To evaluate the effectiveness of multi-ancestry polygenic risk scores (PRSs) in predicting type 2 diabetes across diverse ancestry groups, highlighting their potential to improve risk assessment.
Key Findings:
Multi-ancestry PRSs showed larger effect sizes than single-ancestry PRSs across all ancestry groups, with specific odds ratios provided.
Odds of type 2 diabetes increased significantly with higher PRS values, particularly in the 97.5th percentile.
Predictive performance varied by ancestry, with European and East Asian populations showing the strongest discrimination.
Higher PRS values were associated with earlier onset of type 2 diabetes and increased odds of diabetes-related complications.
Interpretation:
Multi-ancestry PRSs can enhance risk stratification for type 2 diabetes and its complications, particularly in diverse populations, but disparities in predictive performance exist due to overrepresentation of European ancestry in GWAS data, which may limit applicability.
Limitations:
Single-nucleotide polymorphism effect estimates are still heavily influenced by large European cohorts, potentially skewing results.
Discrete ancestry categories may not fully capture genetic diversity, especially in admixed populations, which could affect the generalizability of findings.
The study focused on predictive performance rather than clinical implementation, leaving the impact on patient outcomes uncertain.
Conclusion:
Validated multi-ancestry PRSs can improve risk stratification for type 2 diabetes onset and complications across diverse ancestries, with ongoing trials assessing their integration into routine care to ensure practical application.
