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A simulation of warfarin maintenance dose requirement using a pharmacogenetic algorithm in an ethnically diverse
Patrick Gladding1, John Mackay2,3, Irene Zeng4
1gladdip@ccf.org.
Aims:
Patient demographics and variant alleles in the CYP2C9 and VKORC1 genes account for 50% of the population variability in warfarin maintenance doses. These variant alleles occur in varying frequencies between racial groups and contribute to differences in mean dose requirements between these groups. We used a pharmacogenetic simulation to estimate warfarin maintenance doses in an ethnically diverse cohort.
Materials & Methods:
In total, 366 individuals with coronary disease, of mixed South Pacific and European ethnicity, were genotyped for the CYP2C9*2 (rs1799853), *3 (rs1057910) and the VKORC1*2 haplotype, -1639 G>A, (rs9923231). The cohort contained New Zealand Europeans (n = 287), Mãori (n = 49), Pacific Islanders (n = 21) and Chinese subjects (n = 9). SNPs were genotyped using the Sequenom (CA, USA) mass spectrometer. Body surface area, age, smoking status and genotype were entered into a modified pharmacogenetic algorithm with a target international normalized ratio of 2.5. Bootstrap analysis using the @RISK software v5.0, (Palisade Co., NY, USA) was performed to simulate a population of 1000 for each ethnic group.
Results:
Simulated warfarin doses were lower in Chinese subjects than New Zealand Europeans (Δ1.39 mg; 95% CI: 0.4-2.4; p = 0.006) owing to the high prevalence of the VKORC1*2 haplotype in Chinese subjects. Doses were higher in Pacific Islanders compared with New Zealand Europeans (Δ1.26 mg; 95% CI: 0.6-1.9; p = 0.0002) owing to the near absence of the CYP2C9 variant alleles. Simulated warfarin doses in Mãori patients were similar to those in European patients.
Conclusion:
This simulation study demonstrated differences in mean warfarin maintenance doses between ethnic groups in this cohort. Individualizing treatment regimens, using pharmacogenetics, may reduce ethnic disparities in treatment outcomes, particularly if differences can be appreciated at the genomic level.
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