Purpose: Warfarin is an oral anticoagulant associated with adverse reaction to drugs due to wide inter-and intra-individual dosage variability. Warfarin dosage has been related to non-genetic and genetic factors. CYP2C9 and VKORC1 gene polymorphisms affect warfarin metabolism and dosage. Due to the central role of populations’ ethnical and genetic origin on warfarin dosage variability, novel algorithms for Latin American subgroups are necessary to establish safe anticoagulation therapy. Patients and methods: We genotyped CYP2C9*2 (c.430C > T), CYP2C9*3 (c.1075A > C), CYP4F2 (c.1297G > A), and VKORC1 (-1639 G > A) polymorphisms in 152 Colombian patients who received warfarin. We evaluated the impact on the variability of patients’ warfarin dose requirements. Multiple linear regression analysis, using genetic and non-genetic variables, was used for creating an algorithm for optimal warfarin maintenance dose. Results: Median weekly prescribed warfarin dosage was significantly lower in patients having the VKORC1-1639 AA genotype and poor CYP2C9*2/*2,*2/*3 metabolizers than their wild-type counterparts. We found a 2.3-fold increase in mean dose for normal sensitivity patients (wild-type VKORC1/CYP2C9 genotypes) compared to the other groups (moderate and high sensitivity); 31.5% of the patients in our study group had warfarin sensitivity-related genotypes. The estimated regression equation accounted for 44.4% of overall variability in regard to warfarin maintenance dose. The algorithm was validated, giving 45.9% correlation (R 2 =0.459). Conclusion: Our results describe and validate the first algorithm for predicting warfarin maintenance in a Colombian mestizo population and have contributed toward the understanding of pharmacogenetics in a Latin American population subgroup.
CITATION STYLE
Galvez, J. M., Restrepo, C. M., Contreras, N. C., Alvarado, C., Calderón-Ospina, C. A., Peña, N., … Fonseca, D. J. (2018). Creating and validating a warfarin pharmacogenetic dosing algorithm for colombian patients. Pharmacogenomics and Personalized Medicine, 11, 169–178. https://doi.org/10.2147/PGPM.S170515
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