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Published on: August 9, 2024
Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease
Austin King1, Lang Wu2, Hong-Wen Deng3
1Department of Statistics, Florida State University, Tallahassee, FL, USA.
Insights
Integrating polygenic risk scores (PRS) improves coronary artery disease (CAD) prediction in White British individuals. This PRS-enhanced model offers better risk classification than traditional methods, aiding in CAD screening.
Area of Science:
- Cardiovascular Disease Research
- Genetics and Genomics
- Predictive Modeling
Background:
- The clinical utility of polygenic risk scores (PRS) for coronary artery disease (CAD) prediction alongside existing risk models is debated.
- This study investigates if an integrated PRS enhances CAD prediction beyond current guideline-recommended pooled cohort equations.
Purpose of the Study:
- To evaluate the effectiveness of an integrated polygenic risk score in improving coronary artery disease risk prediction.
- To compare the predictive performance of pooled cohort equations, an integrated PRS, and a PRS-enhanced model.
Main Methods:
- An observational study utilized UK Biobank data from 291,305 White British participants (2006-2010).
- A case-control sample (9499 CAD cases and controls) was used for PRS tuning.
- Risk prediction was assessed in a separate cohort of 272,307 individuals with follow-up to 2020, analyzing discrimination and reclassification.
Main Results:
- The PRS-enhanced pooled cohort equation achieved a C-statistic of 0.753, outperforming the pooled cohort equation (0.718) and integrated PRS (0.640).
- Adding the integrated PRS to the pooled cohort equation resulted in a net reclassification improvement of 0.093, correctly reclassifying 14.2% of incident CAD cases to higher risk.
Conclusions:
- Integrating a polygenic risk score significantly improves the predictive accuracy and clinical risk classification for incident coronary artery disease in the White British population.
- These findings support the potential of integrated PRS to enhance CAD risk prediction and screening strategies within this demographic.
Background:
The value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. METHODS: An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case-control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold.
Results:
In the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634-0.646), 0.718 (95% CI, 0.713-0.723), and 0.753 (95% CI, 0.748-0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and - 0.023 (95% CI, - 0.025 to - 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category.
Conclusions:
Addition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.
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