Marginal role for 53 common genetic variants in cardiovascular disease prediction

<jats:sec> <jats:title>Objective</jats:title> <jats:p>We investigated discrimination and calibration of cardiovascular disease (CVD) risk scores when genotypic was added to phenotypic information. The potential of genetic information for those at intermediate risk by a phenotype-based risk score was assessed.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>Data were from seven prospective studies including 11 851 individuals initially free of CVD or diabetes, with 1444 incident CVD events over 10 years' follow-up. We calculated a score from 53 CVD-related single nucleotide polymorphisms and an established CVD risk equation ‘QRISK-2’ comprising phenotypic measures. The area under the receiver operating characteristic curve (AUROC), detection rate for given false-positive rate (FPR) and net reclassification improvement (NRI) index were estimated for gene scores alone and in addition to the QRISK-2 CVD risk score. We also evaluated use of genetic information only for those at intermediate risk according to QRISK-2.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>The AUROC was 0.635 for QRISK-2 alone and 0.623 with addition of the gene score. The detection rate for 5% FPR improved from 11.9% to 12.0% when the gene score was added. For a 10-year CVD risk cut-off point of 10%, the NRI was 0.25% when the gene score was added to QRISK-2. Applying the genetic risk score only to those with QRISK-2 risk of 10%–&lt;20% and prescribing statins where risk exceeded 20% suggested that genetic information could prevent one additional event for every 462 people screened.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusion</jats:title> <jats:p>The gene score produced minimal incremental population-wide utility over phenotypic risk prediction of CVD. Tailored prediction using genetic information for those at intermediate risk may have clinical utility.</jats:p> </jats:sec>