title: Pharmacogenetics in warfarin therapy
Creators: name: Ab Ghani, Azizah
Publisher: name: University of Liverpool Repository
Year: 2015

description: Warfarin is a challenging drug to dose accurately, especially during the initiation phase because of its narrow therapeutic range and large inter-individual variability. Therefore, the aim of this thesis was to investigate the use of pharmacogenetics and clinical data to improve warfarin therapy. Genetic variants in cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) are known to influence warfarin dose. Therefore we developed a pharmacogenetic dosing algorithm to predict warfarin stable dose prospectively in a British population based on 456 patients who started warfarin in a hospital setting and validated it in 262 retrospectively recruited patients from a primary care setting. The pharmacogenetic algorithm which included CYP2C9*2, CYP2C9*3 and VKORC1-1693 together with body surface area, age and concomitant amiodarone use, explained 43% of warfarin dose variability. The mean absolute error of the dose predicted by the algorithm was 1.08 mg/day (95% CI 0.95-1.20). 49.6% of patients were predicted accurately (predicted dose fell within 20% of the actual dose). The HAS-BLED score, a bleeding risk score has recently been suggested for use in the management of patients with atrial fibrillation. We validated HAS-BLED performance in predicting major bleeding using a prospective cohort with 6 months follow-up (n=482) (c-statistic 0.80 95% CI (0.71-0.90). Factors significantly associated with major bleeding in our cohort (p≤0.1) were concurrent amiodarone use, labile INR, concurrent clopidogrel use, bleeding predisposition, concurrent aspirin use and CYP2C9*3. Adding a genetic covariate (CYP2C9*3) to the HAS-BLED score did not significantly improve its performance in predicting major bleeding. Considering CYP2C9*3 is a rare allele, our study was underpowered and requires further investigation in a larger cohort. A retrospective study of 97 Caucasian children was conducted to gain greater understanding of the factors that affect warfarin anticoagulant control and response in children. Results from multiple regression analysis of genetic and non-genetic factors showed that indication for treatment (Fontan or non-Fontan group), VKORC1 -1693, and INR group explained 20.8% of variability in proportion time in which INR measurements fell within the target range (PTTR); CYP2C9*2 explained 6.8% of the variability in INR exceeding target range within the first week of treatment; CYP2C9*2, VKORC1 -1693, age and INR group explained 41.4% of warfarin dose variability and VKORC1 -1693 explained 8.7% of haemorrhagic events. The contributions of CYP2C9 and VKORC1 polymorphism were small in the above outcomes. We therefore went onto explore other genetic markers using genome-wide scanning. Two SNPs on chromosome 5, rs13167496 and rs6882472 were found to be significantly associated at a genome-wide significance level with PTIR. However, none of SNPs were significantly associated with warfarin stable dose, INR values exceeding the target range within the first week of treatment and bleeding complications. Because of our small sample size, these findings will need to be validated in a replication cohort. Finally, we have validated and evaluated the performance of Genie HyBeacon®, a point of care therapy (POCT) instrument to genotype 135 samples for CYP2C9*2, CYP2C9*3 and VKORC1 -1693. We showed that the instrument accuracy was &gt;98% (agreement with ABI Taqman® genotyping), it was relatively simple to use and had a good turn-around time (1.6 hours) making it suitable for clinical use. In conclusion, the results presented in this thesis demonstrate how knowledge of pharmacogenetics may help in assessing improvement in the quality of care of patients on warfarin. However, for personalized medicine to be widely adopted in clinical practice, payers need evidence of clinical- and cost-effectiveness. How such evidence is produced and evaluated varies in different healthcare settings, which further increases the challenge of implementing personalised medicine into the clinic.