Clinical Report: Family History and Polygenic Risk Scores in Cardiometabolic Disease Risk

Overview

This study evaluated the independent and combined contributions of family history (FH) and polygenic risk scores (PRS) to the incidence of four common cardiometabolic disorders (CMDs): type 2 diabetes (T2D), obesity, hypertension (HTN), and coronary artery disease (CAD). Using a large, ancestrally diverse cohort from the All of Us dataset, the study developed a quantitative family history score (FHS) and demonstrated that both FHS and PRS independently predict CMD risk, with PRS partially mediating the association between FH and disease.

Background

Cardiometabolic diseases, including T2D, obesity, HTN, and CAD, are leading causes of morbidity and mortality worldwide, with rising prevalence. These conditions result from complex interactions between genetic predisposition and environmental/lifestyle factors such as elevated BMI and physical inactivity. Family history has traditionally served as a clinical proxy for genetic risk but is limited by recall bias and family structure. Advances in genomics have enabled polygenic risk scores (PRS) to quantify genetic susceptibility more objectively. Prior studies have mostly focused on European populations and single traits, leaving gaps in understanding the joint effects of FH and PRS across diverse ancestries and multiple CMDs.

Data Highlights

The study analyzed 127,021 to 130,537 participants per CMD trait from the All of Us dataset, with approximately 75% European, 11% Admixed American, and 11% African ancestry. Incident CMD cases were identified using electronic health records with at least 6 months of follow-up. Family history was assessed via survey and quantified using a weighted family history score (FHS). PRSs were derived from genome-wide association studies. The study examined independent, joint, and mediation effects of FHS and PRS on CMD incidence across ancestry groups.

Key Findings

• Both family history score (FHS) and polygenic risk score (PRS) independently predict incident risk of T2D, obesity, HTN, and CAD.
• FHS captures familial burden by weighting affected first- and second-degree relatives, providing a continuous measure of genetic and environmental risk.
• PRS partially mediates the association between family history and CMD risk, indicating that genetic susceptibility explains some but not all familial risk.
• The combined use of FHS and PRS improves risk stratification beyond either measure alone across multiple ancestries.
• Associations were consistent across European, Admixed American, and African ancestry groups, supporting generalizability.

Clinical Implications

Incorporating both detailed family history and polygenic risk scores into clinical risk assessment can enhance prediction of cardiometabolic disease risk. Quantitative family history measures complement genetic risk captured by PRS, allowing for more precise stratification and potentially informing personalized prevention strategies. Clinicians should consider both familial and genetic factors when evaluating patient risk profiles for CMDs.

Conclusion

This study demonstrates that family history and polygenic risk scores independently and jointly contribute to cardiometabolic disease risk across diverse populations. Utilizing both measures can improve risk prediction and guide targeted interventions to reduce CMD burden.

References

1. All of Us Research Program -- Dataset and Study Design
2. Lu et al. 2022 -- Parental History and Polygenic Risk in Disease Prediction
3. FinnGen Study -- Family History and Polygenic Risk Across Diseases