Polygenic Risk Score–Enhanced Risk Stratification of Coronary Artery Disease in Patients With Stable Chest Pain. (June 2021) - Christiansen, Morten Krogh; Winther, Simon; Nissen, Louise; Vilhjálmsson, Bjarni Jóhann; Frost, Lars; Johansen, Jane Kirk; Møller, Peter Loof; Schmidt, Samuel Emil; Westra, Jelmer; Holm, Niels Ramsing; Jensen, Henrik Kjærulf; Christiansen, Evald Høj; et al.
Abstract : Background: Polygenic risk scores (PRSs) are associated with coronary artery disease (CAD), but the clinical potential of using PRSs at the single-patient level for risk stratification has yet to be established. We investigated whether adding a PRS to clinical risk factors (CRFs) improves risk stratification in patients referred to coronary computed tomography angiography on a suspicion of obstructive CAD. Methods: In this prespecified diagnostic substudy of the Dan-NICAD trial (Danish study of Non-Invasive testing in Coronary Artery Disease), we included 1617 consecutive patients with stable chest symptoms and no history of CAD referred for coronary computed tomography angiography. CRFs used for risk stratification were age, sex, symptoms, prior or active smoking, antihypertensive treatment, lipid-lowering treatment, and diabetes. In addition, patients were genotyped, and their PRSs were calculated. All patients underwent coronary computed tomography angiography. Patients with a suspected ≥50% stenosis also underwent invasive coronary angiography with fractional flow reserve. A combined end point of obstructive CAD was defined as a visual invasive coronary angiography stenosis >90%, fractional flow reserve <0.80, or a quantitative coronary analysis stenosis >50% if fractional flow reserve measurements were not feasible. Results: The PRS was associated with obstructive CAD independent of CRFs (adjusted odds ratio, 1.8 [95% CI, 1.5–2.2] per SD). The PRS had an area under the curve of 0.63 (0.59–0.68), which was similar to that for age and sex. Combining the PRS with CRFs led to a CRF+PRS model with area under the curve of 0.75 (0.71–0.79), which was 0.04 more than the CRF model ( P =0.0029). By using pretest probability (pretest probability) cutoffs at 5% and 15%, a net reclassification improvement of 15.8% ( P =3.1×10 −4 ) was obtained, with a down-classification of risk in 24% of patients (211 of 862) in whom the pretest probability was 5% to 15% based on CRFs alone. Conclusions: Adding a PRS improved risk stratification of obstructive CAD beyond CRFs, suggesting a modest clinical potential of using PRSs to guide diagnostic testing in the contemporary clinical setting. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02264717. Abstract : Supplemental Digital Content is available in the text.