Role of CYP2C9, CYP2C19 and EPHX Polymorphism in the Pharmacokinetic of Phenytoin: A Study on Uruguayan Caucasian Subjects

Pharmacogenetic Variants and Plasma Concentrations of Antiseizure Drugs: A Systematic Review and Meta-Analysis

Importance

Precise estimation of a patient's drug metabolism capacity is important for antiseizure dose personalization.

Objective

To quantify the differences in plasma concentrations for antiseizure drugs associated with variants of genes encoding drug metabolizing enzymes.

Data Sources

PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to September 30, 2023, without language restrictions.

Study Selection

Two reviewers performed independent study screening and assessed the following inclusion criteria: appropriate genotyping was performed, genotype-based categorization into subgroups was possible, and each subgroup contained at least 3 participants.

Data Extraction and Synthesis

The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for data extraction and subsequent quality, validity, and risk-of-bias assessments. The results from the included studies were pooled with random-effect meta-analysis.

Main Outcomes and Measures

Plasma concentrations of antiseizure drugs were quantified with the dose-normalized area under the concentration-time curve, the dose-normalized steady state concentration, or the concentrations after a single dose at standardized dose and sampling time. The ratio of the means was calculated by dividing the mean drug plasma concentrations of carriers and noncarriers of the pharmacogenetic variant.

Results

Data from 98 studies involving 12 543 adult participants treated with phenytoin, valproate, lamotrigine, or carbamazepine were analyzed. Studies were mainly conducted within East Asian (69 studies) or White or European (15 studies) cohorts. Significant increases of plasma concentrations compared with the reference subgroup were observed for phenytoin, by 46% (95% CI, 33%-61%) in CYP2C9 intermediate metabolizers, 20% (95% CI, 17%-30%) in CYP2C19 intermediate metabolizers, and 39% (95% CI, 24%-56%) in CYP2C19 poor metabolizers; for valproate, by 12% (95% CI, 4%-20%) in CYP2C9 intermediate metabolizers, 12% (95% CI, 2%-24%) in CYP2C19 intermediate metabolizers, and 20% (95% CI, 2%-41%) in CYP2C19 poor metabolizers; and for carbamazepine, by 12% (95% CI, 3%-22%) in CYP3A5 poor metabolizers.

Conclusions and Relevance

This systematic review and meta-analysis found that CYP2C9 and CYP2C19 genotypes encoding low enzymatic capacity were associated with a clinically relevant increase in phenytoin plasma concentrations, several pharmacogenetic variants were associated with statistically significant but only marginally clinically relevant changes in valproate and carbamazepine plasma concentrations, and numerous pharmacogenetic variants were not associated with statistically significant differences in plasma concentrations of antiseizure drugs.

[Validation of the immunological method of kinetic interaction of microparticles in solution (KIMS) for the determination of phenytoin in saliva at the Hospital de Niños de Santísima Trinidad.]

Phenytoin (DFH), is an anticonvulsant widely used for the treatment of different types of seizures.(1) Therapeutic monitoring (TDM) is required for DFH due to its narrow therapeutic range and nonlinear pharmacokinetics, among other characteristics. Monitoring is frequently done on plasma or serum (total drug) through immunological methods. DFH can also be monitored in saliva, which shows a good correlation with plasma. The concentration of DFH in saliva reflects the concentration of free drug and due to the simplicity in its collection, it leads to a less stressful process for the patient. The aim of this study was to validate the immunological method of kinetic interaction of microparticles in solution (KIMS) for the determination of DFH using saliva as biological matrix. Linearity, precision, detection and quantification limit, accuracy and interference were analyzed. Infostat 8.0 student version software was used for statistical analysis. The method was linear in a range between 0.41 and 5ug/ml. The detection and quantification limits were 0.14 and 0.45ug/ml, respectively. The equation of the straight line obtained based on the method comparison between KIMS and HPLC-UV was DFHKIMS= 0,81* DFHHPLC – 0,03.  The KIMS method proved to have the necessary analytical characteristics to be applied as a useful and practical tool for the follow-up of those patients with difficult venous access and/or children with chronic DFH treatments.

The role of efflux transporters and metabolizing enzymes in brain and peripheral organs to explain drug-resistant epilepsy

Drug‐resistant epilepsy has been explained by different mechanisms. The most accepted one involves overexpression of multidrug transporters proteins at the blood brain barrier and brain metabolizing enzymes. This hypothesis is one of the main pharmacokinetic reasons that lead to the lack of response of some antiseizure drug substrates of these transporters and enzymes due to their limited entrance into the brain and limited stay at the sites of actions. Although uncontrolled seizures can be the cause of the overexpression, some antiseizure medications themselves can cause such overexpression leading to treatment failure and thus refractoriness. However, it has to be taken into account that the inductive effect of some drugs such as carbamazepine or phenytoin not only impacts on the brain but also on the rest of the body with different intensity, influencing the amount of drug available for the central nervous system. Such induction is not only local drug concentration but also time dependent. In the case of valproic acid, the deficient disposition of ammonia due to a malfunction of the urea cycle, which would have its origin in an intrinsic deficiency of L‐carnitine levels in the patient or by its depletion caused by the action of this antiseizure drug, could lead to drug‐resistant epilepsy. Many efforts have been made to change this situation. In order to name some, the administration of once‐daily dosing of phenytoin or the coadministration of carnitine with valproic acid would be preferable to avoid iatrogenic refractoriness. Another could be the use of an adjuvant drug that down‐regulates the expression of transporters. In this case, the use of cannabidiol with antiseizure properties itself and able to diminish the overexpression of these transporters in the brain could be a novel therapy in order to allow penetration of other antiseizure medications into the brain.

Genetic and clinical risk factors associated with phenytoin-induced cutaneous adverse drug reactions in Thai population

OBJECTIVE

This study aimed to describe the genetic and clinical risk factors associated with phenytoin-induced cutaneous adverse drug reactions (PHT-induced cADRs) in Thai patients.

METHOD

A retrospective case-control study was conducted among 88 PHT- cADRs (25 SJS/TEN, 37 DRESS/DIHS and 26 MPE) compared to 70 PHT-tolerant controls during 2008-2017. Genotyping was performed by Taqman RT-PCR (EPHX1 337 T > C, EPHX1 416A > G and CYP2C9*3), pyrosequencing (UGT1A1*28, UGT1A1*6) and polymerase chain reaction-sequence-specific oligonucleotide probe (HLA-B). Chi-squared test and binary logistic regression were used to identify factors associated with PHT-cADRs.

RESULTS

Multivariate analysis showed that HLA-B*46:01 was significantly associated with all PHT-induced cADRs (OR 2.341; 95% CI, 1.078-5.084; P = .032). Age of ≥60 years showed a significant association with PHT-induced SJS/TEN (OR 3.600; 95% CI, 1.214-10.672; P = .021). CYP2C9*3 was almost reaching statistically associated with an increased risk of PHT-induced SJS/TEN (OR 4.800; 95% CI, 0.960-23.990; P = .056). While HLA-B*56:02/04 was found to have a significant association with PHT-induced DRESS/DIHS (OR 29.312; 95% CI, 1.213-707.994; P = .038). Moreover, female gender and HLA-B*40:01 were associated with an increased risk of PHT-induced MPE at OR 5.734; 95% CI, 0.910-58.351; P = .042 and OR 3.647; 95% CI, 1.193-11.147; P = .023, respectively.

CONCLUSION

Both clinical (advanced age, female gender) and genetic factors (HLA-B*46:01, CYP2C9*3, HLA-B*56:02/04 and HLA-B*40:01) contributed to the risk of PHT-induced cADRs. Further studies with larger sample size may be warranted to confirm these findings and also the influence of EPHX1 gene.

Lamotrigine-Valproic Acid Interaction Leading to Stevens-Johnson Syndrome

Lamotrigine (LTG) is currently indicated as adjunctive therapy for focal and generalized tonic-clonic seizures and for treatment of bipolar disorder and neuropathic pain. A common concern with LTG in children is the frequency of appearance of skin rash. The intensity of this adverse effect can vary from transient mild rash to Stevens–Johnson syndrome (SJS), which can be fatal mainly when LTG is coadministered with valproic acid (VPA). Hereby, we present the case of an 8-year-old boy who suffered from SJS and other complications two weeks after LTG was added to his VPA treatment in order to control his seizures. VPA is known to decrease LTG clearance via reduced glucuronidation. In this case, the minor elimination pathway of LTG would play a more important role, and the formation of an arene oxide metabolite would be enhanced. As this reactive metabolite is detoxified mainly by enzymatic reactions, involving microsomal epoxide hydrolase and/or GSH-S-transferases and these enzymes are polymorphically expressed in humans, arene oxide toxicity is increased when epoxide hydrolase or GSH-S-transferases is either defective or inhibited or a depletion of intracellular glutathione levels is taking place. VPA can cause inhibition of epoxide hydrolase enzymes and/or depletion of glutathione levels leading to adverse cutaneous reactions.