Impact of gender, albumin, and CYP2C19 polymorphisms on valproic acid in Chinese patients: a population pharmacokinetic model

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.

Rescue strategies for valproic acid overdose poisoning: Case series and literature review

Valproic acid (VPA) is a wide-ranging anti-epileptic medication that primarily affects bipolar disorder, mania, and migraine. The leading causes of mortality associated with acute poisoning from VPA are nervous system toxicity, drug-induced shock due to encephalopathy from hyperammonemia, as well as acute liver and kidney failure, and respiratory depression that contribute to hemodynamic instability. Treatment of acute VPA poisoning primarily involves in vitro elimination methods, including hemoperfusion (HP), hemodialysis, and hemofiltration, as well as drug remedies such as L-carnitine and meropenem. Nonetheless, there are conflicting opinions regarding drug usage. This article details the three cases of acute poisoning from VPA. The fundamental approach to treatment employs HP assisted by blood concentration monitoring to alleviate shock and stabilize hemodynamics. This investigation presents guidance for the treatment and management of acute poisoning with VPA in clinical settings.

Effect of ANKK1 Polymorphisms on Serum Valproic Acid Concentration in Chinese Han Adult Patients in the Early Postoperative Period

INTRODUCTION

This study aimed to investigate the relationship between gene polymorphisms and clinical factors with the concentrations of valproic acid (VPA) in adult patients who underwent neurosurgery in China.

METHODS

A total of 531 serum concentration samples at steady state were collected from 313 patients to develop a population pharmacokinetic (PPK) model. Data analysis was performed using nonlinear mixed effects modeling. Covariates included demographic parameters, biological characteristics, and genetic polymorphism. Bootstrap evaluation showed that the final model was stable. Sensitive analysis was performed to verify the relationship between gene polymorphisms and concentrations of VPA. Linear regression was used to analyze the relationship between VPA concentration, ANKK1, and daily dosage.

RESULTS

In the recruited patients, 17 of 25 single-nucleotide polymorphism distributions were consistent with the Hardy-Weinberg equilibrium. A one-compartment model with first-order absorption and elimination was developed for VPA injections. VPA clearance was significantly influenced by three variables: sex (17.41% higher in male than female patients), body weight, and the ANKK1 gene. Typical values for the elimination clearance and the volume of central compartment were 0.614 L/min and 23.5 L, respectively. The model evaluation indicated the stable and precise performance of the final model. After sensitive analysis using Kruskal-Wallis and Mann-Whitney U tests, we found that patients with AA alleles had higher VPA concentrations than those with GG and AG alleles. Linear regression models showed that gene polymorphisms of ANKK1 had little effects on VPA concentration.

CONCLUSION

A PPK model of VPA in Chinese Han patients was successfully established; this can be helpful for model-informed precision-dosing approaches in clinical patient care, and for exploring the mechanism of VPA-induced weight gain.

Pharmacogenetics-based population pharmacokinetic analysis and dose optimization of valproic acid in Chinese southern children with epilepsy: Effect of ABCB1 gene polymorphism

Objective: The aim of this study was to establish a population pharmacokinetic (PPK) model of valproic acid (VPA) in pediatric patients with epilepsy in southern China, and provide guidance for individualized medication of VPA therapy. Methods: A total of 376 VPA steady-state trough concentrations were collected from 103 epileptic pediatric patients. The PPK parameter values for VPA were calculated by using the nonlinear mixed-effects modeling (NONMEM) method, and a one-compartment model with first-order absorption and elimination processes was applied. Covariates included demographic information, concomitant medications and selected gene polymorphisms. Goodness-of-fit (GOF), bootstrap analysis, and visual predictive check (VPC) were used for model evaluation. In addition, we used Monte Carlo simulations to propose dose recommendations for different subgroup patients. Results: A significant effect of the patient age and ABCB1 genotypes was observed on the VPA oral clearance (CL/F) in the final PPK model. Compared with patients with the ABCB1 rs3789243 AA genotype, CL/F in patients with GG and AG genotypes was increased by 8% and reduced by 4.7%, respectively. The GOF plots indicated the satisfactory predictive performance of the final model, and the evaluation by bootstrap and VPC showed that a stable model had been developed. A table of individualized dosing regimens involving age and ABCB1 genotype was constructed based on the final PPK model. Conclusion: This study quantitatively investigated the effects of patient age and ABCB1 rs3789243 variants on the pharmacokinetic variability of VPA. The PPK models could be beneficial to individual dose optimization in epileptic children on VPA therapy.

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.

Published population pharmacokinetic models of valproic acid in adult patients: a systematic review and external validation in a Chinese sample of inpatients with bipolar disorder

BACKGROUND

This study reviewed all published valproic acid (VPA) population pharmacokinetic (PPK) models in adult patients and assessed them using external validation methods to determine predictive performance.

METHODS

Thirteen published PPK models (labeled with letters A to M) not restricted to children were identified in PubMed, Embase, and Web of Science databases. They were evaluated in a sample totaling 411 serum concentrations from 146 adult inpatients diagnosed with bipolar disorder in a Chinese hospital. Serum concentrations of VPA were analyzed by validated ultra-performance liquid chromatography-tandem mass spectrometry. Performance was assessed by 4 tests (prediction-based diagnostics, visual predictive checks, normalized prediction distribution error, and Bayesian forecasting).

RESULTS

Models K and L, developed in large samples of Chinese and Thai patients, showed good performance in our Chinese dataset. Models H and J demonstrated good performance in Tests 2 and 3 of the 4 tests, respectively. Another 7 models exhibited intermediate performance. The models with the worst performance, F and M, could not be improved by Bayesian forecasting.

CONCLUSION

In our validation study the most important factors contributing to good performance were absence of children, Asian ethnicity, one-compartment models and inclusion of body weight and VPA dose in previously published models.

A 5-Year Study of Lithium and Valproic Acid Drug Monitoring in Patients with Bipolar Disorders in an Italian Clinical Center

Therapeutic drug monitoring (TDM) is an effective tool used to improve the pharmacological treatment in clinical practice, especially to detect subtherapeutic drug plasma concentration (Cp) in order to consider a change of dosage during treatment and reach its putative therapeutic range. In this study, we report the Cp values of lithium and valproic acid (VPA), alone and in combination, mostly in bipolar patients admitted to an Italian clinical center of the University of Pisa during the years 2016–2020, which include 12,294 samples of VPA, 7449 of lithium and 1118 of both in combination. Lithium and VPA are the most utilized drugs in treating bipolar disorders, and their TDM is strongly recommended by recent guidelines. In relation to lithium Cp monitoring, several studies have underlined that 0.5–0.8 mmol/L is the optimal range for chronic treatment, and below 0.4 mmol/L, it is unlikely to produce a clinical response. For VPA, the therapeutic range is 50–100 μg/mL and a linear correlation between Cp and clinical efficacy has been proposed, where below 50 μg/mL, the clinical efficacy of VPA has not been proven thus far. Toxic levels of both drugs were rarely found in our study, while a high percentage of patients, about one-third, had sub-therapeutic Cp during their treatments. In addition, in several cases of patients receiving multiple blood sampling, the initial subtherapeutic Cp changed only partially without reaching its therapeutic window. In relation to age, we found a higher percentage of lithium and VPA Cp values in range in the adolescents than in the adults and elderly groups. No differences were reported when analyzing the distribution of Cp values in males and females. In conclusion, this present study suggests that TDM is widely used by many specialists, but there is still a window of improvement for optimizing pharmacological treatments in clinical practice.

The PHARMACOM-EPI Framework for Integrating Pharmacometric Modelling Into Pharmacoepidemiological Research Using Real-World Data: Application to Assess Death Associated With Valproate

In pharmacoepidemiology, it is usually expected that the observed association should be directly or indirectly related to the pharmacological effects of the drug/s under investigation. Pharmacological effects are, in turn, strongly connected to the pharmacokinetic and pharmacodynamic properties of a drug, which can be characterized and investigated using pharmacometric models. Recently, the use of pharmacometrics has been proposed to provide pharmacological substantiation of pharmacoepidemiological findings derived from real-world data. However, validated frameworks suggesting how to combine these two disciplines for the aforementioned purpose are missing. Therefore, we propose PHARMACOM-EPI, a framework that provides a structured approach on how to identify, characterize, and apply pharmacometric models with practical details on how to choose software, format dataset, handle missing covariates/dosing data, how to perform the external evaluation of pharmacometric models in real-world data, and how to provide pharmacological substantiation of pharmacoepidemiological findings. PHARMACOM-EPI was tested in a proof-of-concept study to pharmacologically substantiate death associated with valproate use in the Danish population aged ≥ 65 years. Pharmacological substantiation of death during a follow-up period of 1 year showed that in all individuals who died (n = 169) individual predictions were within the subtherapeutic range compared with 52.8% of those who did not die (n = 1,084). Of individuals who died, 66.3% (n = 112) had a cause of death possibly related to valproate and 33.7% (n = 57) with well-defined cause of death unlikely related to valproate. This proof-of-concept study showed that PHARMACOM-EPI was able to provide pharmacological substantiation for death associated with valproate use in the study population.

Population pharmacokinetics of valproic acid in adult Chinese patients with bipolar disorder

PURPOSE

To develop and validate a population pharmacokinetic (PPK) model of valproic acid (VPA) in adult Chinese patients with bipolar disorder, and provide guidance for individualized therapy in this population.

METHODS

A total of 1104 serum concentrations from 272 patients were collected in this study. The data analysis was performed using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, biological characteristics, and concomitant medications. Bootstrap validation (1000 runs), normalized prediction distribution error (NPDE), and external validation of 50 patients were employed to evaluate the final model.

RESULTS

A one-compartment model with first-order absorption and elimination was developed for VPA extended-release tablets. VPA clearance was significantly influenced by three variables: sex (12% higher in male patients), daily dose (increasing with the 0.13 exponent), and body weight (increasing with the 0.56 exponent). Typical values for the absorption rate constant (K_a), apparent clearance (CL/F), and apparent distribution volume (V/F) for a female patient weighing 70 kg administered VPA 1000 mg/day were 0.18 h^-1, 0.46 L/h, and 12.84 L, respectively. The results of model evaluation indicated a good stable and precise performance of the final model.

CONCLUSIONS

A qualified PPK model of VPA was developed in Chinese patients with bipolar disorder. This model could be used as a suitable tool for the personalization of VPA dosing for bipolar patients.

Effect of CYP2C19 polymorphisms on serum valproic level acid in Chinese Han patients with schizophrenia

Valproic acid is an anticonvulsant, which is also widely used for treating psychiatric disorders. Some clinical trials have demonstrated benefits of valproic acid augmentation therapy in schizophrenia. Interindividual variability in valproic acid dose and serum concentration may reflect functional consequences of genetic polymorphisms in genes encoding drug-metabolizing enzymes. The aim of this study was to determine the relationship between serum concentrations of valproic acid and single nucleotide polymorphisms of the cytochrome P450 (CYP) 2C19 gene in patients with schizophrenia. All patients had been receiving fixed dose of valproic acid for at least 2 weeks. The daily doses were 0.5–1.5 g. No other drugs except olanzapine were coadministered. Serum concentrations of valproic acid were measured using the ultra-high performance liquid chromatography method with mass-spectrometric detection. The CYP2C19 (CYP2C19*2 G681A rs4244285 and CYP2C19*3 G636A rs4986893) genotypes were identified by real-time PCR analyses. The mean concentration/dose ratios of valproic acid were significantly higher in patients with CYP2C19 *1/*2 genotype (P < 0.01) or CYP2C19 *2/*3 genotype (P < 0.01) than in those with CYP2C12 *1/*1 genotype. The mean concentration/dose ratios of valproic acid were significantly higher in patients with 1 (P < 0.01) or 2 (P < 0.01) mutated alleles for CYP2C19 than in those without mutated alleles. And the post hoc analysis revealed that the result has acceptable statistical (power (1 – β) = 0.8486 at type I  level of 0.05) to support the observed significant associations for CYP2C19 SNPs and serum C/D ratios of valproic acid. The findings of this study suggest that the genetic polymorphisms of CYP2C19 significantly affect the steady-state serum concentrations of valproic acid in Chinese Han population. The determination of the CYP2C19 genotypes may be useful for dosing adjustment in schizophrenia patients on valproic acid therapy.

Valproic Acid After Neurosurgery Induces Elevated Risk of Liver Injury: A Prospective Nested Case-Control Study

BACKGROUND

Valproic acid (VPA) has been widely used to prevent epileptic seizures after neurosurgery in China. We have found that the incidence of liver injury (LI) in patients using VPA after neurosurgery is higher than that in other patients.

OBJECTIVE

The objective of this study was to investigate the risk factors of LI in patients using VPA after neurosurgery.

METHODS

A nested case-control study was conducted in patients using VPA after neurosurgery between September 2019 and March 2021. Cases of LI were matched to controls by age and body mass index (BMI). Conditional logistic regression was used to estimate matched odds ratios representing the odds of LI. A receiver operating characteristic curve was used to analyze the optimal cutoff condition.

RESULTS

A total of 248 people (62 LI and 186 control) were enrolled. Among patients with vs without LI, the matched odds ratio for trough concentration of VPA was significant (matched odds ratio [OR], 1.09; 95% confidence interval [CI]: 1.01-1.19). The course of treatment (OR: 1.17, 95% CI: 1.02-1.33), Glasgow score (OR: 0.26, 95% CI: 0.10-0.67), gene polymorphisms of CYP2C19 (OR: 2.09, 95% CI: 1.03-146.93), and UGT1A6 (OR: 34.61, 95% CI: 1.19-1003.23) were all related to the outcome. The optimal cutoff of the course of treatment was 10 days, while the trough concentration of VPA was determined to be 66.16 mg/L.

CONCLUSION

Length of treatment, VPA trough concentration, and Glasgow score were associated with LI in patients after neurosurgery. A gene test may be necessary for people who are prescribed VPA for a long time.