These findings provide new insight to the fact that the interindividual variability of methadone dosage requirement is polygenetic and cannot be explained by a single-gene effect.

Our results showed that the three loci, C1236T, G2677T and C3435T, jointly influenced the treatment response for epileptic patients. They should be regarded together as a complex polymorphic drug-response system. These findings suggest that examination of the haplotypes of the three loci could be useful in predicting drug resistance in epilepsy.

To search for the optimal dosage of phenytoin in patients with epilepsy based on the metabolic activities of CYP2C9 and CYP2C19 polymorphisms, a total of 169 patients receiving phenytoin treatment for more than 1 month were recruited. Phenytoin concentration, serum albumin, liver function tests, and renal function tests were measured. CYP2C9 and CYP2C19 polymorphisms were genotyped by PCR-RFLP analysis, and NONMEM models were built to evaluate factors that would affect phenytoin metabolism. Patients were divided into 5 groups according to genotyping results (G1 to G5). Compared with extensive metabolizers in both CYP2C9 and CYP2C19 (G1), the Vmax (mg/kg/d) was 8.29% and 36.96% lower in CYP2C19 poor metabolizers (G3) and CYP2C9 poor metabolizers (G4), respectively. For the patient who was identified as a poor metabolizer in both CYP2C19 and CYP2C9 (G5), the Vmax was 45.75% lower than that of G1. In respect to Km (mg/L), it was 15.09% higher in G3 and 27.36% higher in G4 compared with that in G1. The Km of G5 was 91.71% higher than that of G1. The results revealed that the CYP2C9 and CYP2C19 polymorphisms have dramatic effects on the population pharmacokinetic parameters of phenytoin, especially for CYP2C9. Based on the Vm and Km values obtained in this study, the recommended dose ranges for G1, G2, G3, G4, and G5 patients would be 5.5-7, 5-7, 5-6, 3-4, and 2-3 mg/kg/d, respectively.

These results are not a replication of the original study. They do, however, support the hypothesis that this polymorphism influences the clinical use of phenytoin. They also demonstrate the utility of using multiple phenotypes in pharmacogenetics studies, particularly when attempting to separate pharmacokinetic and pharmacodynamic effects. As the SCN1A polymorphism affects phenytoin pharmacodynamics, it is particularly useful to obtain data on serum levels in addition to dose because association of a pharmacodynamic variant may be stronger with serum levels than dose as the serum level may eliminate or reduce pharmacokinetic variability.

Our results indicated that 2677G>T and 3435C > T in the ABCB1 gene contributed to drug-resistant epilepsy. Although biologically plausible, the polymorphisms in NR1I2 investigated in the present study did not play a role in epilepsy treatment responses. Other unveiled genetic variants in the NR1I2 gene that may have the potential to affect ABCB1 gene expression are worth further investigation in future studies.

Although there was a limited sample size, the study identified genetic factors associated with VPA therapy optimization that has not been revealed, and provided useful information for individualized VPA therapy in epileptic patients.

The present study identified genetic factors associated with CBZ therapy optimization and provided useful information for individualized CBZ therapy in epileptic patients. Further studies in larger populations are needed to confirm our results.

Our findings demonstrated that human ABCB1 polymorphisms may alter the interactions between Pgp and substrates, and provided functional evidence for ABCB1 haplotypes-associated epilepsy treatment responses.