Type 2 diabetes (T2D), low-density lipoprotein-cholesterol (LDL-c), body mass index (BMI), blood pressure and smoking are established risk factors that play a causal role in coronary artery disease (CAD). Numerous common genetic variants associating with these and other risk factors have been identified, but their association with CAD has not been comprehensively examined in a single study. Our goal was to comprehensively evaluate the associations of established and emerging risk factors with CAD using genetic variants identified from Genome-wide Association Studies (GWAS).We tested the effect of 60 traditional and putative risk factors with CAD, using summary statistics obtained in GWAS. We approximated the regression of a response variable onto an additive multi-SNP genetic risk score in the Coronary Artery DIsease Genomewide Replication And Meta-analysis (CARDIoGRAM) consortium dataset weighted by the effect of the SNP on the risk factors.The strongest association with risk of CAD was for LDL-c SNPs (p = 3.96E-34). For non-established CAD risk factors, we found significant CAD associations for coronary artery calcification (CAC), Lp(a), LP-PLA2 activity, plaque, vWF and FVIII. In an attempt to identify independent associations between risk factors and CAD, only SNPs with an effect on the target trait were included. This identified CAD associations for Lp(a)(p = 1.77E-21), LDL-c (p = 4.16E-06), triglycerides (TG) (p = 1.94E-05), height (p = 2.06E-05), CAC (p = 3.13E-23) and carotid plaque (p = 2.08E-05).We identified SNPs associated with the emerging risk factors Lp(a), TG, plaque, height and CAC to be independently associated with risk of CAD. This provides further support for-ongoing clinical trials of Lp(a) and TG, and suggests that CAC and plaque could be used as surrogate markers for CAD in clinical trials.


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35 - 41


Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands; Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, The Netherlands. Electronic address: e.p.vaniperen@amc.uva.nl.