Abstract
Leukotrienes are arachidonic acid derivatives long known for their inflammatory properties and their involvement with a number of human diseases, most particularly asthma. Recently, leukotriene-based inflammation has also been shown to play an important role in atherosclerosis: ALOX5AP and LTA4H, both genes in the leukotriene biosynthesis pathway, have individually been shown to be associated with various cardiovascular disease (CVD) phenotypes. To assess the role of the leukotriene pathway in CVD pathogenesis, we performed genetic association studies of ALOX5AP and LTA4H in a family based study of early onset coronary artery disease (EOCAD) (GENECARD, 1,101 families) and in a non-familial dataset of EOCAD (CATHGEN, 656 cases and 405 controls). We found weak to moderate association between single nucleotide polymorphisms (SNPs) in ALOX5AP and LTA4H with EOCAD. The previously reported four-SNP haplotype (HapA) in ALOX5AP showed association with EOCAD in CATHGEN (P = 0.02), while controlling for age, race and CVD risk factors. HapK, the previously reported ten-SNP haplotype in LTA4H was associated with EOCAD in CATHGEN (P = 0.04). Another previously reported four-SNP haplotype in ALOX5AP (HapB) was not significant in our sample (P = 0.39). The overall lack of (or weak) association of single SNPs as compared with the haplotype results demonstrates the need for analyzing multiple SNPs within each gene in such studies. Interestingly, we detected an association of SNPs in ALOX5 (P < 0.05), the target of ALOX5AP, with CVD. Using a pathway-based approach, we also detected statistical evidence for interactions among ALOX5, ALOX5AP and LTA4H using RNA expression data from a collection of freshly harvested human aortas with varying degrees of atherosclerosis. The GENECARD families did not demonstrate evidence for linkage or association with ALOX5, ALOX5AP or LTA4H. Our results support a modest role for the leukotriene pathway in atherosclerosis pathogenesis, reveal important genomic interactions within the pathway, and suggest the importance of using pathway-based modeling for evaluating the genomics of atherosclerosis susceptibility.