| Title: | Predictive Accuracy of a Polygenic Risk Score-Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease |
| Journal: | JAMA |
| Published: | 18 Feb 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32068818/ |
| DOI: | https://doi.org/10.1001/jama.2019.22241 |
| URL: | https://jamanetwork.com/journals/jama/articlepdf/2761088/jama_elliott_2020_oi_190153.pdf |
Publication 13684
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Abstract
Importance: The incremental value of polygenic risk scores in addition to well-established risk prediction models for coronary artery disease (CAD) is uncertain.</p>
Objective: To examine whether a polygenic risk score for CAD improves risk prediction beyond pooled cohort equations.</p>
Design, Setting, and Participants: Observational study of UK Biobank participants enrolled from 2006 to 2010. A case-control sample of 15 947 prevalent CAD cases and equal number of age and sex frequency-matched controls was used to optimize the predictive performance of a polygenic risk score for CAD based on summary statistics from published genome-wide association studies. A separate cohort of 352 660 individuals (with follow-up to 2017) was used to evaluate the predictive accuracy of the polygenic risk score, pooled cohort equations, and both combined for incident CAD.</p>
Exposures: Polygenic risk score for CAD, pooled cohort equations, and both combined.</p>
Main Outcomes and Measures: CAD (myocardial infarction and its related sequelae). Discrimination, calibration, and reclassification using a risk threshold of 7.5% were assessed.</p>
Results: In the cohort of 352 660 participants (mean age, 55.9 years; 205 297 women [58.2%]) used to evaluate the predictive accuracy of the examined models, there were 6272 incident CAD events over a median of 8 years of follow-up. CAD discrimination for polygenic risk score, pooled cohort equations, and both combined resulted in C statistics of 0.61 (95% CI, 0.60 to 0.62), 0.76 (95% CI, 0.75 to 0.77), and 0.78 (95% CI, 0.77 to 0.79), respectively. The change in C statistic between the latter 2 models was 0.02 (95% CI, 0.01 to 0.03). Calibration of the models showed overestimation of risk by pooled cohort equations, which was corrected after recalibration. Using a risk threshold of 7.5%, addition of the polygenic risk score to pooled cohort equations resulted in a net reclassification improvement of 4.4% (95% CI, 3.5% to 5.3%) for cases and -0.4% (95% CI, -0.5% to -0.4%) for noncases (overall net reclassification improvement, 4.0% [95% CI, 3.1% to 4.9%]).</p>
Conclusions and Relevance: The addition of a polygenic risk score for CAD to pooled cohort equations was associated with a statistically significant, yet modest, improvement in the predictive accuracy for incident CAD and improved risk stratification for only a small proportion of individuals. The use of genetic information over the pooled cohort equations model warrants further investigation before clinical implementation.</p>
16 Keywords
- Adult
- Aged
- Case-Control Studies
- Coronary Artery Disease
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Genotype
- Humans
- Male
- Middle Aged
- Multifactorial Inheritance
- Predictive Value of Tests
- ROC Curve
- Risk
- Risk Assessment
10 Authors
- Joshua Elliott
- Barbara Bodinier
- Tom A. Bond
- Marc Chadeau-Hyam
- Evangelos Evangelou
- Karel G. M. Moons
- Abbas Dehghan
- David C. Muller
- Paul Elliott
- Ioanna Tzoulaki
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