Abstract 2180: Joint Effects of Genetic Variants From Multiple Pathways on Risk of Premature Coronary Artery Disease
Background: Much of the genetic basis of coronary artery disease (CAD) remains unexplained. Progress is occurring using both candidate gene and genome-wide association studies (GWAS). Emphasis on pathobiologic pathways for atherothrombosis promises to facilitate this effort. CorGen tested the hypothesis that a multigenic, multipathway genetic risk score (GRS) could predict angiographic CAD.
Methods: Subjects with premature CAD and controls were selected from the Intermountain Heart Angiographic Registry and DNA bank. Single nucleotide polymorphisms (SNPs) at 56 loci were tested in a discovery set of angiographic cases (n=1,003) and controls (n=510). These SNPs were tagging SNPs discovered for 6 lipoprotein metabolic genes and/or replicated literature SNPs diversified among 4 pathobiologic pathways. Twenty-eight SNPs met nominal criteria for lipid and CAD associations or GWAS replication, and 10 of these contributed independently to CAD discrimination (i.e., ApoF rs11171814, CETP rs1800775, CETP rs11076175, CETP rs289715, LIPC rs6082, 9p21 rs2383206, F2 rs1799963, PSRC1 rs599839, CETP rs3764261, ApoC1 rs4420638). These 10 were carried forward for testing in a validation set of 915 cases and 522 controls. Count GRS was calculated by summing the number of high risk alleles. To calculate the weighted GRS, discovery set β-coefficients for each SNP were multiplied by the number of risk alleles, summed, and normalized.
Results: The simple count GRS10 discriminated angiographic CAD in the validation set across the GRS range (p=6×10−5), odds ratio=1.12 (95% CI 1.6 –1.18) per high risk allele (median count, 11, range= 6 –17). Weighting GRS10 further improved on CAD discrimination (OR=1.93 [CI, 1.42–2.63], Q4 vs Q1, p=1.3×10−5). GRS contributed independently to standard risk factors in multivariable modeling and significantly modified Framingham risk classification (net reclassification index=0.132, p=0.007).
Conclusions: CorGen demonstrates the incremental value of combining individual SNPs into a polygenic, multipathway GRS to discriminate angiographic CAD. This GRS shows promise to better identify populations of younger adults at increased CAD risk, illuminate pathways of disease pathogenesis, and target novel treatment approaches.