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Objective: To evaluate the feasibility of clinical application for genetic based dosing algorithm in the predication of warfarin maintenance dose in Chinese population., Methods: The clinical data were collected and blood samples harvested from a total of 126 patients undergoing heart valve replacement. The genotypes of VKORC1 and CYP2C9 were determined by melting curve analysis after PCR. They were divided randomly into the study and control groups. In the study group, the first three doses of warfarin were prescribed according to the predicted warfarin maintenance dose while warfarin was initiated at 2.5 mg/d in the control group. The warfarin doses were adjusted according to the measured international normalized ratio (INR) values. And all subjects were followed for 50 days after an initiation of warfarin therapy., Results: At the end of a 50-day follow-up period, the proportions of the patients on a stable dose were 82.4% (42/51) and 62.5% (30/48) for the study and control groups respectively. The mean durations of reaching a stable dose of warfarin were (27.5 ± 1.8) and (34.7 ± 1.8) days and the median durations were (24.0 ± 1.7) and (33.0 ± 4.5) days in the study and control groups respectively. Significant differences existed in the durations of reaching a stable dose between the two groups (P = 0.012). Compared with the control group, the hazard ratio (HR) for the duration of reaching a stable dose was 1.786 in the study group (95%CI 1.088 - 2.875, P = 0.026)., Conclusion: The predicted dosing algorithm incorporating genetic and non-genetic factors may shorten the duration of achieving efficiently a stable dose of warfarin. And the present study validates the feasibility of its clinical application.

Objective: To investigate the effect of genetic polymorphisms in VKORC1, CYP2C9, GGCX, EPHX1, APOE genes on inter-individual variation in warfarin maintenance dose., Methods: Two hundred and forty-nine patients with stable warfarin dose were enrolled in this study, and the clinical data and blood samples of the patients were collected. Genotypes for the 5 genes were determined by using PCR and denaturing high performance liquid chromatography (DHPLC) assay. The warfarin maintenance doses were compared among patients with different genotypes of the 5 genes, and a warfarin stable dosing algorithm was derived based on genetic and non-genetic factors., Results: Of the 5 genes, VKORC1, CYP2C9 and GGCX were associated with warfarin stable dose. The multiple linear regression analysis indicated that VKORC1, CYP2C9 and GGCX genes, age and weight, had significant influence on inter-individual variation in warfarin stable dose, which contributed 30.2%, 22.8%, 1.5%, 4.7% and 6.7% respectively. The warfarin stable dosing algorithm acquired from the optimal regression model could explain 57.8% variation in warfarin dose., Conclusion: This study suggested that genetic factors are the major determinants of the warfarin maintenance dose, and warfarin stable dosing algorithm may be useful for helping clinicians to prescribe warfarin with greater safety and efficiency.

Introduction: It has been widely accepted that genetic factors were the major sources of the variation in warfarin dose. This study is intended to investigate whether the 3261G>A variation in GGCX gene influences stable warfarin dose in Chinese patient population., Materials and Methods: A total of 217 patients with stable warfarin dose were enrolled. Genomic DNA was extracted from each subject and the genotype of GGCX 3261G>A was determined by using of denaturing high-performance liquid chromatography (DHPLC). Least significant difference tests (LSDs) were used to compare dose with genotypes. Analysis of variance (ANVOA) was used to calculate the proportion of warfarin dose that could be explained by variation in genotype., Results: In the total of 217 subjects, 84 patients (38.7%) were GG homozygote, whereas 117 (53.9%) were GA heterozygote and 16 (7.4%) were AA homozygote. Patients with the GGCX 3261AA genotype had a significantly higher average daily maintenance dose (3.39 ± 1.40 mg) than those with the GG genotype (2.69 ± 1.07 mg; P=0.027), and GGCX 3261G>A explains 2.3% of the univariate warfarin dose variance., Conclusion: GGCX 3261G>A may affect warfarin dose requirements, and showed a small but significant effect on warfarin dose in a Chinese patient population., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Objectives: To develop a warfarin-dosing algorithm that could be combined with pharmacogenomic and demographic factors, and to evaluate its effectiveness in a randomized prospective controlled clinical trial., Methods: A pharmacogenetics-based dosing model was derived using retrospective data from 266 Chinese patients and multiple linear regression analysis. To prospectively validate this model, 156 patients with an operation of heart valve replacement were enrolled and randomly assigned to the group of pharmacogenetics-guided or traditional dosing for warfarin therapy. All patients were followed up for 50 days after initiation of warfarin therapy. The log-rank test was compared with the time-to-event (Kaplan-Meier) curves. Cox proportional hazards-regression model was used to assess the hazard ratio of the time to reach stable dose., Results: The linear regression model derived from the pharmacogenomic model correlated with 54.1% of warfarin dosing variance. The final multiple linear regression model included age, body surface area, VKORC1, and CYP2C9 genotype. The study showed that the hazard ratio for the time to reach stable dose was 1.932 for the traditional dosing group versus the model-based group and a close and highly significant relationship was observed to exist between the predicted and the actual warfarin dose (R=0.454)., Conclusion: A pharmacogenetics-based dosing algorithm has been developed for improvement in the time to reach the stable dosing of warfarin. This model may be useful in helping the clinicians to prescribe warfarin with greater safety and efficiency.

Background: Polymorphisms in VKORC1 (vitamin K epoxide reductase complex subunit 1) and CYP2C9 (cytochrome P450 2C9) genes are considered the major genetic factors modulating warfarin dose requirement. As a result, a rapid and economic method for genotyping patients for predicting warfarin dose could be useful in clinical applications., Methods: In this study, we developed and validated a melting temperature (T(m))-shift genotyping assay for detection of VKORC1 C1173T and CYP2C9 A1075C polymorphisms by using SYBR Green-based multiplex allele-specific PCR and consequent melting curve analysis. In this T(m)-shift genotyping assay, a GC-tail was incorporated into one of the two allele-specific primers to increase the melting temperature of PCR product, such that both alleles can be differentially detected simultaneously at their respective melting curve patterns. In total, 100 randomly selected samples of both VKORC1 and CYP2C9 genes from each genotype group determined by melting curve were validated by direct DNA sequencing and denaturing high-performance liquid chromatography (DHPLC) analysis., Results: There was 100% concordance between the results of DNA sequencing and T(m)-shift genotyping, and 99% concordance between the results of DHPLC assay and T(m)-shift genotyping., Conclusions: This allele-specific PCR assay is convenient, inexpensive and will be useful for VKORC1 and CYP2C9 genotyping in a clinic laboratory.