To examine recent methodological and translational advances in polygenic risk score (PRS) development across diverse populations, particularly in relation to cardiovascular and cardiometabolic diseases, while addressing the limitations faced by underrepresented groups.
Approach:
Key Findings:
Most PRSs were derived from predominantly European-ancestry datasets, leading to limited performance in underrepresented populations.
Performance discrepancies in PRSs are influenced by allele frequencies, linkage disequilibrium, environmental context, and ancestry-specific effects.
Admixed populations, such as those in Brazil, highlight the need for models that account for local ancestry and internal heterogeneity.
Emerging multi-ancestry frameworks and ancestry-aware models have improved predictive performance, particularly for coronary artery disease (CAD).
Progress in PRS development varies across traits, with CAD showing the most maturity and obesity and atrial fibrillation being less developed.
Interpretation:
Admixed and underrepresented populations should be viewed as essential contexts for building robust and clinically generalizable PRS models, with implications for improving patient care.
Limitations:
Current PRS methodologies still face challenges in calibration and context dependence, particularly in diverse populations.
Evidence for implementation in diverse populations remains incomplete, highlighting the need for further research.
Conclusion:
The next phase of precision cardiovascular medicine will require PRS-informed risk assessments that are calibrated, interpretable, and clinically useful across diverse populations, necessitating ongoing research.
Federal prosecutors allege that a Florida physician and research staff fabricated clinical trial records that were submitted into database systems used to evaluate investigational drugs.
