Title: Effects of polymorphisms in six candidate genes on phenytoin maintenance therapy in Han Chinese patients
Chin-Chuan Hung, Ph.D.1, 2; Hsiao-Ching Huang, MS 1; Yun-Han Gao, MS 1; Wei-Lun Chang, MS 1; Jia-Ling Ho, MS 1; Mu-Han Chiou, MS 3; Yow-Wen Hsieh, Ph.D.1,
2# ; Horng-Huei Liou, MD., Ph.D. 4*#
1Department of Pharmacy, College of Pharmacy, China Medical University;2Department of Pharmacy, China Medical University Hospital, Taichung, Taiwan; 3 Graduate Institute of Drug Safety, College of Pharmacy, China Medical University; 4 Department of Neurology
and Pharmacology, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan.
*Corresponding Author: Horng-Huei Liou, MD., Ph.D.
Department of Neurology and Pharmacology, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan.
No. 7, Chung-San South Road, Taipei, Taiwan 100 e-mail: hhl@ntu.edu.tw
TEL:+886-2-23123456 ext 88325 FAX: +886-2-23418395
Abstract
Objective The present study aimed to investigate the associations between variants in pharmacokinetic and pharmacodynamic related genes with the dosages, concentrations and concentration-to-dose ratios (CDRs) of phenytoin (PHT).
Methods and results Eleven genetic polymorphisms in the six candidate genes were detected in 269 epileptic patients under maintenance PHT monotherapy by realtime-PCR and PCR-RFLP. Results of bi-variate analysis demonstrated that among tested polymorphisms, carriers of the variant CYP2C9*3 tended to require significantly lower maintenance PHT dosages than wild-type carriers (p<0.0001); on the other hand, carriers of the variant CYP2C9*3 or CYP2C19*3 revealed significantly higher CDRs than wild-type carriers (p<0.004). In further multivariate analysis, variants in SCN1A, CYP2C9, CYP2C19 and ABCB1 genes were significantly associated with CDRs of PHT under adjustment of age, gender and epilepsy classifications (adjusted r2=20.07 %).
Conclusion The results of present study indicated that polygenic analysis may provide useful information in PHT therapy optimization.
Executive Summary
Aim
‧The present study aimed to identify the multiple genetic effect and the interactions between genes regarding influences on PHT dosages and concentration-to-dose ratios (CDRs) in epilepsy patients.
Results and conclusion
‧In the pharmacokinetic related genes, CYP2C9*3 and CYP2C19*3 were demonstrated to be significantly associated with PHT dosages and CDRs.
‧The multivariate regression model demonstrated that SCN1A, CYP2C9, CYP2C19 and ABCB1genes were interactively associated with the CDRs of PHT.
Introduction
Phenytoin (5,5-diphenylhydantoin; PHT) is a widely prescribed antiepileptic drug effectively against generalized tonic-clonic and partial seizures [1]. With large interindividual variation in metabolism and narrow therapeutic index, patients may experience side effects or uncontrolled seizures during optimization of PHT dosages. Therefore, how to safely and effectively prescribe dosages of PHT is an important issue in clinical practice.
PHT is mainly metabolized by cytochrome P450 enzymes and only 2-5 % unchanged form is excreted by kidney [2, 3]. CYP2C9 is responsible for about 90% metabolism of PHT, while CYP2C19 accounts for less than 10 % [2, 3]. These two enzymes metabolize PHT to a mixture of (R)- and (S)-stereoisomers of the inactive metabolite 5-(4’)-hydroxyphenyl-5-phenylhydantoin (p-HPPH) [4]. Both CYP2C9 and CYP2C19 are polymorphic genes and several studies have demonstrated significant association between CYP2C9/CYP2C19 genotypes and PHT dosing variations [5-12]. Although the effects of single nucleotide polymorphisms (SNPs) in
CYP2C9 and CYP2C19 genes on PHT metabolism were robust, clinical application
was limited due to the low correlation between CYP2C9/CYP2C19 genotypes and interindividual variations of PHT therapy [13, 14]. This phenomenon indicated that other genetic variants and non-genetic factors may also contribute to the
interindividual variability of PHT therapy.
PHT primarily targets on voltage-gated sodium channels and binds to the α-subunits [15, 16]. Human brain sodium channels comprise a central large α-subunit and two auxiliary small β-subunits [17]. There are several isoforms of α-subunits expressed in the brain, Nav1.1, 1.2, 1.3 and 1.8, which is encoded by SCN1A, 2A, 3A and 8A gene, respectively [18]. A functional polymorphism in SCN1A gene, SCN1A IVS5-91G>A, was demonstrated to be associated with maximum dose of carbamazepine and PHT [19, 20]. However, the association between SCN1A IVS5-91G>A and maximum dose of carbamazepine was not detected in other replication studies [21-23]. Another gene encoded the sodium channel α-subunit, SCN2A, was reported to be associated with epilepsy treatment response [24, 25], therefore, may affect dosage requirement of PHT therapy.
PHT is also a substrate of P-glycoprotein (P-gp) and multidrug resistant-associated protein 2 (MRP2) [26-29]. Human P-glycoprotein is encoded by ABCB1 gene, which is a highly polymorphic gene [30]. Among the identified polymorphisms in ABCB1 gene, c.1236C>T, c.2677G>T/A and c.3435C>T were most commonly studied [31]. Several studies have demonstrated that these genetic variants may affect plasma concentrations of drugs those are substrates of P-gp, such as cyclosporine, doxorubicin and digoxin [32]. However, in terms of effects of ABCB1 genetic variants
on epilepsy treatment outcomes, conflicting results were reported by different studies [33-38]. Since phenytoin is transported by human P-gp, maintenance doses and concentrations of PHT may be affected by these variants.
As for the human MRP2, it was found to be overexpressed in the human epileptogenic brain tissues [39]. Human MRP2 is encoded by ABCC2 gene, and recent studies have identified several ABCC2 genetic variants [40]. The ABCC2 -24C>T was associated with plasma concentrations of methotrexate, while ABCC2 1249G>A showed effect on clearance of talinolol and associated with the occurrence of neurological side effects of carbamazepine [41]. Therefore, as a substrate of MRP2, maintenance dosages and concentrations of PHT may be affected by genetic variants of ABCC2 gene.
To investigate the genetic variants associated with PHT maintenence dosages and steady-state concentrations, we included candidate genes related to pharmacokinetics and pharmacodynamics of PHT treatment efficacy. The present study aimed to identify the polygenic effect and the interactions between genes regarding influences on PHT maintenance dosages, concentrations and CDRs in epileptic patients.
Methods Subjects
This study was approved by the Ethics Committee of the National Taiwan University Hospital and whole blood samples for genotyping were collected after written informed consents were obtained. Electroencephalogram and magnetic resonance imaging (MRI) brain scans were performed in every included patient. The classifications of epilepsies and epileptic syndromes were conducted according to the guidelines of ILAE 1989 [42]. Clinical information, such as gender, weight (kg), age, epilepsy classification, etiology, PHT maintenance dose (mg/kg/day), PHT serum concentration at maintenance dose (mg/L), AST, ALT and albumin levels, were recorded in each patient. The inclued patients did not use any other AED, and non-AED that may interact with PHT was also avoided for safety considerations. The maintenance dose of PHT was defined as the dosage which has not been changed for at least one year under good compliance and good seizure control. Good seizure control was defined as freedom from seizures for a minimum of three times the longest preintervention interseizure interval (determined from seizures occurring within the past 12 months) or 12 months, whichever is longer [43]. Compliance of patients to the medication was checked by counting the pills remained in the drug bag during every visit. All of the recuited patients were achieved over 90% compliance.
Concentration-dose ratios (CDRs) were calculated by dividing the mean steady state PHT serum concentration by the PHT daily dose. The steady-state PHT serum concentrations were measured by the fluorescence polarization immunoassay commercialized kit (FPIA; Abbott Laboratories®) according to the manufacture protocol and performed by hospital technicians.
A total of 269 patients with epilepsy under phenytoin monotherapy treatment (168 men, 101 women, age 41.72 ± 0.72 (mean ± SD)) were included and each of them reached a maintenance dose for at least one year (PHT dose: 315.48 ± 86.47 mg/day; concentration: 15.13 ± 6.62 mg/L). Of these patients, 187 subjects (69.51 %) were localization-related epilepsies (Table 1). As normal controls, 190 healthy volunteers (96 men, 94 women, age 40.1± 0.92) were genotyped to be used as an evidence of the identical genetic background and provided information of whether the genotypic distributions were all consistent with Hardy-Weinberg equilibrium proportions in patients and healthy controls. All patients and controls were recruited from the same center and unrelated. The ethnic background of patients and controls was Han Chinese and it was ascertained by patient self-identity.
Genotyping
As for PHT pharmacokinetic and pharmacodynamic related genes, it is known that several variants in SCN1A, SCN2A, CYP2C9, CYP2C19, ABCB1, and ABCC2
genes would affect the basic expression or function of the target protein [5-12, 19, 20, 22, 24, 44]. Although UGT1A1 is the enzyme responsible for the conjugation of the PHT oxidative metabolites [45], the activity of UGT1A1 has not been reported to be relevant to PHT concentrations. Therefore, variants in UGT1A1 gene were not included. Among these variants, it has been shown that SCN1A IVS5-91 G>A
(rs3812718), c.3184A>G (rs2298771), SCN2A c.56G>A (rs17183814), CYP2C9*3
(rs1057910), CYP2C19*2 (rs4244285), CYP2C19*3 (rs4986893), ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582), c.3435C>T (rs1045642), ABCC2 c.-24C>T (rs717620) and c.1249G>A (rs2273697) were the eleven polymorphisms with higher allele frequency of variant in Han Chinese according to the NCBI database. Hence, these eleven variants were selected for investigation in our study. Genomic DNA was isolated from peripheral blood sample by the QIAamp DNA Mini Kit. Genotyping of
SCN1A IVS5-91 G>A (rs3812718), c.3184A>G (rs2298771), SCN2A c.56G>A
(rs17183814), CYP2C9*3 (rs1057910), CYP2C19*2 (rs4244285), ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582), ABCC2 c.-24C>T (rs717620) and c.1249G>A (rs2273697) were carried out using the Applied Biosystem Assay on Demand reagents (Applied Biosystem, Foster City, Calif.). PCRs were performed in 20 μl volume, containing allele-specific probes, assay-specific primers, TaqMan Universal PCR Master Mix, and genomic DNA (50 ng). Genotypes analyses were
estimated by SDS 2.2 software (Applied Biosystems).
Genotyping of CYP2C19*3 (rs4986893) and ABCB1 c.3435C>T (rs1045642) were conducted by using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). PCRs were performed in 25 ul volumes containing 50 ng genomic DNA, 2.5 μM/μL dNTPs, 10 μM/μL each primers, 1×reaction Buffer, and 5 unit Taq DNA polymerase (Fermentas, Inc.). PCR conditions were denaturation at 94 °C for 5 min followed by 35 cycles at 94 °C for 20 s, annealing at 60°C for 20 s, 72 °C for 20 s with a final elongation step at 72 °C for 5 min. The restriction enzymes used in the genotyping CYP2C19*3 (rs4986893) and ABCB1 c.3435C>T (rs1045642) were Bam HI and Mbo I, respectively. The genotyping methods were validated by direct sequencing.
Statistical Analysis
Prior to statistical analysis, the normality and the homogeneity of variance of data set, such as PHT dosages, concentrations and CDRs, were tested. The CDRs of PHT were not demonstrated normal distribution before natural logarithm transformation. Therefore, lnCDRs of PHT were applied in the statistical analysis. For the association between dosages, concentrations and lnCDRs with each genetic polymorphism were analyzed by one way ANOVA followed by Bonferroni post hoc test with parametric analyses. The standardized linkage disequilibrium values (D’)
were calculated for measurement of the linkage disequilibrium (LD) among these loci [46, 47]. A p-value less than 0.05 was considered to indicate statistical significance. Compliance with Hardy-Weinberg equilibrium for the genotype frequency distributions were performed in patients and healthy controls by the χ2 test. The power estimate was performed using GPower 3.1 and the sample size of the present study had a maximum power of 80% to detect the effect size of 0.15 at p<0.05. Analysis of association between a genotype and the PHT dosages, concentrations or lnCDRs, the adjusted α level was prescribed at 0.0015 (0.05/33) for the 33 comparisons among the eleven genetic polymorphisms. Similar association analysis was also carried out for alleles. As for genotype combinations (diplotypes) analysis, the adjusted α level was prescribed at 0.0055 (0.05/9) for diplotypes composed of SCN1A IVS5-91 G>A (rs3812718) and c.3184A>G (rs2298771), as well as diplotypes composed of
CYP2C9*3 (rs1057910), CYP2C19*3 (rs4986893) and CYP2C19*2 (rs4244285).
Further multivariate regression models were conducted to detect the joint effect of SCN1A, SCN2A, CYP2C9, CYP2C19, ABCB1, and ABCC2 polymorphisms on maintenance dosages, steady-state concentrations and lnCDRs of PHT with the adjustment for the epilepsy syndromes, age and weight. Doing Multifactor Dimensionality Reduction (MDR) in addition to regression analysis is highly recommended to know the direction and nature of interaction between variables [48].
However, the MDR method is used as a alternative to logistic regression and the dependent variable should be categorical. Thus, this MDR method was not performed in the present study. The dependent variables in this study, such as maintenance PHT dosages, steady-state PHT concentrations and lnCDRs of PHT, were continuous variables. As for independent variables in this study, age and weight were continuous variables while the epilepsy syndromes were classified into two groups, one was temporal lobe epilepsy and the other was not temporal lobe epilepsy, coded 1 and 0, respectively. The genotypes of the included polymorphisms were coded as dummy variables to avoid the assumption of inheritance models. The model selection procedures were undergone based on the backward elimination and the partial F tests [49]. All data analyses were performed using SAS version 9.1.3 (SAS Inc, Cary, NC, USA).
Results
There were 301 epileptic patients were initially enrolled and thirty-two patients were dropped out because of non-compliance or change to another AED. As a result, 269 epileptic patients under PHT maintenance therapy remained in the present study and were further genotyped. The allele and genotype frequencies of the SCN1A,
SCN2A, CYP2C9, CYP2C19, ABCB1, and ABCC2 polymorphic loci for patients
under PHT maintenance mono-therapy and healthy controls were listed in Table 2 and Table 3. The genotypic distributions were all consistent with Hardy-Weinberg equilibrium proportions and genotype frequencies were not significantly different between patients and healthy controls. Significant linkage disequilibrium were detected between SCN1A IVS5-91 G>A (rs3812718) and c.3184A>G (rs2298771), among CYP2C9*3 (rs1057910), CYP2C19*3 (rs4986893) and CYP2C19*2
(rs4244285), and among ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582), and c.3435C>T (rs1045642) as indicated by high values of D’ (>0.8; all p-values < 0.0001).
Association of genetic variants with PHT maintenance Dosages
The bi-variate analysis analyses revealed that among the tested genetic polymorphisms, only CYP2C9*3 (rs1057910) showed significant associations with the PHT maintenance dosages (mg/kg/day) (Table 2 and Table 3). Carriers of the
variant CYP2C9*3 allele tended to require lower PHT maintenance dosages than noncarriers (p<0.0001, uncorrected) and the heterozygous variant carriers also seemed to require lower PHT maintenance dosages (p<0.0001, uncorrected). These genetic associations remained significant after Bonferroni’s correction as described in the statistical methods.
Diplotype analyses demonstrated that diplotypes composed of CYP2C9*3 (rs1057910), CYP2C19*3 (rs4986893) and CYP2C19*2 (rs4244285) demonstrated significant association with maintenance dosages of PHT, whereas the diplotypes composed of SCN1A IVS5-91 G>A (rs3812718) and c.3184A>G (rs2298771), or
ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582), and c.3435C>T
(rs1045642) showed no effect on PHT maintenance dosages. The comparisons of diplotype pattern distributions revealed that patients with AC/GG/GA and AC/GG/GG diplotypes composed of CYP2C9*3 (rs1057910), CYP2C19*3
(rs4986893) and CYP2C19*2 (rs4244285) were more likely to require lower maintenance dosages of PHT (both p<0.0005, uncorrected; Table 4). These diplotype associations remained significant after Bonferroni’s correction as described in the statistical methods.
Association of genetic variants with PHT Steady-state concentrations and Concentration-Dose Ratios
None of the tested genetic polymorphisms showed significant association with the steady-state PHT concentrations (Table 2 and Table 3). As for the association between tested genetic variants and lnCDRs of PHT, CYP2C9*3 (rs1057910) and
CYP2C19*3 (rs4986893) significantly affected lnCDRs of PHT. Carriers of the
variant CYP2C9*3 allele tended to have higher lnCDRs than noncarriers (p<0.001, uncorrected) and the heterozygous carriers also seemed to have higher lnCDRs (p<0.001, uncorrected). Similar results were observed in carriers of CYP2C19*3. Carriers of the variant CYP2C19*3 allele were more likely to have higher lnCDRs than noncarriers (p<0.003, uncorrected) and the heterozygous carriers seemed to have higher lnCDRs as well (p<0.004, uncorrected).
Diplotype analyses demonstrated that diplotypes composed of CYP2C9*3 (rs1057910), CYP2C19*3 (rs4986893) and CYP2C19*2 (rs4244285) demonstrated significant association with lnCDRs of PHT, whereas the diplotypes composed of
SCN1A IVS5-91 G>A (rs3812718) and c.3184A>G (rs2298771), or ABCB1
c.1236C>T (rs1128503), c.2677G>T/A (rs2032582), and c.3435C>T (rs1045642) showed no effect on lnCDRs of PHT. The comparisons of diplotype pattern distributions revealed that patients with AA/GA/GA and AC/GG/GG diplotypes composed of CYP2C9*3 (rs1057910), CYP2C19*3 (rs4986893) and CYP2C19*2 (rs4244285) were more likely to have higher PHT lnCDRs (both p<0.002,
uncorrected; Table 4). These diplotype associations remained significant after Bonferroni’s correction as described in the statistical methods.
Regression model analysis
Multivariate regression analysis was applied to evaluate the combined effect of pharmacokinetic and pharmacodynamic related genes on lnCDRs of PHT under adjustment of cofactors, such as epilepsy syndromes, weight, and age. Among the included factors, genetic variants in SCN1A, CYP2C9, CYP2C19 and ABCB1 genes demonstrated significant effect on lnCDR of PHT. The most fitted model indicated that SCN1A IVS5-91 G>A (rs3812718), CYP2C9*3 (rs1057910), CYP2C19*3
(rs4986893), CYP2C19*2 (rs4244285), ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582) and c.3435C>T (rs1045642) showed synergistic effect on the lnCDRs of PHT (adjusted r2=20.07 %; Table 5).
Discussion
The present study demonstrated that among the included polymorphic loci,
CYP2C9*3 was significantly associated with PHT maintenance dosages and CYP2C9*3 and CYP2C19*3 showed significant effects on the lnCDRs of PHT in
single SNP analyses. With adjustment of cofactors, SCN1A IVS5-91 G>A,
CYP2C9*3, CYP2C19*3, CYP2C19*2, ABCB1 c.1236C>T, c.2677G>T/A and
c.3435C>T showed synergistic effect on the lnCDRs of PHT in the multivariate model. This was a proof-of-principle study and the polygenic effect regarding drug target and drug metabolism related genes on CDRs of PHT has not been reported before. Findings of the present study may provide clinicians information regarding how to solve the dosing difficulty in PHT maintenance therapy. The value of CDR could be taken as normalization of concentration by dose, and it could also be used as an indicator of intrinsic clearance of PHT. By the multiple regression model purposed by this study, clinicians could estimate PHT CDR of individual patient based on their genotype and this is the future vision of pharmacotherapy.
The correlation between CYP2C9/CYP2C19 genotypes and PHT maintenance dosage, concentration and toxicity has been reported by multiple independent studies [7-11]. Previous studies mainly focused on the association of CYP2C9 c.430C>T
636G>A (CYP2C19*3) with PHT therapy optimization [7-11]. Despite significant effect of CYP2C9/CYP2C19 genotypes on PHT dosages, a limited proportion of PHT dosing variation could be explained. A recent study illustrated that variants in the promoter region of CYP2C9 (CYP2C9*1B), in linkage with CYP2C19*2, may provide additional 10% explanation of clinical PHT dosing variation in Caucasians [6]. Since CYP2C19*2 is a common variant in Han Chinese population, we included
CYP2C19*2 to represent this block. Our results demonstrated that diplotypes composed of CYP2C9*3, CYP2C19*3 and CYP2C19*2 were significantly associated with dosages and CDRs of PHT maintenance therapy. In terms of the efflux transporters, ABCB1 and ABCC2 are two biological plausible genes may show effect on PHT maintenance therapy. Although PHT is a substrate of these two efflux transporters and variants in ABCB1 and ABCC2 were demonstrated to influent plasma concentrations of some substrates, the effect of common SNPs in ABCB1 and ABCC2 on PHT maintenance therapy was not detected in the single gene analysis of the present study. However, when clinical predictors, such as age, gender, height, weight, and clinical classifications of epilepsy syndromes, were taken into account in the multivariate model, ABCB1 c.1236C>T, c.2677G>T/A and c.3435C>T together with other genes showed significant effect on PHT maintenance therapy in the polygenic model.
As for the pharmacodynamic related genes, the effect of SCN1A IVS5-91 G>A, c.3184A>G and SCN2A c.56G>A on the dosages of sodium channel-blocking AEDs or drug resistance has been evaluated in several studies [20, 21, 23-25, 50]. Inconsistent results have been reported regarding whether SCN1A IVS5-91 G>A influences the dosage requirement or treatment responses of sodium channel blocking agents, such as carbamazepine and PHT [20-23, 50]. Several reasons may explain these discrepancies, including different ethnic background, different drug profiles (monotherapy or not), and different clinical factors (age, gender, epilepsy syndromes and etiologies). The majority of patients in the present study were symptomatic epilepsy may have lead to differential dose requirement. Therefore, the classifications of epilepsy were included in the multiple regression model to justify the differential dosage requirement resulted from different types of epilepsy. In the most fitted model, whether patient was a TLE case would significantly influence PHT lnCDR. The limited influence of a SNP is also a possible reason. Since determination of the response or dosage requirement of a drug is biologically polygenic, the impact of a single variant may be confounded by effects of other genes and clinical information as well. Therefore, the multivariate model was applied in the present study to improve the clinical correlation and increase the proportion of variation explained. None of the included variant in SCN1A and SCN2A showed significant effect on PHT maintenance
therapy in single gene analyses, however, when it comes to the multivariate model,
SCN1A IVS5-91 G>A contributed significant effect on lnCDRs of PHT in a polygenic
way. The molecular mechanism of the possible association between SCN1A IVS5-91 G>A and the efficacy of sodium channel-blocking AEDs has been reported [19]. The variant A allele has been demonstrated to cause an alternative splicing and as a consequence, the expression proportions of neonate and adult exon 5 transcripts in adult brain tissue would be changed. Individuals with the wild-type G allele expressed 30-40% neonatal form in the SCN1A transcripts, whereas those with the variant A allele expressed less than 1% [19].
There were inter-ethnic differences in the frequencies of genetic variants in
SCN1A, CYP2C9 and CYP2C19 genes. According to the HapMap database and a
recent study [45], the minor allele frequencies of SCN1A IVS5-91G>A were lower in Africans but similar in Caucasians and Indians as compared with the present study. The minor allele frequencies of CYP2C9*3 were higher in Caucasians and Indians but lower in African-Americans as compared with the present study. As for CYP2C19*3 and CYP2C19*2, the minor allele frequencies were relatively lower in Caucasians and Indians than in Asians. Therefore, there might be the possibility of a population-specific effect regarding the genetic association of PHT therapy optimization. In the present study, the CYP2C9*3 and CYP2C19*3 were rare variants which may result in
type I error or false positive results, therefore further larger sample sized studies should be conducted to confirm the single locus effect and combination effect in this study. The included patients were all under maintenance PHT therapy for at least one year and well controlled. Since clinicians would adjust PHT dosages according to PHT concentrations to achieve the therapeutic range, this may be the reason why these genetic variants were associated with PHT dosages rather than PHT concentrations. As for the strength of this study may include large monotherapy cohort of well-controlled patients, while the limitations may include inability to measure metabolites of phenytoin and lack of knowledge on distribution of other important allelic variants specifically those characterizing CYP2C9 and CYP2C19.
In conclusion, based on polygenic analysis of pharmacokinetic and pharmacodynamic related genetic variants, the present study revealed that CYP2C9,
CYP2C19, SCN1A and ABCB1 genetic polymorphisms, along with clinical factors,
modulated the PHT maintenance doses and CDRs. These results may provide information regarding personalized pharmacotherapy approaches to PHT maintenance therapy, and further larger population studies with different ethnics may need to confirm our findings.
Funding
The authors extend their sincere thanks to National Science Council, Taiwan (NSC-99-2320-B-039-005-MY3), Taiwan Department of Health Clinical Trial and Research Center of Excellence (DOH101-TD-B-111-004) and China Medical University, Taiwan (CMU99-N1-15-1 and CMU99-N1-15-2) for funding this research.
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