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Polygenic risk score in comparison with C-reactive protein for predicting incident coronary heart disease
Aaron W Aday1, Minoo Bagheri2, Nataraja Sarma Vaitinadin3
1Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN, USA; Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Insights
Polygenic risk scores (PRS) show similar performance to high-sensitivity C-reactive protein (hsCRP) in predicting coronary heart disease (CHD) risk. PRS do not offer unique clinical utility beyond hsCRP in unselected populations.
Area of Science:
- Genetics
- Cardiovascular Disease Epidemiology
- Biomarkers
Background:
- Polygenic risk scores (PRS) are of interest for predicting coronary heart disease (CHD) risk.
- The clinical utility of PRS compared to conventional risk factors remains undemonstrated.
Purpose of the Study:
- To compare the predictive performance of PRS against high-sensitivity C-reactive protein (hsCRP) for incident CHD.
- To evaluate the clinical utility of PRS in established cohorts.
Main Methods:
- Utilized two cohorts: ARIC (N=13,113) and Framingham Offspring Study (FHS) (N=2,696) of European ancestry, free of baseline CHD.
- Assessed a validated PRS (>6.6 million SNPs) and hsCRP as primary predictors of incident CHD (myocardial infarction).
- Compared predictor performance using multivariable-adjusted Cox regression, adjusting for Pooled Cohort Equations, and assessed discrimination/reclassification via c-statistics and net reclassification improvement.
Main Results:
- Both PRS and hsCRP were significantly associated with incident CHD in both cohorts (p < 0.05).
- Hazard ratios per SD increment were similar for PRS and hsCRP in the ARIC cohort (1.38 vs 1.41).
- Neither PRS nor hsCRP significantly improved model discrimination or reclassification when added to the Pooled Cohort Equations alone.
Conclusions:
- Polygenic risk scores (PRS) demonstrated similar performance to hsCRP in predicting CHD risk across two independent cohorts.
- Findings suggest PRS do not offer unique clinical utility beyond the established, inexpensive hsCRP measure in unselected middle-aged populations.
Background And Aims:
Despite interest in the use of polygenic risk scores (PRS) for predicting coronary heart disease (CHD) risk, the clinical utility of PRS compared to conventional risk factors has not been demonstrated. We compared the performance of PRS with that of high-sensitivity C-reactive protein (hsCRP) in two well-established cohorts.
Methods:
The study population included individuals of European ancestry free of baseline CHD from ARIC (N = 13,113) and the Framingham Offspring Study (FHS) (N = 2,696). The primary predictors included a validated PRS consisting of >6.6 million single nucleotide polymorphisms and hsCRP. The outcome was incident CHD, defined as non-fatal or fatal myocardial infarction. We compared the performance of both predictors after adjusting for the Pooled Cohort Equations in multivariable-adjusted Cox regression models. We assessed discrimination and reclassification using c-statistics and net reclassification improvement.
Results:
Incident CHD occurred in 565 ARIC and 153 FHS participants. In multivariable-adjusted models, both PRS and hsCRP were associated with incident CHD (p < 0.05 in both cohorts). In models incorporating both predictors, strengths of association were similar. For instance, in ARIC, the hazard ratio per SD increment was 1.38 (95% CI, 1.27-1.50, p = 2.94 × 10-14) for PRS and 1.41 (1.30-1.55, p = 3.10 × 10-15) for hsCRP. Neither predictor significantly increased model discrimination or net reclassification when compared with models containing the Pooled Cohort Equations alone.
Conclusions:
In two independent cohorts, PRS performed similarly to hsCRP for the prediction of CHD risk. These findings suggest PRS does not have unique clinical utility beyond this widely-available, inexpensive measure of risk in unselected middle-aged populations.
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