To evaluate the associations of family history (FH), degree of FH, and polygenic risk scores (PRS) with the incidence of common cardiometabolic disorders (CMDs) in a diverse population, emphasizing the need for inclusivity in genetic research.
Key Findings:
Family history is a strong predictor of CMDs, but its utility is limited by factors like family size and recall bias, highlighting the need for improved assessment methods.
Polygenic risk scores provide an objective measure of genetic risk and can enhance risk stratification beyond family history alone, offering a more nuanced understanding of risk.
The study found that both FH and PRS contribute independently and interactively to CMD susceptibility, suggesting a complex interplay between genetic and familial factors.
Interpretation:
The findings suggest that integrating FH and PRS can improve risk prediction for CMDs, highlighting the importance of both genetic and familial factors in assessing individual risk, with potential implications for personalized medicine.
Limitations:
The study primarily focused on a cohort of European ancestry, which may limit generalizability to other populations.
Potential biases in self-reported family history data and reliance on electronic health records for phenotype definitions may affect the results.
Conclusion:
Combining family history and polygenic risk scores may provide a more comprehensive understanding of individual risk for cardiometabolic disorders, warranting further research in diverse populations.
