baseline GDF15 · 5 and 10 years
GDF15 AUC at 5 years (best performing biomarker)
0.90
GDF15 AUC at 10 years
0.86
Observational data: associations, not effects.
Further findings
Four-biomarker model (GDF15, FGF21, IL-6, THBS2) · 5 and 10 years
- AUC at both 5 and 10 years
- 0.88
Protein-clinical model (4 biomarkers plus BMI, ALT, TC) · 5 and 10 years
- AUC at 5 years
- 0.92
- AUC at 10 years
- 0.89
Original publication
Identification of growth differentiation factor 15 as an early predictive biomarker for metabolic dysfunction‐associated steatohepatitis: A nested case–control study of UK Biobank proteomic data. Diabetes Obes Metab. Published 5 February 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →