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.

BMC Medicine
|November 6, 2022
PubMed

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.
Abstract

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