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The effect of genetic and nongenetic factors on warfarin dose variability in Qatari population

Abstract

The objective of this study is to estimate the prevalence of VKORC1, CYP2C9, and CYP4F2 genetic variants and their contribution to warfarin dose variability in Qataris. One hundred and fifty warfarin-treated Qatari patients on a stable dose and with a therapeutic INR for at least three consecutive clinic visits were recruited. Saliva samples were collected using Oragene DNA self-collection kit, followed by DNA purification and genotyping via TaqMan Real-Time-PCR assay. The population was stratified into derivation and validation cohorts for the dosing model. The minor allele frequency (MAF) of VKORC1 (−1639G>A) was A (0.47), while the MAF’s for the CYP2C9*2 and *3 and CYP4F2*3 were T (0.12), C (0.04) and T (0.43), respectively. Carriers of at least one CYP2C9 decreased function allele (*2 or *3) required lower median (IQR) warfarin doses compared to noncarriers [24.5 (14.5) mg/week vs. 35 (21) mg/week, p < 0.001]. Similarly, carriers of each additional copy of (A) variant in VKORC1 (−1639G>A) led to reduction in warfarin dose requirement compared to noncarriers [21(7.5) vs. 31.5(18.7) vs. 43.7(15), p < 0.0001]. CYP4F2*3 polymorphism on the other hand was not associated with warfarin dose. Multivariate analysis on the derivation cohort (n = 104) showed that a dosing model consisting of hypertension (HTN), heart failure (HF), VKORC1 (−1639G>A), CYP2C9*2 & *3, and smoking could explain 39.2% of warfarin dose variability in Qataris (P < 0.001). In the validation cohort (n = 45), correlation between predicted and actual warfarin doses was moderate (Spearman’s rho correlation coefficient = 0.711, p < 0.001). This study concluded that VKORC1 (−1639G>A), CYP2C9*2 & *3 are the most significant predictors of warfarin dose along with HTN, HF and smoking.

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Correspondence to Hazem Elewa.

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Bader, L., Mahfouz, A., Kasem, M. et al. The effect of genetic and nongenetic factors on warfarin dose variability in Qatari population. Pharmacogenomics J 20, 277–284 (2020). https://doi.org/10.1038/s41397-019-0116-y

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