Genetic determinants of response to aspirin and warfarin and development of silicon nanowire based genotyping

Abstract

Chronic diseases such as cardiovascular diseases and colorectal cancer are the leading cause of mortality worldwide. Commonly used drugs such as aspirin and warfarin are shown to effective at reducing the risk of chronic diseases but have a narrow therapeutic window and are associated with adverse drug reactions, particularly, hemorrhage. Identification of pharmacogenetic markers such as single nucleotide polymorphisms (SNPs) that could help deliver personalized dose could help improve the risk-benefit ratio. Furthermore, development of a rapid point of care genotyping device consisting of a pharmacogenetic SNP panel for aspirin and warfarin could help implement personalized medicine in the clinical setting. Analysis of candidate SNPs in aspirin’s pharmacokinetic and pharmacodynamic pathways was carried out to explain variation in aspirin’s colorectal chemopreventive efficacy using two large population based case-control datasets. Associations and interactions were tested using logistic regression models and meta-analysis of the 2 datasets. A novel sitespecific association for rs1799853 (OR=0.73, 95% CI=0.60-0.90, P=0.003) and rs1105879 (OR=1.16, 95% CI=1.02-1.32, P=0.03) with colon cancer risk was observed. Furthermore, stratification by aspirin use showed increased risk of colorectal cancer in aspirin users but not in non-users carrying variant allele of the SNPs rs4936367 and rs7112513 in PAFAH1B2 gene and rs2070959 and rs1105879 in UGT1A6 gene (Pinteraction<0.05 for all). These results provide insight into aspirin’s differential chemopreventive efficacy and the neoplastic transformation of cells in colon and rectum. Utility of clinically validated pharmacogenetic dosing algorithms consisting of three warfarin dose associated SNPs from the European population needs to tested in the Gujarati Indians, an Indian sub-population. Dose prediction accuracy of the algorithms was compared between Gujarati Indian and European population. Mean squared difference of both pharmacogenetic algorithms was higher in Gujarati Indian compared to European population (Klein et al 2009, 216.3 v/s 160.7, P=0.05; Gage et al 2008, 170.6 v/s 143.2, P=0.07). Poor prediction accuracy could be explained by the presence of study subjects requiring dose for target INR range 2.5-3.5 and low frequency of the VKORC1 rs9923231 variant, which is the most important genetic determinant of warfarin dosing in Europeans. Therefore, the SNP panel and dosing algorithms developed from European populations cannot be assumed to have utility in the Gujarati Indian population. Finally, to help develop a rapid, point-of care, silicon nanowire (SiNW) based SNP genotyping device, a panel of isothermal melting probes were designed to genotype three warfarin dose associated SNPs. Testing of hybridization and washing conditions to have optimal hybridization kinetics between the probe and target DNA and high target sequence specificity was carried out using custom designed microarray platform. Accurate genotype calls for all 3 SNPs in 2 anonymised samples using empirically optimized hybridization and washing conditions was carried out successfully. Current work highlighted associations between probe characteristics and hybridization parameters, which would be useful in designing and testing probes on the SiNW platform. Identification, validation and testing of clinical utility of population specific pharmacogenetic markers along with development and deployment of ultra-rapid point of care genotyping technologies could help deliver personalized risk-benefit ratio for aspirin and warfarin.