Evaluating cardiovascular disease risk stratification using multiple-polygenic risk scores and pooled cohort...

Area of Science:

• Genetics
• Cardiology
• Public Health

Background:

• Cardiovascular disease (CVD) is a leading global cause of death.
• Genetic and environmental factors contribute to CVD development.
• Accurate risk prediction is crucial for effective CVD prevention.

Purpose of the Study:

• To evaluate the combined efficacy of multi-polygenic risk scores (wPRSsum) and Pooled Cohort Equations (PCE) for predicting CVD risk in Koreans.
• To assess the added value of genetic information to traditional clinical risk factors.

Main Methods:

• Longitudinal study of 7,612 Korean individuals over 17 years.
• Calculation of weighted sum of polygenic risk scores (wPRSsum) using PRS-CS.
• Recalibration and application of Pooled Cohort Equations (PCE).
• Analysis using Cox proportional hazards models and Kaplan-Meier analysis.

Main Results:

• wPRSsum showed a significant association with incident CVD (HR=1.15).
• The top 20% high-risk genetic group had a 1.50 HR.
• Combined wPRSsum and PCE enhanced CVD risk stratification, especially for high-risk individuals (HR=4.99).
• Predictive model showed slight improvement in males <55 years (C-index=0.640).

Conclusions:

• Integrating multi-polygenic risk scores with clinical tools like PCE enhances CVD risk stratification.
• This combined approach is valuable for identifying high-risk individuals for personalized CVD prevention.
• The findings support tailored strategies for CVD management in diverse populations.