Evaluation of a warfarin dosing algorithm including CYP2C9, VKORC1, and CYP4F2 polymorphisms and non-genetic determinants for the Iranian population

BackgroundThe response to warfarin, as an oral anticoagulant agent, varies widely among patients from different ethnic groups. In this study, we tried to ascertain and determine the relationship between non-genetic factors and genetic polymorphisms with warfarin therapy; we then proposed a new warfarin dosing prediction algorithm for the estimation of drug sensitivity and resistance in the Iranian population.MethodsOverall, 200 warfarin-treated patients with stable doses were recruited, the demographic and clinical characteristics were documented, and genotyping was done using a sequencing assay.ResultsThe outcomes of our investigation showed that the genetic polymorphisms of VKORC1(-1639 G > A), CYP2C9*3, CYP2C9*2, amiodarone use, and increasing age were found to be related to a significantly lower mean daily warfarin dose. In contrast, the CYP4F2*3 variant and increased body surface area were linked with an increased dose of warfarin in the Iranians. Our descriptive model could describe 56.5% of the variability in response to warfarin. This population-specific dosing model performed slightly better than other previously published warfarin algorithms for our patient's series. Furthermore, our findings provided the suggestion that incorporating the CYP4F2*3 variant into the dosing algorithm could result in a more precise calculation of warfarin dose requirements in the Iranian population.ConclusionsWe proposed and validated a population-specific dosing algorithm based on genetic and non-genetic determinants for Iranian patients and evaluated its performance. Accordingly, by using this newly developed algorithm, prescribers could make more informed decisions regarding the treatment of Iranian patients with warfarin.