Jun Mei Teng,1 Shuiqing Qin,2 Danyu Lu,1 Yefa Gu,3 Shi Jie Tang,3 Qiong Yan,1 Jiawei Yao,1 Chao Zhang1

1Laboratory Department, The Fifth People’s Hospital of Nanning, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 2Department of Science and Education, The Fifth People’s Hospital of Nanning, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 3Department of Psychiatry, The Fifth People’s Hospital of Nanning, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China

Correspondence: Danyu Lu, Laboratory Department, The Fifth People’s Hospital of Nanning, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China, Tel +86 13457087740, Email [email protected]

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.

Keywords: CYP2C19 gene, valproic acid, blood drug concentration, Zhuang Chinese, Han Chinese

Introduction

Pharmacogenomics delves into the intricate interplay between human genomic information and drug responses, with the ultimate goal of elucidating the variations in drug safety and efficacy among individuals.1–3 As a pivotal facet of precision medicine, pharmacogenomics is centrally concerned with meticulous drug and dosage selection, targeted therapeutic interventions, and the anticipation of drug safety concerns, all while mitigating the emergence of deleterious side effects. This avenue of research empowers us to prognosticate patient responses to specific medications, thereby paving the way for bespoke treatment regimens.4,5 The metabolism kinetics and therapeutic potency of drugs are frequently orchestrated by endogenous enzymes, under the orchestration of genes. In instances where distinct genetic variants manifest, their impact on drug effects and safety can be discernible. For instance, the CYP2C19 gene encodes a member of the cytochrome P450 enzyme family, playing a pivotal role in drug metabolism.6,7 This encompassing enzymatic responsibility extends to an array of pharmaceuticals, including certain antifungal agents, antidepressants, proton pump inhibitors, and antiplatelet aggregation medications.8–11 The CYP2C19 enzyme, owing to its intricate genetic diversity, has emerged as a focal point in pharmacogenomic investigations, wherein these genetic variances may conceivably modulate enzyme functionality and drug metabolism.12 Notably, the CYP2C19 allele denoted as CYP2C19*17, endowed with an augmenting influence on enzyme activity, might necessitate a commensurate escalation in drug dosages to attain therapeutic outcomes. Conversely, aberrant CYP2C19 alleles, such as CYP2C19*2 and CYP2C19*3, could engender protracted metabolism, thus heightening the susceptibility to adverse effects, as expounded in the Clinical Pharmacogenetics Implementation Consortium (CPIC) dosing directives.13

VPA stands as an Anti-seizure medication (ASM), harnessed to address an array of seizure types, and extensively wielded in the management of generalized epilepsy. Beyond its epilepsy-related utility, VPA finds application in the realm of schizophrenia treatment. Operating as a mood modulator, it exerts governance over dopamine release and, in conjunction with other antipsychotic agents, orchestrates the containment of emotional volatility and impulsive tendencies. While VPA’s therapeutic spectrum is broad, its margin of safety remains relatively slender. In accordance with consensus directives emanating from the Association for Neuropsychopharmacology and Pharmacopsychiatry (AGNP), the designated therapeutic reference interval for VPA blood concentration spans from 50 to 100 mg/L.14 Dipping beneath this designated threshold might precipitate therapeutic inefficacy, whereas surpassing 120 mg/L could precipitate noteworthy adversities. Specifically, concentrations cresting 175 to 200 mg/L or free VPA levels eclipsing 14.67 mg/L may incite platelet diminution, culminating in purpura, hemorrhaging, and protracted clotting periods.15,16 Noteworthy is the pronounced divergence in clinical dosages and blood VPA concentrations across individuals, with blood levels diverging by a factor of 2 to 2.5 even among recipients of identical doses.17 These elements collectively curb the extent of VPA’s clinical application. Albeit investigations underscore the role of the CYP2C19 enzyme in VPA metabolism,18–20 and existing literature has probed into the ramifications of CYP2C19 genetic variations on VPA blood concentrations within epilepsy patients,21,22 a more comprehensive understanding of VPA metabolism necessitates consideration of additional CYP enzymes as indicated by the PharmGKB database (https://www.pharmgkb.org/pathway/PA165964265), which suggests that variants beyond CYP2C19, such as CYP2C9, CYP2A6, and CYP2B6, may also influence VPA plasma levels. The scope of studies delving into the impact of these genetic variations on VPA blood concentrations among schizophrenia patients remains circumscribed and inconclusive.

Prior investigations have illuminated disparities in the prevalence of CYP2C19*2 and CYP2C19*3 genetic variants across diverse geographical regions and ethnic backgrounds.23 While genetic variations distributions of CYP2C19 have been documented across distinct Chinese regions,24–26 a comprehensive scrutiny of CYP2C19 genetic variant distribution within the Zhuang and Han ethnic groups, specifically concerning individuals with schizophrenia in the Guangxi locale, remains an unexplored terrain. This study elucidates CYP2C19 genetic variant distribution in Guangxi’s Zhuang and Han cohorts, probing its correlation with VPA plasma levels in schizophrenia patients. Analyzing the influence of gender, age, and BMI on VPA concentration, our findings offer a foundation for individualized therapeutic strategies in clinical contexts.

Materials and Methods Participants

The study encompassed a cohort of 192 inpatient individuals afflicted with schizophrenia, constituting 96 individuals of Zhuang ethnicity and an equivalent number of Han ethnicity, all of whom satisfied the established diagnostic criteria for schizophrenia. The eligibility criteria were defined as follows: (1) age spanning from 18 to 60 years; (2) confirmation of schizophrenia diagnosis in alignment with the guidelines stipulated by the International Classification of Diseases, Tenth Revision (ICD-10); (3) affiliation with either the Zhuang or Han ethnic groups; (4) unimpaired liver and kidney functionality; (5) no documented history of substance abuse; (6) alignment of demographic attributes encompassing gender and age between the two ethnic subgroups. Conversely, the exclusion criteria encompassed: (1) treatment-resistant schizophrenia; (2) expectant or nursing women; (3) Severe physical illnesses or organic brain disorders, neurological disorders; (4) concurrent administration of carbamazepine, phenobarbital, or phenytoin. Notably, this investigation garnered approval from the Ethics Committee of the Fifth People’s Hospital of Nanning City and was conducted in full compliance with the ethical standards of the Declaration of Helsinki. All participants provided informed consent prior to the collection of blood specimens, ensuring adherence to ethical guidelines (Approval Number: Ethics Review SL2022-02-03).

Drug Treatment

The patients underwent VPA therapy (Hunan Xiangzhong Pharmaceutical Co., Ltd) as part of a combination treatment, often required for schizophrenia, for a duration spanning at least 5 elimination half-lives, which approximates 100 hours. The VPA was administered at a prescribed dosage ranging from 0.2 to 1.0 grams per day, dispensed orally across two equitably spaced administrations. While VPA is used off-label for schizophrenia treatment and often accompanied by other antipsychotic medications, this study focused on VPA’s role within the combination therapy. Any potential interaction effects were carefully monitored. Blood specimens were procured preceding the subsequent morning’s fasted dose, ensuring a 12-hour interlude, to guarantee accurate assessment of steady-state trough concentrations.

Analytical Methods

The quantification of VPA serum levels was executed through employment of the Roche Cobas 702 fully automated biochemical analyzer in tandem with its corresponding reagents. The assay boasted a minimum detectable concentration of 2.8 milligrams per milliliter, characterized by a coefficient of variation (CV) less than 5%. To neutralize the potential impact of dosage and body weight on blood drug concentration, standardization of VPA concentration ensued as follows:

Isolation of DNA from blood samples was expedited with celerity, courtesy of a nucleic acid extraction kit extended by Suzhou Kuangyuan Biotechnology Co., Ltd. The genotyping of CYP2C19 alleles, encompassing *2 and *3 variants, was consummated utilizing a human CYP2C19 genotyping assay kit, also made available by Suzhou Kuangyuan Biotechnology Co., Ltd.

Statistical Analyses

Data entry procedures were conducted employing Excel 2013, whereas the realm of statistical analysis was navigated through utilization of the SPSS 25.0 software suite. The examination of genetic equilibrium in the context of Hardy-Weinberg equilibrium was accomplished through the chi-square goodness-of-fit test. As for continuous data, the scrutiny for normal distribution entailed the application of the Shapiro–Wilk test. Data diverging from normal distribution were succinctly portrayed as median values interposed within the interquartile range. Comparative analyses across groups were orchestrated using the Mann–Whitney U-test or Kruskal–Wallis test, depending on the nature of the data. Count data found their expression as frequencies or rates, and the chi-square test was employed to scrutinize discrepancies in allelic and metabolic frequencies across distinct ethnic clusters. In relation to VPA blood concentrations, subsequent to logarithmic transformation, the method of multivariate stepwise regression analysis was harnessed to holistically elucidate the nexus between diverse factors and standardized VPA blood concentrations. All statistical evaluations followed the trajectory of two-tailed probability assessments, and a level of significance set at P<0.05 denoted statistical significance.

Results Patient Characteristics

The demographic characteristics of the patients are shown in Table 1. A total of 192 steady-state concentrations was collected. The plasma trough concentrations of VPA of the participants was 52.3 (39.2, 69.3) μg/mL and the median was within the 50~100 μg/mL therapeutic concentration of VPA. The standardized blood concentration of VPA was 2.30 (1.57, 3.51) μg/mL. Table 1.

Table 1 Demographic Characteristics of the Patients

Hardy-Weinberg Equilibrium Test for CYP2C19 Genotypes

CYP2C19 *2 and *3 genetic variants were consistent with Hardy–Weinberg equilibrium (p>0.05). Table 2.

Table 2 CYP2C19 Genetic Variant and Allele Distribution (n=192)

Genotype Distribution and Allele Frequency of CYP2C19 Genetic Variants in Zhuang and Han Ethnic Groups

The genotype frequencies are shown in Table 3. The analysis of CYP2C19 genotypes within the 192 patients revealed significant variances among the genotypes (*1/*1, *1/*2, *1/*3, *2/*2, 2/3) within both the Zhuang and Han ethnic clusters. Notably, neither group exhibited the CYP2C19 3/*3 genotype. The allele frequencies of CYP2C19 *1, *2, and *3 in the Zhuang group were 63.54%, 31.77%, and 4.69% respectively, while in the Han group, they stood at 64.58%, 31.25%, and 4.17% respectively. Additionally, the assessment discerned three distinct CYP2C19 metabolic phenotypes: within the Zhuang group, Normal metabolizer (NM) constituted 41.67%, Intermediate metabolizer (IM) amounted to 43.75%, and Poor metabolizer (PM) accounted for 14.58%; in the Han group, NM represented 41.67%, IM tallied 45.83%, and PM encompassed 12.50%. Intriguingly, the distribution of CYP2C19 genotypes, alleles, and metabolic phenotypes between the two ethnic groups bore no statistically significant disparities (P>0.05). Table 3.

Table 3 Genotype Distribution and Allele Frequency of CYP2C19 Genetic Variants in Zhuang and Han Ethnic Groups

Gender, Age and BMI Characteristics Among Different CYP2C19 Genotypes

The gender, age, and BMI characteristics among the 192 patients with different CYP2C19 genotypes are presented in Table 4. There were no statistically significant differences in gender, age, and BMI among the various genotypes (P>0.05).

Table 4 Gender, Age, and BMI Characteristics Among Different CYP2C19 Genotypes (n=192)

Comparison of CYP2C19 Allele Distribution and Metabolic Phenotype Distribution Between Zhuang Population in Guangxi and Various Population Groups in Other Regions of the Country

Amid the diverse Chinese regions and ethnicities, the mosaic of CYP2C19 allele and metabolic phenotype distribution in Guangxi Han schizophrenia patients unveiled intricate patterns. Comparative analyses underscored noteworthy distinctions in CYP2C19 allele distribution between Guangxi Han and Hui, as well as Kazakh populations (P<0.05). Similarly, the distribution of CYP2C19 metabolic phenotypes in Guangxi Han patients diverged significantly in contrast to Mongol, Hui, and Kazakh populations (P<0.05). Nevertheless, juxtapositions with Guangxi Zhuang, Dongguan, Huzhou, Hebei Han, Uighur, and Mongol populations yielded outcomes lacking statistical significance (P>0.05). Table 5.

Table 5 Comparison of CYP2C19 Allele Distribution and Metabolic Phenotype Distribution Between Zhuang Population in Guangxi and Various Population Groups in Other Regions of the Country

The Influence of CYP2C19 Metabolic Phenotype, Age, and Gender on Standardized VPA Blood Concentration

The standardized VPA blood concentrations for the NM, IM, and PM metabolic phenotypes exhibited a gradual increase without statistical significance. Furthermore, while differences in blood concentrations among different age groups were not statistically significant, females had significantly higher blood concentrations than males, with statistical significance. Table 6.

Table 6 Comparison of Standardized VPA Blood Drug Concentrations in Patients with Different CYP2C19 Metabolic Phenotypes, Age, and Gender

Multiple Stepwise Regression Analysis

The utilization of stepwise regression analysis culminated in the formulation of the regression equation for standardized VPA blood concentrations, incorporating gender and BMI: Standardized VPA blood concentration = 5.835–1.088×gender - 0.113×BMI (male = 1, female = 0). Notably, male blood concentrations trailed those of females (P<0.001), and BMI wielded a discernible influence on blood concentrations (P<0.001). However, the CYP2C19 genotypes and age exhibited no discernible impact on blood concentrations (P>0.05). Table 7.

Table 7 Coefficient

Discussion

The intricate orchestration of drug metabolism pivots upon the catalytic activity of diverse drug-metabolizing enzymes, among which the CYP2C19 gene assumes a pivotal role by encoding pivotal drug-metabolizing enzymes.32 Given the extensive clinical utilization of drugs that undergo metabolism facilitated by the CYP2C19 enzyme, the scrutiny of CYP2C19 genotypes across different geographical regions and ethnic strata has assumed paramount importance. This trajectory of investigation offers a compass for prognosticating patient metabolic phenotypes and furnishing guidance for clinical drug administration.33,34 Within the expanse of the CYP2C19 gene, while an array of SNPs (single nucleotide genetic variants) has surfaced, the preeminent variant sites within the Chinese context involve CYP2C19*2 and CYP2C19*3. Within the ambit of our study, we embarked on a comprehensive analysis of the genetic variants manifested at these two allelic loci of the CYP2C19 gene among Zhuang and Han ethnic individuals afflicted with schizophrenia within Guangxi. The findings unveiled a degree of congruence in the polymorphic distribution of the CYP2C19 gene across the spectrum of patients with schizophrenia belonging to the Zhuang and Han ethnic clusters.

The congruence in the distribution of CYP2C19 gene alleles within Guangxi’s Zhuang and Han patients grappling with schizophrenia can be ascribed to the ethnic diversity underpinning the region. The continuum of long-term migration, intermarriage, and cultural interchange across disparate ethnic cohorts could be hypothesized to have contributed to the attenuation of genetic diversity between the Zhuang and Han populations. Furthermore, the shared living environments and cultural practices might have acted as catalysts for the semblance in gene distribution between the two groups. Our research findings align with those of studies conducted on Han populations in various regions such as Dongguan, Huzhou, Hebei, Xinjiang Uighurs, Guizhou, Hubei, Yunnan, and northern areas.27–30,35–38 Nonetheless, significant disparities were detected in comparison with Hui and Kazakh populations, and distinctive disparities in gene phenotypes surfaced when juxtaposed with the Mongol population, especially in the Normal metabolizer (NM) phenotype.30,31 These insights signify that while the variations in CYP2C19 allele frequencies and metabolic phenotype distributions between Guangxi’s Zhuang and Han populations do not substantially deviate from those observed across different segments of the Han populace, they do manifest marked disparities when compared to specific ethnic minorities. The mosaic of genetic diversity, geographical segregation, and influences of natural selection within China potentially contribute to divergent genetic profiles among distinct ethnic groups, mirroring evolutionary adaptations tailored to unique survival contexts. The existence of variants in the CYP2C19 gene might reflect a survival advantage; nevertheless, these disparities warrant comprehensive contemplation within the context of drug treatment protocols. For instance, the CHANCE study underscored that in patients afflicted with mild ischemic stroke or transient ischemic attack (TIA), the concomitant administration of aspirin and clopidogrel yielded a reduction in stroke recurrence solely in patients devoid of the CYP2C19 loss-of-function allele, as contrasted with the administration of aspirin in isolation.39 Additional clinical applications of CYP2C19 genetic testing encompass the tailored prescription of selective serotonin reuptake inhibitors for depression treatment, the dosage adjustment of proton pump inhibitors for gastroesophageal reflux disease, and the calibration of voriconazole dosage for prophylaxis against invasive fungal infection, among other applications.40

CYP2C19 enzyme plays a vital role in metabolizing numerous drugs, including VPA, an antiepileptic and mood disorder medication. Nonfunctional or null alleles, like CYP2C19*2 and CYP2C19*3, can alter enzyme activity, influencing VPA blood concentrations.21 Our study investigated the relationship between these genetic variants and standardized VPA blood levels, also considering the effects of gender, age, and BMI in schizophrenia patients. Contrary to our hypothesis, these genetic variations did not show a significant impact on VPA concentrations. Instead, gender and BMI appeared to play a notable role. These findings suggest implications for personalized treatment in schizophrenia and open doors for further research in pharmacogenomics.

The landscape of prior research presents a tapestry of inconsistent conclusions concerning the clinical ramifications of CYP2C19 genotypes on VPA blood concentrations. For instance, Guo et al undertook a retrospective study encompassing 60 hospitalized patients, employing a nonlinear mixed-effects model to construct a population pharmacokinetic framework for VPA in Chinese patients. The foundational and ultimate objective function values for this model stood at 851.813 and 817.622, respectively, signifying a significant imprint of CYP2C19 genotypes on VPA clearance rate.41 However, a study by Smith et al involving 252 patients arrived at a contrary finding, unearthing no discernible linkage between CYP2C19 genotypes and VPA blood concentrations.22 Despite the trajectory of our study unveiling an inclination towards escalating standardized VPA blood concentrations across the NM, IM, and PM metabolic phenotypes, both univariate and multivariate analyses failed to unveil a substantive influence of CYP2C19 genotypes on standardized VPA blood concentrations among patients grappling with schizophrenia. This phenomenon could potentially be attributed to the relatively modest VPA doses administered to the participants in our study. For instance, the investigation conducted by Wu et al comprising 122 bipolar disorder patients ascertained that it was only when VPA doses exceeded 1000 mg/d that the VPA concentrations among patients of the CYP2C19 NM phenotype trailed those of the IM subgroup.42 In the realm of in vitro examinations, an array of uridine diphosphate glucuronosyltransferase (UGT) isoforms, encompassing UGT1A3, 1A4, 1A6, 1A8, 1A9, 1A10, 2B7, and 2B15, has been reported to partake in the process of VPA glucuronidation. Glucuronidation, alongside mitochondrial β-oxidation, comprises the dominant pathways governing adult VPA metabolism, while CYP2C19 occupies a relatively minor role.43,44 We propose that CYP2C19-mediated oxidation becomes the primary determinant of serum VPA levels only when VPA concentrations surpass major metabolic pathways. In our study, the average maintenance dose was 0.25 (0.25, 0.50) grams per day, with only 3 of 192 patients receiving high doses. This limited high dose uses likely had minimal effect on CYP2C19 enzyme activity.

The shift in drug-metabolizing enzyme phenotypes potentially elucidates the disjunction between genotype-predicted metabolic phenotypes and the genuine capacity for individual drug metabolism, a disparity often engendered by non-genetic elements.45,46 Investigations revolving around the classification of CYP2C19 activity have underscored a mere 40% alignment between genetically forecasted CYP2C19 phenotypes and actualized phenotypes, thereby unmasking the presence of phenotypic transformation.47 Drug interactions with metabolic enzymes emerge as a prevailing factor instigating such metamorphoses, frequently perturbing enzyme activity via mechanisms of competitive inhibition. A vivid illustration can be found in scenarios involving lansoprazole and voriconazole treatment. Rigorous prospective investigations have brought to light gene-centric CYP2C19 inhibition effects, with NM and IM phenotypes culminating in a reduction of activity by a factor of 2.2-fold and 1.9-fold, respectively.48 Moreover, the landscape of chronic liver disease is another variable that bears the potential to exert an impact on CYP2C19 activity. A forward-looking study delving into HCV-positive patients unearthed intricate interactions between genotype and the sphere of chronic liver disease.49 The intricate interplay between inflammation and drug metabolism ratios is also worth noting. For instance, a meticulous prospective study encompassing 36 patients subjected to fluconazole treatment embarked on unraveling the repercussions of inflammation on fluconazole metabolism ratios.50 Notably, a study by Kiss et al unearthed that CYP2C19 activity in individuals grappling with inflammatory ailments tended to be subpar when juxtaposed against the projected metabolic phenotypes.46 The underlying mechanisms and extent to which the CYP2C19 metabolic enzyme is influenced remain largely ambiguous. Studies posit that diseases might induce a transformative shift in the CYP2C19 enzyme’s phenotype. Specifically, in pathological conditions, when there’s a surge in pro-inflammatory cytokines, particularly interleukin-6 (IL-6), it may trigger a selective inflammatory response that both inhibits the synthesis of the CYP2C19 enzyme and reduces its abundance, subsequently diminishing its metabolic efficacy.51,52 The second-generation antipsychotic, Clozapine, may potentially harm mitochondria and incite the body to evoke a sophisticated inflammatory response, catalyzing the proliferation of pro-inflammatory cytokines such as IL-6, IL-17, GM-CSF, and IL12-p70, subsequently modulating their concentrations.53,54 Consequently, the inflammation associated with Clozapine might instigate a phenotypical transformation of the drug metabolic enzyme. In psychiatry, especially among schizophrenia patients, the co-prescription of various medications is common. This can include combinations of antipsychotics, antidepressants, and drugs for physical conditions. Our study deliberately excluded drugs like phenytoin, carbamazepine, and phenobarbital, known to increase VPA’s intrinsic clearance and alter its plasma concentration. However, how adjunctive drugs might affect the CYP2C19 enzyme is still unclear. The CYP2C19 genotype is not the only factor in its metabolic profile. Such influences could usher in a disparity between genotype and phenotype, prompting phenotypical metamorphoses.46 This might further illuminate the reason the CYP2C19 gene’s genetic variant did not markedly impact the normative VPA blood levels in the studied schizophrenia patients.

Additionally, laboratory experiments highlight that beyond CYP2C19, enzymes such as CYP2A6, CYP2B6, and CYP2C9 are integral to VPA’s metabolic pathway. Specifically, CYP2C9 orchestrates 75–80% of VPA’s terminal desaturation, its 4-hydroxylation, and 5-hydroxylation processes. CYP2A6 shoulders around half of the VPA 3-hydroxylation activity, with CYP2B6 governing the residual metabolic actions.55–57 The internal metabolism of VPA is notably complex. Apart from undergoing Phase I oxidation through the CYP450 enzyme system, VPA also experiences mitochondrial β-oxidation and Phase II glucuronidation facilitated by UGT. Crucially, this Phase II glucuronidation emerges as an essential metabolic route for VPA, largely steered by UGT1A6, UGT1A8, and UGT2B7, encompassing about half of the provided VPA dose.58–60 Consequently, one cannot dismiss the influence of CYP2A6, CYP2B6, CYP2C9, UGT1A6, and UGT2B7 on the metabolism of VPA.

Regression analysis from our study indicates no significant effect of age on VPA blood concentrations. This aligns with the population pharmacokinetic model established by Liu M X, wherein age is not deemed a factor influencing VPA blood concentration.61 Yet, studies by Wang et al and Smith et al found increasing VPA concentrations with age, particularly in the elderly, where intrinsic clearance decreases by 40%.22,62 The FDA drug label also advises reduced doses for the elderly due to decreased VPA clearance. These discrepancies may be linked to age-related metabolic activity of CYP2C19. Our study’s age range was 18–60 years, excluding both minors and those above 65. This exclusion might be associated with the altered CYP2C19 activity in minors and changes in VPA metabolism in the elderly, impacting liver and kidney drug clearance.63,64 Thus, the age effect on drug concentrations needs more comprehensive research in broader age ranges and larger samples.

Our research explores the gender-VPA blood concentration relationship. Females have about 30–50% less UGT activity for VPA daily dosages than males 59, potentially due to gender specific UGT1A gene control, as suggested by Kalthoff et al.65 Though VPA glucuronidation mainly happens in the liver, this does not fully explain the gender differences. Notably, females show a VPA bio-effective dose reabsorption rate of 46.2%, double that of males at 21.8%,66 hinting at bioavailability discrepancies. This could explain gender specific VPA metabolism variations. Such insights might impact gender tailored VPA dosing. Additionally, our findings confirm that as BMI rises, standardized VPA blood concentration drops, aligning with other research.21,67–69 This may result from the influence of body weight on VPA distribution volume: increased weight possibly expands this volume, leading to decreased blood concentrations 65. While certain CYP2C19 alleles may slow VPA metabolism in epilepsy patients, weight gain might speed it up. This could be why we observed no significant influence of the CYP2C19 genotype on VPA concentrations.

Our study acknowledges certain limitations, such as the exclusive focus on the CYP2C19 *2 and *3 alleles and the absence of broader genetic screening for other CYP variants that may impact VPA metabolism. Additionally, metabolic factors such as insulin levels and lipid profiles were not assessed, which could contribute to a more comprehensive understanding of VPA’s pharmacokinetics. Future studies should expand the genetic scope and integrate a wider metabolic assessment to refine personalized treatment strategies for schizophrenia.

Limitations

Owing to the clinical nature of this investigation, it was challenging to effectively regulate confounding variables that might influence drug metabolism, thereby leading to unavoidable limitations in the study outcomes. The research exclusively focused on the *2 and *3 allelic variants of CYP2C19 to determine the impact of genetic variant on the VPA plasma concentration. However, other genetic loci warrant further exploration. Among the 192 schizophrenia patients in this study, only 17 exhibited variants at the *3 loci, and no instances of the CYP2C19*3/*3 genotype were identified. This underscores that the correlation between this locus’s SNPs and VPA metabolism still requires further validation.

Conclusion

In Guangxi, CYP2C19 genetic variants are evident among the Zhuang and Han schizophrenia patients. The allelic frequencies, genotypes, and metabolic phenotypes are similarly distributed between the two ethnicities without statistical significance.

Gender and BMI can affect the standardized VPA blood concentrations in schizophrenia patients. Yet, in our study cohort of schizophrenia patients, the CYP2C19 genotype and age are not the major determinants of standardized VPA blood levels.

Acknowledgments

Research project planned by Guangxi Health Commission. The authors sincerely thank all the subjects for their participation in this study and all the medical staff who assisted in specimen collection.

Disclosure

The authors report no conflicts of interest in this work.

References

1. White C, Scott R, Paul CL, et al. Pharmacogenomics in the era of personalised medicine. Med J Aust. 2022;217(10):510–513. doi:10.5694/mja2.51759

2. Weinshilboum RM, Wang L. Pharmacogenomics: precision medicine and drug response. Mayo Clin Proc. 2017;92(11):1711–1722. doi:10.1016/j.mayocp.2017.09.001

3. Abbasi J. Getting pharmacogenomics into the clinic. JAMA. 2016;316(15):1533–1535. doi:10.1001/jama.2016.12103

4. Hockings JK, Pasternak AL, Erwin AL, et al. Pharmacogenomics: an evolving clinical tool for precision medicine. Cleve Clin J Med. 2020;87(2):91–99. doi:10.3949/ccjm.87a.19073

5. Cecchin E, Stocco G. Pharmacogenomics and personalized medicine. Genes. 2020;11(6):679. doi:10.3390/genes11060679

6. Scott SA, Sangkuhl K, Shuldiner AR, et al. PharmGKB summary: very important pharmacogene information for cytochrome P450, family 2, subfamily C, polypeptide 19. Pharmacogenet Genomics. 2012;22(2):159–165. doi:10.1097/FPC.0b013e32834d4962

7. Stajnko A, Runkel AA, Kosjek T, et al. Assessment of susceptibility to phthalate and DINCH exposure through CYP and UGT single nucleotide poly- morphisms. Environ Int. 2022;159:107046. doi:10.1016/j.envint.2021.107046

8. Biswas M, Shobana J, Jinda P, et al. Azole antifungals and inter-individual differences in drug metabolism: the role of pharmacogenomics and precision medicine. Expert Opin Drug Metab Toxicol. 2023;19(3):165–174. doi:10.1080/17425255.2023.2203860

9. Jukić MM, Haslemo T, Molden E, et al. Impact of CYP2C19 genotype on escitalopram exposure and therapeutic failure: a retrospective study based on 2087 patients. Am J Psychiatry. 2018;175(5):463–470. doi:10.1176/appi.ajp.2017.17050550

10. Bernal CJ, Aka I, Carroll RJ, et al. CYP2C19 phenotype and risk of proton pump inhibitor-associated infections. Pediatrics. 2019;144(6):e20190857. doi:10.1542/peds.2019-0857

11. Lee CR, Luzum JA, Sangkuhl K, et al. Clinical pharmacogenetics implementation consortium guideline for CYP2C19 genotype and clopidogrel therapy: 2022 update. Clin Pharmacol Ther. 2022;112(5):959–967. doi:10.1002/cpt.2526

12. Uppugunduri CR, Daali Y, Desmeules J, et al. Transcriptional regulation of CYP2C19 and its role in altered enzyme activity. Curr Drug Metab. 2012;13(8):1196–1204. doi:10.2174/138920012802850146

13. Hicks JK, Bishop JR, Sangkuhl K, et al.; Clinical Pharmacogenetics Implementation Consortium. Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and dosing of selective serotonin reuptake inhibitors. Clin Pharmacol Ther. 2015;98(2):127–134. doi:10.1002/cpt.147

14. Hiemke C, Bergemann N, Clement HW, et al. Consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology: 2017 edition. Pract Pharm Clin Remedies. 2022;25(02):97–118. Chinese.

15. Tseng YJ, Huang SY, Kuo CH, et al. Safety range of free valproic acid serum concentration in adult patients. PLoS One. 2020;15(9):e0238201. doi:10.1371/journal.pone.0238201

16. Lin K, Cao VFS, Au C, et al. Clinical pharmacokinetic monitoring of free valproic acid levels: a systematic review. Clin Pharmacokinet. 2022;61(10):1345–1363. doi:10.1007/s40262-022-01171-w

17. Thummel KE, Shen DD. Design and optimization of dosage regimens: pharmacokinetic data. In: Hardman JG, Limbird LE, Gilman AG, editors. Goodman and Gilman’s the Pharmacological Basis of Therapeutics. 10th ed. New York: McGraw-Hill; 2001:1917–2023.

18. Song C, Li X, Mao P, et al. Impact of CYP2C19 and CYP2C9 genetic variants on sodium valproate plasma concentration in patients with epilepsy. Eur J Hosp Pharm. 2022;29(4):198–201. doi:10.1136/ejhpharm-2020-002367

19. López-García MA, Feria-Romero IA, Serrano H, et al. Influence of genetic variants of CYP2D6, CYP2C9, CYP2C19 and CYP3A4 on antiepileptic drug metabolism in pediatric patients with refractory epilepsy. Pharmacol Rep. 2017;69(3):504–511. doi:10.1016/j.pharep.2017.01.007

20. Han R, Li Y, Wu W. Effects of CYP2C19 genetic polymorphism on plasma concentration of sodium valproate in epileptic patients. Neural Injury Funct Reconstr. 2015;10:295–297.

21. Wang S, Li J, Song M, et al. Effect of CYP2C19 polymorphisms on serum valproic level acid in Chinese Han patients with schizophrenia. Sci Rep. 2021;11(1):23150. doi:10.1038/s41598-021-02628-x

22. Smith RL, Haslemo T, Refsum H, et al. Impact of age, gender and CYP2C9/2C19 genotypes on dose-adjusted steady-state serum concentrations of valproic acid—a large-scale study based on naturalistic therapeutic drug monitoring data. Eur J Clin Pharmacol. 2016;72(9):1–6. doi:10.1007/s00228-016-2087-0

23. Fricke-Galindo I, Céspedes-Garro C, Rodrigues-Soares F, et al. Interethnic variation of CYP2C19 alleles, ‘predicted’ phenotypes and “measured” metabolic phenotypes across world populations. Pharmacogen J. 2015;16(2):113–123. doi:10.1038/tpj.2015.70

24. He L, Chen S, Li J, et al. Genetic and phenotypic frequency distribution of CYP2C9, CYP2C19 and CYP2D6 in over 3200 Han Chinese. Clin Exp Pharmacol Physiol. 2020;47(10):1659–1663. doi:10.1111/1440-1681.13357

25. Shu Y, Zhou HH. Individual and ethnic differences in CYP2C19 activity in Chinese populations. Zhong Guo Yao Li Xue Bao. 2000;21(3):193–199.

26. Yin SJ, Ni YB, Wang SM, et al. Differences in genotype and allele frequency distributions of polymorphic drug metabolizing enzymes CYP2C19 and CYP2D6 in mainland Chinese Mongolian, Hui and Han populations. J Clin Pharm Therapeutics. 2012;37(3):364–369. doi:10.1111/j.1365-2710.2011.01298.x

27. Ruan FW, Yang WY, Chen XL, et al. Analysis of distribution characteristics of CYP2C19 gene polymorphism in Han nationality patients with coronary heart disease in Dongguan. Lab Med Clinic. 2020;17(3):3. Chinese.

28. Bao Y, Qian FC, Fu TG, et al. Analysis of CYP2C19 gene polymorphism in population of Huzhou area. Chin J Health Lab Technol. 2022;32(19):4. Chinese.

29. Jin SL, Yan HM, Wu Y, et al. Analysis of the relationship between CYP2C19 gene polymorphism and valproic acid metabolism in han Chinese patients with mental illness in Hebei Province. Hebei Med. 2023;29(1):97–102. Chinese.

30. Zuo LJ, Guo T, Xia DY, et al. Allele and Genotype Frequencies of CYP3A4, CYP2C19, and CYP2D6 in Han, Uighur, Hui, and Mongolian Chinese Populations. Genet Test Mol Biomar. 2012;16(2):102–108. doi:10.1089/gtmb.2011.0084

31. Wang SM, Zhu AP, Li D, et al. Frequencies of genotypes and alleles of the functional SNPs in CYP2C19 and CYP2E1 in mainland Chinese Kazakh, Uygur and Han populations. J Hum Genet. 2009;54(6):372–375. doi:10.1038/jhg.2009.41

32. López-Fernández LA. Pharmacogenetics to avoid adverse drug reactions. J Personal Med. 2022;12(2):159. doi:10.3390/jpm12020159

33. Ma WB, Zhang LT, Ren XD, et al. Distribution of CYP2C19 gene polymorphisms in different sex, age and ethnio groups of patients with coronary heart disease in Shaanxi province and a comparative analysis with other areas in China. Int J Lab Med. 2020;41(5):5. Chinese.

34. Li J, Wang YX, Wang HP, et al. Distribution of CYP2C19 polymorphisms in Mongolian and Han nationals and the choice of specific antiplatelet drugs. Int J Clin Pharm. 2017;39(4):791–797. doi:10.1007/s11096-017-0451-5

35. Zhang S, Luo J, Xu Q, et al. Analysis of CYP2C19 gene polymorphism and metabolic phenotype in Alzheimer’s disease patients of Han Nationality in Guizhou. J Mod Lab Med. 2020;35(5):4. Chinese.

36. Huan LJ, Wang PY. Analysis of CYP2C19*2 and *3 locus gene polymorphisms in elderly Han population of Hubei. Int J Lab Med. 2021;42(24):3014–3017. Chinese.

37. Zhang JY, Yang XB, Li Y, et al. Preliminary study on CYP2C19gene polymorphism in patients with coronary heart disease in Yunnan province. Chin J Hospital Pharm. 2021;41(1):4. Chinese.

38. Jiang XR, Zhang YG, Lu J, et al. Distribution of CYP2C19 genetic polymorphisms in a north Chinese Han population with digestive tract diseases. Chin J Clin Exper Pathol. 2016;32(10):5. Chinese.

39. Wang Y, Zhao X, Lin J, et al. Association between CYP2C19 loss-of-function allele status and efficacy of clopidogrel for risk reduction among patients with minor stroke or transient ischemic attack. JAMA. 2016;316(1):70–78. doi:10.1001/jama.2016.8662

40. Botton MR, Whirl-Carrillo M, Del Tredici AL, et al. PharmVar GeneFocus: CYP2C19. Clin Pharmacol Ther. 2021;109(2):352–366. doi:10.1002/cpt.1973

41. Guo J, Huo Y, Li F, et al. Impact of gender, albumin, and CYP2C19 polymorphisms on valproic acid in Chinese patients: a population pharmacokinetic model. J Int Med Res. 2020;48(8):300060520952281. doi:10.1177/0300060520952281

42. Wu ZT, Wang GH, Xiao L, et al. Effect of CYP2C19 gene polymorphism on liver function changes induced by high valproic acid dosages in patients with bipolar disorder. Med J Wuhan Univ. 2021;42(01):119–122. Chinese.

43. Ghodke-Puranik Y, Thorn CF, Lamba JK, et al. Valproic acid pathway: pharmacokinetics and pharmacodynamics. Pharmacogenet Genom. 2013;23(4):236–241. doi:10.1097/FPC.0b013e32835ea0b2

44. Inoue K, Suzuki E, Yazawa R, et al. Influence of uridine diphosphate glucuronosyltransferase 2B7 −161C>T polymorphism on the concentration of valproic acid in pediatric epilepsy patients. Therap Drug Monitor. 2014;36(3):406. doi:10.1097/FTD.0000000000000012

45. Karle J, Bolbrinker J, Vogl S, et al. Influence of CYP2D6 genotype on tamoxifen efficacy in advanced breast cancer. Breast Cancer Res Treat. 2014;139(2):553–560. doi:10.1007/s10549-013-2565-3

46. Kiss ÁF, Vaskó D, Déri MT, et al. Combination of CYP2C19 genotype with non-genetic factors evoking phenoconversion improves phenotype prediction. Pharmacol Rep. 2018;70(3):525–532. doi:10.1016/j.pharep.2017.12.001

47. de Jong LM, Boussallami S, Sánchez-López E, et al. The impact of CYP2C19genotype on phenoconversion by concomitant medication. Front Pharmacol. 2023;14:1201906. doi:10.3389/fphar.2023.1201906

48. Miura M, Tada H, Yasui-Furukori N, et al. Enantioselective disposition of lansoprazole in relation to CYP2C19 genotypes in the presence of fluvoxamine. Br J Clin Pharmacol. 2005;60(1):61–68. doi:10.1111/j.1365-2125.2005.02381.x

49. Ohnishi A, Murakami S, Akizuki S, et al. In vivo metabolic activity of CYP2C19 and CYP3A in relation to CYP2C19 genetic polymorphism in chronic liver disease. Clin Pharmacol. 2005;45(11):1221–1229. doi:10.1177/0091270005280787

50. Veringa A, Ter Avest M, Span LF, et al. Voriconazole metabolism is influenced by severe inflammation: a prospective study. Antimicrob Chemother. 2017;72(1):261–267. doi:10.1093/jac/dkw349

51. Shah RR, Smith RL. Inflammation-induced phenoconversion of polymorphic drug metabolizing enzymes: hypothesis with implications for personalized medicine. Drug Metab Dispos. 2015;43(3):400. doi:10.1124/dmd.114.061093

52. Stanke-Labesque F, Gautier-Veyret E, Chhun S, et al. Inflammation is a major regulator of drug metabolizing enzymes and transporters: consequences for the personalization of drug treatment. Pharmacol Ther. 2020;215(9):107627. doi:10.1016/j.pharmthera.2020.107627

53. Contreras-Shannon V, Heart DL, Paredes RM, et al. Clozapine-induced mitochondria alterations and inflammation in brain and insulin-responsive cells. PLoS One. 2013;8(3):e59012. doi:10.1371/journal.pone.0059012

54. Himmerich H, Schönherr J, FuLda S, et al. Impact of antipsychotics on cytokine production in-vitro. J Psychiatr Res. 2011;45(10):1358–1365. doi:10.1016/j.jpsychires.2011.04.009

55. Liao QC, Shi JJ, Zhang Y, et al. Effects of cytochrome P450 isozymes 2A6, 2B6, 2C9 and 2C19 genetic polymorphisms on plasma concentration of sodium valproate. Chin J Neurol. 2013;46(2):82–86. Chinese.

56. Yoon HY, Min HA, Yee J, et al. Influence of CYP2C9 and CYP2A6 on plasma concentrations of valproic acid: a meta-analysis. Eur J Clin Pharmacol. 2020;76(8):1053–1058. doi:10.1007/s00228-020-02872-6

57. Kiang TKL, Ho PC, Reza AM, et al. Contribution of CYP2C9, CYP2A6, and CYP2B6 to valproic acid metabolism in hepatic microsomes from individuals with the CYP2C9*1/*1 genotype. Toxicol Sci. 2006;94(2):261–271. doi:10.1093/toxsci/kfl096

58. Mei S, Feng W, Zhu L, et al. Effect of CYP2C19, UGT1A8, and UGT2B7 on valproic acid clearance in children with epilepsy: a population pharmacokinetic model. Eur J Clin Pharmacol. 2018;74(8):1029–1036. doi:10.1007/s00228-018-2440-6

59. Song C, Li X, Zhang H, et al. Impact of MDR1 and UGT gene polymorphisms on sodium valproate plasma concentration in patients with epilepsy. Clin Lab. 2022;68(10):326–351. doi:10.7754/Clin.Lab.2022.220101

60. Guo Y, Hu C, He X, et al. Effects of UGT1A6, UGT2B7, and CYP2C9 genotypes on plasma concentrations of valproic acid in Chinese children with epilepsy. Drug Metab Pharmacokinet. 2012;27(5):536–542. doi:10.2133/dmpk.DMPK-11-NT-144

61. Liu MX. Pharmacokinetics of Valproic Acid Population and Meta-Analysis of the Effect of CYP2C19 Gene Polymorphism on Valproic Acid Plasma Concentration. Shihezi University; 2020. Chinese.

62. Wang Y, Hu W, Li Z. Influence of age and co-medication on the concentration and efficacy of valproic acid in Chinese epilepsy children. Pak J Pharm Sci. 2020;33(2):537–542.

63. Chen R. Impact of CYP2C19 Genotypes on Serum Concentrations of Valproic Acid in Epileptic Children. Fujian Medical University; 2017. Chinese.

64. Methaneethorn J. A systematic review of population pharmacokinetics of valproic acid. Br J Clin Pharmacol. 2018;84(5):816–834. doi:10.1111/bcp.13510

65. Kalthoff S, Winkler A, Freiberg N, et al. Gender matters: estrogen receptor alpha (ERα) and histone deacetylase (HDAC) 1 and 2 control the gender-specific transcriptional regulation of human uridine diphosphate glucuronosyltransferases genes (UGT1A). J Hepatol. 2013;59(4):797–804. doi:10.1016/j.jhep.2013.05.028

66. Ibarra M, Vázquez M, Fagiolino P, et al. Sex related differences on valproic acid pharmacokinetics after oral single dose. J Pharmacokinet Pharmacodyn. 2013;40(4):479–486. doi:10.1007/s10928-013-9323-3

67. Alqahtani S, Alandas N, Alsultan A. Estimation of apparent clearance of valproic acid in adult Saudi patients. Int J Clin Pharm. 2019;41(4):1056–1061. doi:10.1007/s11096-019-00864-w

68. Usman M, Shaukat QU, Khokhar MI, et al. Comparative pharmacokinetics of valproic acid among Pakistani and South Korean patients: a population pharmacokinetic study. PLoS One. 2022;17(8):e0272622. doi:10.1371/journal.pone.0272622

69. Mani B, Nair P, Sekhar A, et al. CYP2C19 & UGT1A6 genetic polymorphisms and the impact on Valproic acid-induced weight gain in people with epilepsy: prospective genetic association study. Epilepsy Res. 2021;177:106786. doi:10.1016/j.eplepsyres.2021.106786