Influence of FMO1 and 3 polymorphisms on serum olanzapine and its N-oxide metabolite in psychiatric patients

CYP1A2 expression rather than genotype is associated with olanzapine concentration in psychiatric patients

Olanzapine is a commonly prescribed atypical antipsychotic agent for treatment of patients with schizophrenia and bipolar disorders. Previous in vitro studies using human liver microsomes identified CYP1A2 and CYP2D6 enzymes being responsible for CYP-mediated metabolism of olanzapine. The present work focused on the impact of CYP1A2 and CYP2D6 genetic polymorphisms as well as of CYP1A2 metabolizing capacity influenced by non-genetic factors (sex, age, smoking) on olanzapine blood concentration in patients with psychiatric disorders (N = 139). CYP2D6 genotype-based phenotype appeared to have negligible contribution to olanzapine metabolism, whereas a dominant role of CYP1A2 in olanzapine exposure was confirmed. However, CYP1A2 expression rather than CYP1A2 genetic variability was demonstrated to be associated with olanzapine concentration in patients. Significant contribution of - 163C > A (rs762551), the most common SNP (single nucleotide polymorphism) in CYP1A2 gene, to enhanced inducibility was confirmed by an increase in CYP1A2 mRNA expression in smokers carrying - 163A, and smoking was found to have appreciable impact on olanzapine concentration normalized by the dose/bodyweight. Furthermore, patients' olanzapine exposure was in strong association with CYP1A2 expression; therefore, assaying CYP1A2 mRNA level in leukocytes can be an appropriate tool for the estimation of patients' olanzapine metabolizing capacity and may be relevant in optimizing olanzapine dosage.

Quantification of olanzapine and its three metabolites by liquid chromatography-tandem mass spectrometry in human body fluids obtained from four deceased, and confirmation of the reduction from olanzapine N-oxide to olanzapine in whole blood in vitro

PURPOSE

Quantification of olanzapine (OLZ) and its metabolites such as N-desmethylolanzapine (DM-O), 2-hydroxymethylolanzapine (2H-O) and olanzapine N-oxide (NO-O) in five kinds of human body fluids including whole blood by liquid chromatography (LC)-tandem mass spectrometry (MS/MS) has been presented; the quantification methods were carefully devised and validated using the matrix-matched calibration and standard addition methods.

METHODS

OLZ and its three metabolites were extracted from 40 μL each of body fluids by two-step liquid-liquid separations. The samples and reagents were pre-cooled in a container filled with ice for the extraction because of the thermal instability of OLZ and its three metabolites especially in whole blood.

RESULTS

The limits of quantification (LOQs) of OLZ and 2H-O were 0.05 ng/mL and those of DM-O and NO-O were 0.15 ng/mL in whole blood and urine, respectively. The concentrations of OLZ and its metabolites in heart whole blood, pericardial fluid, stomach contents, bile and urine were determined for two cadavers and those in whole blood and urine for the other two cadavers. The reduction from NO-O to OLZ was observed at 25 ℃ in whole blood in vitro.

CONCLUSIONS

To our knowledge, this is the first report on the quantification of metabolites of olanzapine in the authentic human body fluids by LC-MS/MS as well as on the confirmation of in vitro reduction from NO-O to OLZ in whole blood that seems to have induced the quick decrease of NO-O.

Individualizing busulfan dose in specific populations and evaluating the risk of pharmacokinetic drug-drug interactions

INTRODUCTION

Busulfan is an alkylating agent widely used in the conditioning of hematopoietic stem cell transplantation possessing a complex metabolism and a large interindividual and intra-individual variability, especially in children. Combined with the strong rationale of busulfan PK/PD relationships, factors altering its clearance (e.g., weight, age, and GST-A genetic polymorphism mainly) can also affect clinical outcomes.

AREAS COVERED

This review aims to provide an overview of the current knowledge on busulfan pharmacokinetics, its pharmacokinetics variabilities in pediatric populations, drug-drug interactions (DDI), and their consequences regarding dose individualization. This review was based on medical literature up until October 2021.

EXPERT OPINION

To ensure effective busulfan exposure in pediatrics, different weight-based nomograms have been established to determine busulfan dosage and provided improved results (65 - 80% of patients correctly exposed). In addition to nomograms, therapeutic drug monitoring (TDM) of busulfan measuring plasmatic concentrations to estimate busulfan pharmacokinetic parameters can be used. TDM is now widely carried out in routine practices and aims to ensure the targeting of the reported therapeutic windows by individualizing busulfan dosing based on the clearance estimations from a previous dose.

Roles of selected non-P450 human oxidoreductase enzymes in protective and toxic effects of chemicals: review and compilation of reactions

This is an overview of the metabolic reactions of drugs, natural products, physiological compounds, and other (general) chemicals catalyzed by flavin monooxygenase (FMO), monoamine oxidase (MAO), NAD(P)H quinone oxidoreductase (NQO), and molybdenum hydroxylase enzymes (aldehyde oxidase (AOX) and xanthine oxidoreductase (XOR)), including roles as substrates, inducers, and inhibitors of the enzymes. The metabolism and bioactivation of selected examples of each group (i.e., drugs, “general chemicals,” natural products, and physiological compounds) are discussed. We identified a higher fraction of bioactivation reactions for FMO enzymes compared to other enzymes, predominately involving drugs and general chemicals. With MAO enzymes, physiological compounds predominate as substrates, and some products lead to unwanted side effects or illness. AOX and XOR enzymes are molybdenum hydroxylases that catalyze the oxidation of various heteroaromatic rings and aldehydes and the reduction of a number of different functional groups. While neither of these two enzymes contributes substantially to the metabolism of currently marketed drugs, AOX has become a frequently encountered route of metabolism among drug discovery programs in the past 10–15 years. XOR has even less of a role in the metabolism of clinical drugs and preclinical drug candidates than AOX, likely due to narrower substrate specificity.

The pharmacogenetics of treatment with olanzapine

Genetic polymorphism in olanzapine-metabolizing enzymes, transporters and drug targets is associated with alterations in safety and efficacy. The aim of this systematic review is to describe all clinically relevant pharmacogenetic information on olanzapine and to propose clinically actionable variants. Two hundred and eighty-four studies were screened; 76 complied with the inclusion criteria and presented significant associations. DRD2 Taq1A (rs1800497) *A1, LEP -2548 (rs7799039) G and CYP1A2*1F alleles were related to olanzapine effectiveness and safety variability in several studies, with a high level of evidence. DRD2 -141 (rs1799732) Ins, A-241G (rs1799978) G, DRD3 Ser9Gly (rs6280) Gly, HTR2A rs7997012 A, ABCB1 C3435T (rs1045642) T and G2677T/A (rs2032582) T and UGT1A4*3 alleles were related to safety, effectiveness and/or pharmacokinetic variability with moderated level of evidence.

Genetic Polymorphisms Associated With the Pharmacokinetics, Pharmacodynamics and Adverse Effects of Olanzapine, Aripiprazole and Risperidone

Olanzapine, aripiprazole and risperidone are atypical antipsychotics or neuroleptics widely used for schizophrenia treatment. They induce various adverse drug reactions depending on their mechanisms of action: metabolic effects, such as weight gain and alterations of glucose and lipid metabolism; hyperprolactinemia and extrapyramidal effects, such as tremor, akathisia, dystonia, anxiety and distress. In this review, we listed polymorphisms associated with individual response variability to olanzapine, aripiprazole and risperidone. Olanzapine is mainly metabolized by cytochrome P450 enzymes, CYP1A2 and CYP2D6, whereas aripiprazole and risperidone metabolism is mainly mediated by CYP2D6 and CYP3A4. Polymorphisms in these genes and other enzymes and transporters, such as enzymes from the uridine 5'-diphospho-glucuronosyltransferase (UGT) family and ATP-binding cassette sub-family B member 1 (ABCB1), are associated to differences in pharmacokinetics. The three antipsychotics act on dopamine and serotonin receptors, among others, and several studies found associations between polymorphisms in these genes and variations in the incidence of adverse effects and in the response to the drug. Since olanzapine is metabolized by CYP1A2, a lower starting dose should be considered in patients treated with fluvoxamine or other CYP1A2 inhibitors. Regarding aripiprazole, a reduced dose should be administered in CYP2D6 poor metabolizers (PMs). Additionally, a reduction to a quarter of the normal dose is recommended if the patient is treated with concomitant CYP3A4 inhibitors. Risperidone dosage should be reduced for CYP2D6 PMs and titrated for CYPD6 ultrarapid metabolizers (UMs). Moreover, risperidone dose should be evaluated when a CYP2D6, CYP3A4 or ABCB1 inhibitor is administered concomitantly.

The Impact of Smoking, Sex, Infection, and Comedication Administration on Oral Olanzapine: A Population Pharmacokinetic Model in Chinese Psychiatric Patients

BACKGROUND AND OBJECTIVE: Prior olanzapine population pharmacokinetic (PPK) models have focused on the effects of sex and smoking on olanzapine clearance. This PPK model in Chinese adult psychiatric patients also investigated the influence of comedications and co-occurrence of infections on olanzapine clearance, and explored how to personalize oral olanzapine dosage in the clinical setting.

METHODS

A total of 1546 serum concentrations from 354 patients were collected in this study. A one-compartment model with first-order absorption was employed to develop the PPK model using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, co-occurrence of infection and concomitant medications (including dangguilonghui tablets, a Chinese herbal medicine for constipation). Bootstrap validation (1000 runs) and external validation of 50 patients were employed to evaluate the final model. Simulations were performed to explore the personalization of olanzapine dosing after stratification by sex, smoking, and comedication with valproate.

RESULTS

Typical estimates for the absorption rate constant (K_a), apparent clearance (CL/F), and apparent distribution volume (V/F) were 0.30 h^-1, 12.88 L/h, and 754.41 L, respectively. Olanzapine clearance was increased by the following variables: 1.23-fold by male sex, 1.23-fold by smoking, 1.23-fold by comedication with valproate, 1.16-fold by sertraline, and 2.01-fold by dangguilonghui tablets. Olanzapine clearance was decreased by the following variables: 0.75-fold by co-occurrence of infection, 0.70-fold by fluvoxamine, and 0.78-fold by perphenazine. The model evaluation indicated that the final model's performance was good, stable, and precise.

CONCLUSION

This study contributes to the personalization of oral olanzapine dosing, but further studies should be performed to verify the effects of infection and comedications, including valproate and dangguilonghui.

Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women

Adverse drug reactions are the fourth leading cause of death in the US. Although women take longer to metabolize medications and experience twice the risk of developing adverse reactions compared with men, these sex differences are not comprehensively understood. Real-world clinical data provide an opportunity to estimate safety effects in otherwise understudied populations, i.e., women. These data, however, are subject to confounding biases and correlated covariates. We present AwareDX, a pharmacovigilance algorithm that leverages advances in machine learning to predict sex risks. Our algorithm mitigates these biases and quantifies the differential risk of a drug causing an adverse event in either men or women. AwareDX demonstrates high precision during validation against clinical literature and pharmacogenetic mechanisms. We present a resource of 20,817 adverse drug effects posing sex-specific risks. AwareDX, and this resource, present an opportunity to minimize adverse events by tailoring drug prescription and dosage to sex.

Genetic Association of Olanzapine Treatment Response in Han Chinese Schizophrenia Patients

Olanzapine, a second-generation antipsychotic medication, plays a critical role in current treatment of schizophrenia (SCZ). It has been observed that the olanzapine responses in schizophrenia treatment are different across individuals. However, prediction of this individual-specific olanzapine response requires in-depth knowledge of biomarkers of drug response. Here, we performed an integrative investigation on 238 Han Chinese SCZ patients to identify predictive biomarkers that were associated with the efficacy of olanzapine treatment. This study applied HaloPlex technology to sequence 143 genes from 79 Han Chinese SCZ patients. Our result suggested that there were 12 single nucleotide polymorphisms (SNPs) had significant association with olanzapine response in Han Chinese SCZ patients. Using MassARRAY platform, we tested that if these 12 SNPs were also statistically significant in 159 other SCZ patients (independent cohort) and the combined 238 SCZ patients (composed of two tested cohorts). The result of this analysis showed that 2 SNPs were significantly associated with the olanzapine response in both independent cohorts (rs324026, P = 0.023; rs12610827, P = 0.043) and combined SCZ patient population (rs324026, adjust P = 0.014; rs12610827, adjust P = 0.012). Our study provides systematic analyses of genetic variants associated with olanzapine responses of Han Chinese SCZ patients. The discovery of these novel biomarkers of olanzapine-response will facilitate to advance future olanzapine treatment specific for Han Chinese SCZ patients.

Physiologically Based Pharmacokinetic Modeling Approach to Predict Drug-Drug Interactions With Ethionamide Involving Impact of Genetic Polymorphism on FMO3

The widely used second-line antituberculosis drug ethionamide shows wide interindividual variability in its disposition; however, the relevant factors affecting this phenomenon have not been characterized. We previously reported the major contribution of flavin-containing monooxygenase 3 (FMO3) in the reductive elimination pathway of ethionamide. In this study, ethionamide metabolism was potentially inhibited by methimazole in vitro. The drug-drug interaction leading to methimazole affecting the disposition of ethionamide mediated by FMO3 was then quantitated using a bottom-up approach with a physiologically based pharmacokinetic framework. The maximum concentration (C_max ) and area under the curve (AUC) of ethionamide were estimated to increase by 13% and 16%, respectively, when coadministered with methimazole. Subsequently, we explored the effect of FMO3 genetic polymorphism on metabolic capacity, by constructing 2 common functional variants, Lys¹⁵⁸ -FMO3 and Gly³⁰⁸ -FMO3. Compared to the wild type, recombinant Lys¹⁵⁸ -FMO3 and Gly³⁰⁸ -FMO3 variants significantly decreased the intrinsic clearance of ethionamide by 2% and 24%, respectively. Two prevalent functional variants of FMO3 were predicted to affect ethionamide disposition, with mean ratios of C_max and AUC of up to 1.5 and 1.7, respectively, in comparison with the wild type. In comparing single ethionamide administration with the wild type, simulations of the combined effects of comedications and FMO3 genetic polymorphism estimated that the C_max and AUC ratios of ethionamide increased up to 1.7 and 2.0, respectively. These findings suggested that FMO3-mediated drug-drug interaction and genetic polymorphism could be important determinants of interindividual heterogeneity in ethionamide disposition that need to be considered comprehensively to optimize the personalized dosing of ethionamide.

Drug metabolism by flavin-containing monooxygenases of human and mouse

INTRODUCTION

Flavin-containing monooxygenases (FMOs) play an important role in drug metabolism. Areas covered: We focus on the role of FMOs in the metabolism of drugs in human and mouse. We describe FMO genes and proteins of human and mouse; the catalytic mechanism of FMOs and their significance for drug metabolism; differences between FMOs and CYPs; factors contributing to potential underestimation of the contribution of FMOs to drug metabolism; the developmental and tissue-specific expression of FMO genes and differences between human and mouse; and factors that induce or inhibit FMOs. We discuss the contribution of FMOs of human and mouse to the metabolism of drugs and how genetic variation of FMOs affects drug metabolism. Finally, we discuss the utility of animal models for FMO-mediated drug metabolism in humans. Expert opinion: The contribution of FMOs to drug metabolism may be underestimated. As FMOs are not readily induced or inhibited and their reactions are generally detoxifications, the design of drugs that are metabolized predominantly by FMOs offers clinical advantages. Fmo1^(-/-),Fmo2^(-/-),Fmo4^(-/-) mice provide a good animal model for FMO-mediated drug metabolism in humans. Identification of roles for FMO1 and FMO5 in endogenous metabolism has implications for drug therapy and initiates an exciting area of research.

Trimethylamine and Trimethylamine N-Oxide, a Flavin-Containing Monooxygenase 3 (FMO3)-Mediated Host-Microbiome Metabolic Axis Implicated in Health and Disease

Flavin-containing monooxygenase 3 (FMO3) is known primarily as an enzyme involved in the metabolism of therapeutic drugs. On a daily basis, however, we are exposed to one of the most abundant substrates of the enzyme trimethylamine (TMA), which is released from various dietary components by the action of gut bacteria. FMO3 converts the odorous TMA to nonodorous TMA N-oxide (TMAO), which is excreted in urine. Impaired FMO3 activity gives rise to the inherited disorder primary trimethylaminuria (TMAU). Affected individuals cannot produce TMAO and, consequently, excrete large amounts of TMA. A dysbiosis in gut bacteria can give rise to secondary TMAU. Recently, there has been much interest in FMO3 and its catalytic product, TMAO, because TMAO has been implicated in various conditions affecting health, including cardiovascular disease, reverse cholesterol transport, and glucose and lipid homeostasis. In this review, we consider the dietary components that can give rise to TMA, the gut bacteria involved in the production of TMA from dietary precursors, the metabolic reactions by which bacteria produce and use TMA, and the enzymes that catalyze the reactions. Also included is information on bacteria that produce TMA in the oral cavity and vagina, two key microbiome niches that can influence health. Finally, we discuss the importance of the TMA/TMAO microbiome-host axis in health and disease, considering factors that affect bacterial production and host metabolism of TMA, the involvement of TMAO and FMO3 in disease, and the implications of the host-microbiome axis for management of TMAU.

Individual differences in in vitro and in vivo metabolic clearances of the antipsychotic drug olanzapine from non-smoking and smoking Japanese subjects genotyped for cytochrome P4502D6 and flavincontaining monooxygenase 3

OBJECTIVE

The antipsychotic olanzapine is reportedly metabolized by inducible human cytochrome P450 (CYP) 1A2 and variable copy-number CYP2D6 and polymorphic flavin-containing monooxygenase 3 (FMO3) in different pathways. We investigated individual differences in the metabolite formation and clearance of olanzapine in vitro and in vivo.

METHODS

Human liver microsomal olanzapine oxidation activities were evaluated, and plasma concentrations of olanzapine were determined in 21 Japanese patients (mean age: 50 years, range: 32-69 years, 14 male and 7 female, including 6 smokers) genotyped for CYP2D6 (*1, *5, and *10) and FMO3 (E158K, C197fsX, R205C, V257M, E308G, and R500X).

RESULTS

Furafylline (a CYP1A2 inhibitor), quinidine (a CYP2D6 inhibitor), and heat treatment (inactivates FMO3) suppressed liver microsomal metabolic clearance of olanzapine by approximately 30%. Olanzapine N-demethylation and N-oxygenation were found to be catalyzed by CYP1A2 and CYP2D6 and by CYP2D6 and FMO3, respectively, in experiments using liver microsomes and recombinant enzymes. Plasma concentrations and clearance of olanzapine were not affected by CYP2D6 or FMO3 genotypes or smoking behavior.

CONCLUSIONS

Olanzapine clearance was not affected by CYP2D6 or FMO3 genotypes or smoking behavior as a single factor under the present conditions because olanzapine clearance is mediated by multiple enzymes involved in two major and one minor pathways.

No influence of CYP3A43 rs472660G> A on steady-state serum olanzapine concentrations in white psychiatric patients

The potential involvement of CYP3A43 in systemic olanzapine (OLA) metabolism has been suggested by one reported association between the intronic polymorphism CYP3A43 rs472660G>A and OLA clearance in 235 White and African-American patients. Trough plasma OLA concentrations in AA carriers were predicted on average 48% lower than in GG carriers. In the current study, we evaluated this finding by genotyping 374 White psychiatric patients on long-term OLA treatment. No significant difference in dose-adjusted trough serum OLA concentrations was observed between the seven AA carriers identified and the other two genotypes, without (P=0.6) or with (P=0.23) adjustment for additional covariates previously known to influence systemic OLA exposure. Because of the low prevalence of the rs472660 AA genotype in White populations (2%), larger study cohorts are needed for future association confirmation. Overall, CYP3A43 rs472660 is not likely to be a major contributor towards variability in systemic OLA exposure among White patients.

Pharmacokinetics and pharmacogenomics of daunorubicin in children: a report from the Children's Oncology Group

PURPOSE

We explored the impact of obesity, body composition, and genetic polymorphisms on the pharmacokinetics (PK) of daunorubicin in children with cancer.

PATIENTS AND METHODS

Patients ≤21 years receiving daunorubicin as an infusion of any duration <24 h for any type of cancer were eligible. Plasma drug concentrations were measured by high-performance liquid chromatography. Body composition was measured by dual-energy X-ray absorptiometry. Obesity was defined as a BMI >95% for age or as body fat >30%. NONMEM was used to perform PK model fitting. The Affymetrix DMET chip was used for genotyping. The impact of genetic polymorphisms was investigated using SNP/haplotype association analysis with estimated individual PK parameters.

RESULTS

A total of 107 subjects were enrolled, 98 patients had PK sampling, and 50 patients underwent DNA analysis. Population estimates for daunorubicin clearance and volume of distribution were 116 L/m(2)/h ± 14% and 68.1 L/m(2) ± 24%, respectively. Apparent daunorubicinol clearance and volume of distribution were 26.8 L/m(2)/h ± 5.6% and 232 L/m(2) ± 10%, respectively. No effect of body composition or obesity was observed on PK. Forty-four genes with variant haplotypes were tested for association with PK. FMO3-H1/H3 genotype was associated with lower daunorubicin clearance than FMO3-H1/H1, p = 0.00829. GSTP1*B/*B genotype was also associated with lower daunorubicin clearance compared to GSTP1*A/*A, p = 0.0347. However, neither of these associations was significant after adjusting for multiple testing by either Bonferroni or false discovery rate correction.

CONCLUSIONS

We did not detect an effect of body composition or obesity on daunorubicin PK. We found suggestive associations between FMO3 and GSTP1 haplotypes with daunorubicin PK that could potentially affect efficacy and toxicity.

Meta-analysis: the effects of smoking on the disposition of two commonly used antipsychotic agents, olanzapine and clozapine

OBJECTIVE

To clarify the effects of smoking on the disposition of two commonly used antipsychotics, olanzapine and clozapine, and to create standards to adjust the doses of these drugs in clinical practice based on the smoking status.

DESIGN

A meta-analysis was conducted by searching MEDLINE, Scopus and the Cochrane Library for relevant prospective and retrospective studies.

INCLUDED STUDIES

We included the studies that investigated the effects of smoking on the concentration to dose (C/D) ratio of olanzapine or clozapine.

PRIMARY OUTCOME MEASURE

The weighted mean difference was calculated using a DerSimonian-Laird random effects model, along with 95% CI.

RESULTS

Seven association studies, comprising 1094 patients (652 smokers and 442 non-smokers) with schizophrenia or other psychiatric disorders, were included in the meta-analysis of olanzapine. The C/D ratio was significantly lower in smokers than in non-smokers (p<0.00001), and the mean difference was -0.75 (ng/mL)/(mg/day) (95% CI -0.89 to -0.61). Therefore, it was estimated that if 10 and 20 mg/day of olanzapine would be administered to smokers, about 7 and 14 mg/day, respectively, should be administered to non-smokers in order to obtain the equivalent olanzapine concentration. Four association studies of clozapine were included in the meta-analysis of clozapine, comprising 196 patients (120 smokers and 76 non-smokers) with schizophrenia or other psychiatric disorders. The C/D ratio was significantly lower in smokers than in non-smokers (p<0.00001), and the mean difference was -1.11 (ng/mL)/(mg/day) (95% CI -1.53 to -0.70). Therefore, it was estimated that if 200 and 400 mg/day of clozapine would be administered to smokers, about 100 and 200 mg/day, respectively, should be administered to non-smokers.

CONCLUSIONS

We suggest that the doses of olanzapine and clozapine should be reduced by 30% and 50%, respectively, in non-smokers compared with smokers in order to obtain an equivalent olanzapine or clozapine concentration.