Warfarin pharmacogenetics: development of a dosing algorithm for Omani patients.

Area of Science:

• Pharmacogenomics
• Clinical Pharmacology
• Genetics

Background:

• Warfarin dosing algorithms exhibit population-specific performance, impacting therapeutic efficacy and safety.
• Inter-patient variability in warfarin maintenance dose is substantial, necessitating personalized dosing strategies.

Purpose of the Study:

• To develop and validate a warfarin dosing algorithm tailored for the ethnically diverse Omani population.
• To investigate the influence of functional polymorphisms in CYP2C9, CYP4F2, and VKORC1 genes on warfarin dose requirements in Omani patients.

Main Methods:

• Genotyping of CYP2C9, CYP4F2, and VKORC1 gene variants in an admixed Omani cohort.
• Development of a multivariate regression model incorporating demographic, clinical, and pharmacogenetic variables.
• Comparison of the locally developed model's performance against the International Warfarin Pharmacogenetics Consortium (IWPC) model.

Main Results:

• A 64-fold inter-patient variability in warfarin dose was observed.
• Atrial fibrillation and homozygous CYP2C9 (*2/*3, *3/*3) and VKORC1 (GA, AA) genotypes were significant predictors of warfarin dose.
• The developed multivariate model explained 63% of warfarin dose variability, outperforming the IWPC model (34%).
• VKORC1 3673G>A polymorphism was the strongest predictor of warfarin dose variability (partial R²=0.45).

Conclusions:

• A locally developed warfarin dosing algorithm incorporating pharmacogenetic data significantly enhances dose prediction accuracy in the Omani population.
• Genetic variations, particularly in VKORC1 and CYP2C9, are critical determinants of warfarin dose requirements in this admixed cohort.
• Personalized warfarin dosing strategies based on pharmacogenetics are essential for optimizing patient outcomes.