Association of genetically predicted levels of circulating blood lipids with coronary artery disease incidence

Background and aims: Estimating the genetic risk of coronary artery disease (CAD) is now possible by aggregating data from genome-wide association studies (GWAS) into polygenic risk scores (PRS). Combining multiple PRS for specific circulating blood lipids could improve risk prediction. Here, we sought to evaluate the performance of PRS derived from CAD and blood lipids GWAS to predict the incidence of CAD.

Methods: This study included individuals aged between 40 and 69 from UK Biobank. We conducted GWAS for blood lipids measured by nuclear magnetic resonance in individuals without lipid-lowering treatments (n = 73,915). Summary statistics were used to derive PRS in the remaining participants (n = 318,051). A PRS_CAD was derived using the CARDIoGRAMplusC4D GWAS. Hazard ratios (HR) for CAD (n = 9017 out of 301,576; median follow-up: 12.6 years) were calculated per standard deviation increase in each PRS. Models' discrimination capacity and goodness-of-fit were evaluated.

Results: Out of 30 PRS, 27 were significantly associated with the incidence of CAD (p < 0.0017). The optimal combination of PRS included PRS for CAD, VLDL-C, total cholesterol and triglycerides. Discriminative capacities were significantly increased in the model including PRS_CAD and clinical risk factors (CRF) (C-statistic = 0.778 [0.773-0.782]) compared to the model with CRF only (C-statistic = 0.755 [0.751-0.760], difference = 0.022 [0.020-0.025]). Although the C-statistic remained similar when independent lipids PRS were added to the model with PRS_CAD and CRF (C-statistic = 0.778 [0.773-0.783]), the goodness-of-fit was significantly increased (chi-square test statistic = 20.18, p = 1.56e-04).

Conclusions: Although independently associated with CAD incidence, blood lipids PRS provide modest improvement in the predictive performance when added to PRS_CAD.