Abstract 3546: Genetic Variables Contributing To Aspirin Resistance: A Genome-Wide Association Study

Background: Aspirin reduces risk of vascular events by 15-30% in patients with ischemic stroke, but recurrent vascular events occur in up to 45% on aspirin therapy. Understanding factors contributing to aspirin resistance is important in secondary stroke prevention. Several clinical and genetic factors have been implicated. We sought to use GWAS data from the Vitamin Intervention for Stroke Prevention (VISP) trial to evaluate genetic factors that may contribute to aspirin resistance. Methods: We conducted a case-control analysis in participants in the VISP study. We included all individuals on aspirin at the time of enrollment. Patients on combination antiplatelet and/or anticoagulation therapy were excluded. We conducted a survival analysis of 960 individuals using Cox proportional hazards model with multiple clinical, demographic and genetic covariates. Demographic factors include sex, age and 10 principle components from population structure analysis. A total of 11 clinical factors and 14 genes (319 single nucleotide polymorphisms (SNPs)) were analyzed ( Table ). Results: The top SNPs were rs12603582 in the integrin beta 3 (platelet glycoprotein IIIa) gene (ITGB3) on Chromosome 17 (p=0.0056); rs9472831 in the phospholipase A2 gene (PLA2G7) on Chromosome 6 (p=0.0079), and rs5985 in the coagulation factor XIII gene (F13A1) on Chromosome 6 (p=0.0080). Of the 16 SNPs with p-values less than 0.05, 5 were in phospholipase A2, group IVA (PLA2G4A), 2 were in the coagulation factor XIII (F13B), 3 were in F13A1, 1 was in PLA2G7, and 5 were in ITGB3.x Conclusion: No individual genetic factor was significantly associated with recurrent stroke or MI in the VISP population after correction for multiple comparisons. Our study had limited power to detect associations due to a small sample size. A Bayesian network has been used to develop a predictive model for stroke in sickle cell patients. We will apply a similar approach to develop a model for genetic and clinical variables ( Table ). We also will expand our sample by inclusion of cases from the Women’s Health Initiative. With further study and analysis we hope to identify additional genetic factors that may predispose patients to aspirin resistance.