Related Experiment Video
Updated: Jun 28, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
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.
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.
Abstract:
Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan-Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10-5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10-4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with PCE did not significantly outperform the PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.
Related Concept Videos
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Assessment of blood pressure in brachial artery(two-step method)
Pre-Procedural Guidelines for Assessing Blood Pressure

