Genome‐wide polygenic risk score, cardiometabolic risk factors, and type 2 diabetes mellitus in the Chinese population
Authors' conclusion
This study identified an ideally fitting PRS model for identifying and predicting the risk of T2D suitable for the Chinese population. The quantified proportional structure of genetic risk factors, cardiometabolic risk factors, and their interaction was detected, which elucidated the critical effect of genetic factors.
Study context
- Population
- Chinese adults, China Kadoorie Biobank
- Participants
- 93,488 adults
- Exposure
- Polygenic risk scores (PRS), cardiometabolic risk score (CRS) and PRS × CRS interaction in T2D risk
- Outcome
- T2D prediction and PRS–CRS interaction
Methodological detailspolygenic risk score analysis, China Kadoorie Biobank
- Polygenic risk score analysis
- China Kadoorie Biobank
Main finding
As reported in the abstract
Variance explained by ideally fitting PRS model (R2)
7.6%
Additive interaction between PRS and CRS: coefficient
28%
95% CI 0.20–0.36p < 0.001
R2 of T2D predictive model with CRS and PRS × CRS interaction
8.3%
Ratio of genetic : cardiometabolic : interaction effects in T2D etiological composition
67:16:17
Observational data: associations, not effects.
Original publication
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