Enhanced fracture risk prediction: a novel multi-trait genetic approach integrating polygenic scores of fracture-related traits
Main finding · Incident fractures, per SD of metaPGSResult — go to the resultHazard ratio 1.21 per SD 95% CI 1.18–1.25Authors' conclusion
The metaPGS is a promising approach for stratifying fracture risk in the European population, improving fracture risk prediction by combining genetic information from multiple fracture-related traits.
Study context
- Population
- European population
- Comparison
- Model with metaPGS vs base model of guideline-recommended clinical risk factors
- Outcome
- Incident fractures
Methodological detailselastic-net logistic regression, metaPGS combining 11 of 16 individual polygenic scores (PGSs)
- Elastic-net logistic regression
- metaPGS combining 11 of 16 individual PGSs
Main finding
Incident fractures, per SD of metaPGS
Hazard ratio
1.21 per SD
95% CI 1.18–1.25
metaPGS
HR 1.21 per SD (95% CI 1.18–1.25)
Per SD, as printed
As reported in the abstract
Further findings
C-index
| Outcome | metaPGS | PGS_FNBMD | PGS_TBBMD | Base model |
|---|---|---|---|---|
| Discrimination (c-index) | 0.644 | 0.640 | 0.644 | 0.638 |
Discrimination (c-index)
- Slightly higher but statistically non-significant c-index vs base model
Reclassification (net reclassification improvement (NRI), integrated discrimination improvement (IDI))
- Model with metaPGS improves reclassification of fracture vs base model
Original publication
Enhanced fracture risk prediction: a novel multi-trait genetic approach integrating polygenic scores of fracture-related traits. Osteoporos Int. Published 7 May 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →