Prediction of warfarin dose reductions in Puerto Rican patients, based on combinatorial CYP2C9 and VKORC1 genotypes.

BACKGROUND

The influence of CYP2C9 and VKORC1 polymorphisms on warfarin dose has been investigated in white, Asian, and African American populations but not in Puerto Rican Hispanic patients.

OBJECTIVE

To test the associations between genotypes, international normalized ratio (INR) measurements, and warfarin dosing and gauge the impact of these polymorphisms on warfarin dose, using a published algorithm.

METHODS

A retrospective warfarin pharmacogenetic association study in 106 Puerto Rican patients was performed. DNA samples from patients were assayed for 12 variants in both CYP2C9 and VKORC1 loci by HILOmet PhyzioType assay. Demographic and clinical nongenetic data were retrospectively collected from medical records. Allele and genotype frequencies were determined and Hardy-Weinberg equilibrium (HWE) was tested.

RESULTS

Sixty-nine percent of patients were carriers of at least one polymorphism in either the CYP2C9 or the VKORC1 gene. Double, triple, and quadruple carriers accounted for 22%, 5%, and 1%, respectively. No significant departure from HWE was found. Among patients with a given CYP2C9 genotype, warfarin dose requirements declined from GG to AA haplotypes; whereas, within each VKORC1 haplotype, the dose decreased as the number of CYP2C9 variants increased. The presence of these loss-of-function alleles was associated with more out-of-range INR measurements (OR = 1.38) but not with significant INR >4 during the initiation phase. Analyses based on a published pharmacogenetic algorithm predicted dose reductions of up to 4.9 mg/day in carriers and provided better dose prediction in an extreme subgroup of highly sensitive patients, but also suggested the need to improve predictability by developing a customized model for use in Puerto Rican patients.

CONCLUSIONS

This study laid important groundwork for supporting a prospective pharmacogenetic trial in Puerto Ricans to detect the benefits of incorporating relevant genomic information into a customized DNA-guided warfarin dosing algorithm.