Impact of CYP2C19 and CYP2C9 gene polymorphisms on sodium valproate plasma concentration in patients with epilepsy

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.

Evaluation of CYP2C19 Genetic Variant and Its Lack of Association with Valproic Acid Plasma Concentrations Among Zhuang and Han Schizophrenia Patients in Guangxi

Purpose

To investigate the CYP2C19 genotype distribution and allelic frequency among the Zhuang and Han schizophrenic populations in Guangxi, examine the correlation between CYP2C19 genetic variants and standardized blood levels of Valproic Acid (VPA) in schizophrenic patients, and evaluate the effects of age, gender, and Body Mass Index (BMI) on standardized VPA blood concentrations.

Patients and Methods

Between February and December 2022, 192 Zhuang and Han schizophrenia patients treated with VPA were studied. Steady-state VPA concentrations were determined using homogeneous enzyme immunoassays, and CYP2C19 *1, *2, and *3 loci via q-PCR. CYP2C19 genotype distributions between Zhuang and Han groups in Nanning were compared using chi-square tests and contrasted with other ethnicities. Non-parametric tests analyzed VPA variations, identifying critical factors through multivariate stepwise regression.

Results

The study identified five CYP2C19 genotypes at the *2 and *3 loci, with the *3/*3 genotype absent in both cohorts. The CYP2C19 distribution in Guangxi Zhuang and Han mirrors, yet diverges significantly from Hui and Kazakh groups. Among 192 subjects, VPA blood levels remained consistent across metabolic types and ages 18-60 but varied significantly by gender. Multivariate analysis revealed gender and BMI as significant factors, overshadowing CYP2C19 genotype and age.

Conclusion

In Guangxi, CYP2C19 genetic variants in Zhuang and Han schizophrenia patients demonstrate statistically indistinguishable allelic and metabolic distributions. Gender and BMI can influence standardized VPA blood concentrations in schizophrenia patients. However, in our study cohort, the CYP2C19 genotype and age are not the primary determinants of standardized VPA blood levels.

Ethnic Aspects of Valproic Acid P-Oxidation

The safety of the use of psychotropic drugs, widely used in neurological and psychiatric practice, is an urgent problem in personalized medicine. This narrative review demonstrated the variability in allelic frequencies of low-functioning and non-functional single nucleotide variants in genes encoding key isoenzymes of valproic acid P-oxidation in the liver across different ethnic/racial groups. The sensitivity and specificity of pharmacogenetic testing panels for predicting the rate of metabolism of valproic acid by P-oxidation can be increased by prioritizing the inclusion of the most common risk allele characteristic of a particular population (country).

Pharmacokinetic characterisation of a valproate Autism Spectrum Disorder rat model in a context of co-exposure to α-Hexabromocyclododecane

Assessing the role of α-hexabromocyclododecane α-HBCDD as a factor of susceptibility for Autism Spectrum disorders by using valproic acid-exposed rat model (VPA) required characterizing VPA pharmacokinetic in the context of α-HBCDD-co-exposure in non-pregnant and pregnant rats. The animals were exposed to α-HBCDD by gavage (100 ng/kg/day) for 12 days. This was followed by a single intraperitoneal dose of VPA (500 mg/kg) or a daily oral dose of VPA (500 mg/kg) for 3 days. Exposure to α-HBCDD did not affect the pharmacokinetics of VPA in pregnant or non-pregnant rats. Surprisingly, VPA administration altered the pharmacokinetics of α-HBCDD. VPA also triggered higher foetal toxicity and lethality with the PO than IP route. α-HBCDD did not aggravate the embryotoxicity observed with VPA, regardless of the route of exposure. Based on this evidence, a single administration of 500 mg/kg IP is the most suitable VPA model to investigate α-HBCDD co-exposure.

A real-life pilot study of the clinical application of pharmacogenomics testing on saliva in epilepsy

Response to antiseizure medications (ASMs) can be influenced by several gene polymorphisms, causing either lower efficacy or higher occurrence of adverse drug reactions (ADRs). We investigated the clinical utility of salivary pharmacogenomic testing on epilepsy patients. A commercialized pharmacogenomic salivary test was performed in a cohort of epileptic patients. Genetic variants on five genes (i.e., CYP1A2, CYP2C9, CYP2C19, EPHX1, and ABCB1) involved in common ASMs metabolism were selected. Twenty-one individuals (median age [Q1 -Q3 ]: 15 [6.5-28] years) were enrolled. Six patients harboring the homozygous *1F allele in CYP1A2 could have reduced chance of response to stiripentol due to fast metabolism. CYP2C9 had reduced activity in 10 patients (alleles *2 and *3), potentially affecting phenytoin (PHT), phenobarbital (PB), primidone, lacosamide (LCM), and valproic acid metabolism. Seven patients, carrying the *2 allele of CYP2C19, had an increased risk of ADRs with clobazam (CLB), PB, PHT, LCM, brivaracetam; while one individual with the *17 allele in heterozygosity reported a CLB fast metabolism. Six patients showed a CC polymorphism of EPHX1 associated with the impaired efficacy of carbamazepine. ABCB1 polymorphisms related to drug-resistance (3435 CC) or drug-sensitive phenotype (CT or TT) were found in 6 out of 7 patients. Pharmacogenomic testing on saliva proved easy and safe in clinical practice to convey information for the management of epileptic patients, especially those resistant to treatment or sensitive to severe ADRs.

Effects of UGT1A, CYP2C9/19 and ABAT polymorphisms on plasma concentration of valproic acid in Chinese epilepsy patients

Aim: To evaluate the association between genetic polymorphisms and plasma concentration-to-dose ratio of valproic acid (CDRV) in Chinese epileptic patients. Methods: A total of 46 epileptic patients treated with valproic acid therapy were enrolled. 18 SNPs in nine genes related to valproic acid were directly sequenced with Sanger methods. Results: Patients carrying UGT1A6 heterozygous genotypes had significantly lower CDRV than those carrying the wild-type genotypes. In contrast, patients with the homozygote genotypes of CYP2C9 and ABAT had higher CDRV than those with the wild-type genotypes and patients with the heterozygous genotypes of CYP2C19 had higher CDRV. Conclusion: Detection of genetic polymorphism in these genes might facilitate an appropriate dose of valproic acid for epileptic patients. Further studies with larger cohorts are necessary to underpin these observations.

Effects of CYP2C19 genetic polymorphism on the pharmacokinetics of tolperisone in healthy subjects

Tolperisone hydrochloride is a centrally-acting muscle relaxant used for relieving spasticities of neurological origin and muscle spasms associated with painful locomotor diseases. It is metabolized to the inactive metabolite mainly by CYP2D6 and, to a lesser extent, by CYP2C19 and CYP1A2. In our previous study, the pharmacokinetics of tolperisone was significantly affected by the genetic polymorphism of CYP2D6, but the wide interindividual variation of tolperisone pharmacokinetics was not explained by genetic polymorphism of CYP2D6 alone. Thus, we studied the effects of CYP2C19 genetic polymorphism on tolperisone pharmacokinetics. Eighty-one subjects with different CYP2C19 genotypes received a single oral dose of 150 mg tolperisone with 240 mL of water, and blood samples were collected up to 12 h after dosing. The plasma concentration of tolperisone was measured by a liquid chromatography-tandem mass spectrometry system. The CYP2C19PM group had significantly higher C_max and lower CL/F values than the CYP2C19EM and CYP2C19IM groups. The AUC_inf of the CYP2C19PM group was 2.86-fold and 3.00-fold higher than the CYP2C19EM and CYP2C19IM groups, respectively. In conclusion, the genetic polymorphism of CYP2C19 significantly affected tolperisone pharmacokinetics.

Therapeutic and Toxic Effects of Valproic Acid Metabolites

Valproic acid (VPA) and its salts are psychotropic drugs that are widely used in neurological diseases (epilepsy, neuropathic pain, migraine, etc.) and psychiatric disorders (schizophrenia, bipolar affective disorder, addiction diseases, etc.). In addition, the indications for the appointment of valproate have been expanding in recent years in connection with the study of new mechanisms of action of therapeutic and toxic metabolites of VPA in the human body. Thus, VPA is considered a component of disease-modifying therapy for multiple tumors, neurodegenerative diseases (Huntington's disease, Parkinson's disease, Duchenne progressive dystrophy, etc.), and human immunodeficiency syndrome. The metabolism of VPA is complex and continues to be studied. Known pathways of VPA metabolism include: β-oxidation in the tricarboxylic acid cycle (acetylation); oxidation with the participation of cytochrome P-450 isoenzymes (P-oxidation); and glucuronidation. The complex metabolism of VPA explains the diversity of its active and inactive metabolites, which have therapeutic, neutral, or toxic effects. It is known that some active metabolites of VPA may have a stronger clinical effect than VPA itself. These reasons explain the relevance of this narrative review, which summarizes the results of studies of blood (serum, plasma) and urinary metabolites of VPA from the standpoint of the pharmacogenomics and pharmacometabolomics. In addition, a new personalized approach to assessing the cumulative risk of developing VPA-induced adverse reactions is presented and ways for their correction are proposed depending on the patient's pharmacogenetic profile and the level of therapeutic and toxic VPA metabolites in the human body fluids (blood, urine).

Machine learning advances the integration of covariates in population pharmacokinetic models: Valproic acid as an example

Background and Aim: Many studies associated with the combination of machine learning (ML) and pharmacometrics have appeared in recent years. ML can be used as an initial step for fast screening of covariates in population pharmacokinetic (popPK) models. The present study aimed to integrate covariates derived from different popPK models using ML.

Methods: Two published popPK models of valproic acid (VPA) in Chinese epileptic patients were used, where the population parameters were influenced by some covariates. Based on the covariates and a one-compartment model that describes the pharmacokinetics of VPA, a dataset was constructed using Monte Carlo simulation, to develop an XGBoost model to estimate the steady-state concentrations (Css) of VPA. We utilized SHapley Additive exPlanation (SHAP) values to interpret the prediction model, and calculated estimates of VPA exposure in four assumed scenarios involving different combinations of CYP2C19 genotypes and co-administered antiepileptic drugs. To develop an easy-to-use model in the clinic, we built a simplified model by using CYP2C19 genotypes and some noninvasive clinical parameters, and omitting several features that were infrequently measured or whose clinically available values were inaccurate, and verified it on our independent external dataset.

Results: After data preprocessing, the finally generated combined dataset was divided into a derivation cohort and a validation cohort (8:2). The XGBoost model was developed in the derivation cohort and yielded excellent performance in the validation cohort with a mean absolute error of 2.4 mg/L, root-mean-squared error of 3.3 mg/L, mean relative error of 0%, and percentages within ±20% of actual values of 98.85%. The SHAP analysis revealed that daily dose, time, CYP2C19*2 and/or *3 variants, albumin, body weight, single dose, and CYP2C19*1*1 genotype were the top seven confounding factors influencing the Css of VPA. Under the simulated dosage regimen of 500 mg/bid, the VPA exposure in patients who had CYP2C19*2 and/or *3 variants and no carbamazepine, phenytoin, or phenobarbital treatment, was approximately 1.74-fold compared to those with CYP2C19*1/*1 genotype and co-administered carbamazepine + phenytoin + phenobarbital. The feasibility of the simplified model was fully illustrated by its performance in our external dataset.

Conclusion: This study highlighted the bridging role of ML in big data and pharmacometrics, by integrating covariates derived from different popPK models.

Metabolizing status of CYP2C19 in response and side effects to medications for depression: Results from a naturalistic study

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Polymorphisms in cytochrome P450 genes (CYP450) were demonstrated to play a significant role in antidepressant response and side effects, but their effect in real-world clinical practice is poorly known. We determined the metabolic status of CYP2C19 based on the combination of *1, *2, *3 and *17 alleles extracted from genome-wide data in 1239 patients with MDD, pharmacologically treated in a naturalistic setting. Symptom improvement and side effects were assessed using the Montgomery and Åsberg Depression Rating Scale and the Udvalg for Kliniske Undersøgelse scale, respectively. We tested if symptom improvement, response and side effects were associated with CYP2C19 metabolic status adjusting for potential confounders. We considered patients treated with drugs for depression having CYP2C19 genotyping recommended by guidelines (T1 Drugs); secondarily, with all psychotropic drugs having CYP2C19 as relevant metabolic path (T2 Drugs). In the group treated with T1 drugs (n = 540), poor metabolizers (PMs) showed higher response and higher symptom improvement compared to normal metabolizers (p = 0.023 and p = 0.009, respectively), but also higher risk of autonomic and neurological side effects (p = 0.022 and p = 0.022 respectively). In patients treated with T2 drugs (n = 801), similar results were found. No associations between metabolizer status and other types of side effects were found (psychic and other side effects). Our study suggests potential advantages of CYP2C19 pharmacogenetic testing to guide treatment prescription, that may not be limited to the drugs currently recommended by guidelines.

Pharmacogenetics of Carbamazepine and Valproate: Focus on Polymorphisms of Drug Metabolizing Enzymes and Transporters

Pharmacogenomics can identify polymorphisms in genes involved in drug pharmacokinetics and pharmacodynamics determining differences in efficacy and safety and causing inter-individual variability in drug response. Therefore, pharmacogenomics can help clinicians in optimizing therapy based on patient's genotype, also in psychiatric and neurological settings. However, pharmacogenetic screenings for psychotropic drugs are not routinely employed in diagnosis and monitoring of patients treated with mood stabilizers, such as carbamazepine and valproate, because their benefit in clinical practice is still controversial. In this review, we summarize the current knowledge on pharmacogenetic biomarkers of these anticonvulsant drugs.