OBJECTIVES: The dose of carbamazepine required to achieve optimal seizure control varies widely from patient to patient. We investigated polymorphic variants in various genes involved in the pharmacokinetics and pharmacodynamics of carbamazepine in an effort to identify predictors of maintenance dose. METHODS: : A total of 70 patients with epilepsy (49% were males; median age, 34 years; range, 14-72 years) who had benefited (>50% reduction in seizure frequency for at least 12 months) from treatment with carbamazepine monotherapy were included in the analysis. Known variants in drug-metabolizing enzyme genes, including those encoding cytochrome P450s, uridine 5'-diphosphate-glycosyltransferase, and microsomal epoxide hydrolase, together with a sodium channel polymorphism in SCN2A, were screened using polymerase chain reaction-restriction fragment length polymorphism or direct sequencing. Associations between demographic and genetic variables and carbamazepine dose were identified by univariate and multivariate regression analyses. RESULTS: All genotype frequencies were consistent with Hardy-Weinberg equilibrium (P > 0.05). No single demographic or genetic variable was of sufficient strength to independently influence carbamazepine dosing requirements. However, a multivariate model, incorporating patient age and specific genotypes (c.337T>C, c.416A>G) of the EPHX1 gene encoding microsomal epoxide hydrolase, revealed a significant association with the maintenance dose of carbamazepine (r(2) = 0.362, P= 0.002). CONCLUSIONS: This proof-of-principle study suggests that genetic variants in EPHX1 can be used to predict maintenance doses of carbamazepine. A large-scale prospective investigation of genetic influences on drug dosing strategies in epilepsy, with specific focus on whole gene variability for those proteins involved in the pharmacokinetics and pharmacodynamics of antiepileptic agents, is warranted.
OBJECTIVES: The dose of carbamazepine required to achieve optimal seizure control varies widely from patient to patient. We investigated polymorphic variants in various genes involved in the pharmacokinetics and pharmacodynamics of carbamazepine in an effort to identify predictors of maintenance dose. METHODS: : A total of 70 patients with epilepsy (49% were males; median age, 34 years; range, 14-72 years) who had benefited (>50% reduction in seizure frequency for at least 12 months) from treatment with carbamazepine monotherapy were included in the analysis. Known variants in drug-metabolizing enzyme genes, including those encoding cytochrome P450s, uridine 5'-diphosphate-glycosyltransferase, and microsomal epoxide hydrolase, together with a sodium channel polymorphism in SCN2A, were screened using polymerase chain reaction-restriction fragment length polymorphism or direct sequencing. Associations between demographic and genetic variables and carbamazepine dose were identified by univariate and multivariate regression analyses. RESULTS: All genotype frequencies were consistent with Hardy-Weinberg equilibrium (P > 0.05). No single demographic or genetic variable was of sufficient strength to independently influence carbamazepine dosing requirements. However, a multivariate model, incorporating patient age and specific genotypes (c.337T>C, c.416A>G) of the EPHX1 gene encoding microsomal epoxide hydrolase, revealed a significant association with the maintenance dose of carbamazepine (r(2) = 0.362, P= 0.002). CONCLUSIONS: This proof-of-principle study suggests that genetic variants in EPHX1 can be used to predict maintenance doses of carbamazepine. A large-scale prospective investigation of genetic influences on drug dosing strategies in epilepsy, with specific focus on whole gene variability for those proteins involved in the pharmacokinetics and pharmacodynamics of antiepileptic agents, is warranted.
Authors: Yogita Ghodke Puranik; Angela K Birnbaum; Susan E Marino; Ghada Ahmed; James C Cloyd; Rory P Remmel; Ilo E Leppik; Jatinder K Lamba Journal: Pharmacogenomics Date: 2013-01 Impact factor: 2.533
Authors: Elizabeth M J Lee; Karen Xu; Emma Mosbrook; Amanda Links; Jessica Guzman; David R Adams; Elise Flynn; Elise Valkanas; Camillo Toro; Cynthia J Tifft; Cornelius F Boerkoel; William A Gahl; Murat Sincan Journal: Genet Med Date: 2016-06-02 Impact factor: 8.822