Key result
Pharmacogenetic modeling showed target plasma S-warfarin concentration was significantly associated with VKORC1 genotype (P<0.05), and CYP2C9 genotype predicted 58% of concentration variation.
Why the study?
Does genotype-guided pharmacokinetic/pharmacodynamic modeling using CYP2C9 and VKORC1 genotypes predict target plasma S-warfarin concentrations in patients with stable INRs?
Observational (n=137)
Does genotype-guided pharmacokinetic/pharmacodynamic modeling using CYP2C9 and VKORC1 genotypes predict target plasma S-warfarin concentrations in patients with stable INRs?
p-value: p=<0.05
Combining CYP2C9 and VKORC1 genotype data with pharmacokinetic/pharmacodynamic modeling accurately predicts target S-warfarin concentrations for therapeutic INR, providing a decision-support tool for warfarin dosing.
May aid genotype-guided warfarin dosing in stable patients; hypothesis-generating and requires randomized validation before practice change.
BACKGROUND: The application of pharmacogenetic results requires demonstrable correlations between a test result and an indicated specific course of action. We developed a computational decision-support tool that combines patient-specific genotype and phenotype information to provide strategic dosage guidance. This tool, through estimating quantitative and temporal parameters associated with the metabolism- and concentration-dependent response to warfarin, provides the necessary patient-specific context for interpreting international normalized ratio (INR) measurements. METHODS: We analyzed clinical information, plasma S-warfarin concentration, and CYP2C9 (cytochrome P450, family 2, subfamily C, polypeptide 9) and VKORC1 (vitamin K epoxide reductase complex, subunit 1) genotypes for 137 patients with stable INRs. Plasma S-warfarin concentrations were evaluated by VKORC1 genotype (-1639G>A). The steady-state plasma S-warfarin concentration was calculated with CYP2C9 genotype-based clearance rates and compared with actual measurements. RESULTS: The plasma S-warfarin concentration required to yield the target INR response is significantly (P < 0.05) associated with VKORC1 -1639G>A genotype (GG, 0.68 mg/L; AG, 0.48 mg/L; AA, 0.27 mg/L). Modeling of the plasma S-warfarin concentration according to CYP2C9 genotype predicted 58% of the variation in measured S-warfarin concentration: Measured [S-warfarin] = 0.67(Estimated [S-warfarin]) + 0.16 mg/L. CONCLUSIONS: The target interval of plasma S-warfarin concentration required to yield a therapeutic INR can be predicted from the VKORC1 genotype (pharmacodynamics), and the progressive changes in S-warfarin concentration after repeated daily dosing can be predicted from the CYP2C9 genotype (pharmacokinetics). Combining the application of multivariate equations for estimating the maintenance dose with genotype-guided pharmacokinetics/pharmacodynamics modeling provides a powerful tool for maximizing the value of CYP2C9 and VKORC1 test results for ongoing application to patient care.
No takes yet. Share an insight, caveat, or question.
Linder et al. (2009) conducted an observational in Warfarin therapy (n=137). Pharmacogenetic decision-support tool (CYP2C9 and VKORC1 genotype-guided modeling) was evaluated on Association of plasma S-warfarin concentration required to yield target INR response with VKORC1 -1639G>A genotype (p=<0.05). Pharmacogenetic modeling showed target plasma S-warfarin concentration was significantly associated with VKORC1 genotype (P<0.05), and CYP2C9 genotype predicted 58% of concentration variation.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: