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

Yi Seul Park1, Hye-Mi Jang1, Ji Hye Park1

  • 1Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea.

Frontiers in Genetics
|April 12, 2024
PubMed

Insights

Combining genetic risk scores with clinical assessments improves cardiovascular disease (CVD) risk stratification. This approach helps identify high-risk individuals for personalized prevention strategies.

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.

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