Conserved immunomodulatory transcriptional networks underlie antipsychotic-induced weight gain

Although antipsychotics, such as olanzapine, are effective in the management of psychiatric conditions, some patients experience excessive antipsychotic-induced weight gain (AIWG). To illuminate pathways underlying AIWG, we compared baseline blood gene expression profiles in two cohorts of mice that were either prone (AIWG-P) or resistant (AIWG-R) to weight gain in response to olanzapine treatment for two weeks. We found that transcripts elevated in AIWG-P mice relative to AIWG-R are enriched for high-confidence transcriptional targets of numerous inflammatory and immunomodulatory signaling nodes. Moreover, these nodes are themselves enriched for genes whose disruption in mice is associated with reduced body fat mass and slow postnatal weight gain. In addition, we identified gene expression profiles in common between our mouse AIWG-P gene set and an existing human AIWG-P gene set whose regulation by immunomodulatory transcription factors is highly conserved between species. Finally, we identified striking convergence between mouse AIWG-P transcriptional regulatory networks and those associated with body weight and body mass index in humans. We propose that immunomodulatory transcriptional networks drive AIWG, and that these networks have broader conserved roles in whole body-metabolism.

Investigation of Clozapine and Olanzapine Reactive Metabolite Formation and Protein Binding by Liquid Chromatography-Tandem Mass Spectrometry

Drug-induced toxicity has, in many cases, been linked to oxidative metabolism resulting in the formation of reactive metabolites and subsequent covalent binding to biomolecules. Two structurally related antipsychotic drugs, clozapine (CLZ) and olanzapine (OLZ), are known to form similar nitrenium ion reactive metabolites. CLZ-derived reactive metabolites have been linked to agranulocytosis and hepatotoxicity. We have studied the oxidative metabolism of CLZ and OLZ as well as two known metabolites of CLZ, desmethyl-CLZ (DCLZ), and CLZ-N-oxide (CLZ-NO), using in vitro rat liver microsomal (RLM) incubations with glutathione (GSH) trapping of reactive metabolites and liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS). Reactive metabolite binding to selected standard peptides and recombinant purified human proteins was also evaluated. Bottom-up proteomics was performed using two complementary proteases, prefractionation of peptides followed by LC-HRMS/MS for elucidating modifications of target proteins. Induced RLM was selected to form reactive metabolites enzymatically to assess the complex profile of reactive metabolite structures and their binding potential to standard human proteins. Multiple oxidative metabolites and several different GSH adducts were found for CLZ and OLZ. Modification sites were characterized on human glutathione S-transferase (hGST) alpha 1 (OLZ-modified at Cys112), hGST mu 2 (OLZ at Cys115), and hGST pi (CLZ, DCLZ, CLZ-NO and OLZ at Cys170), human microsomal GST 1 (hMGST1, CLZ and OLZ at Cys50), and human serum albumin (hSA, CLZ at Cys34). Furthermore, two modified rat proteins, microsomal GST 1 (CLZ and OLZ at Cys50) and one CYP (OLZ-modified, multiple possible isoforms), from RLM background were also characterized. In addition, direct effects of the reactive metabolite modifications on proteins were observed, including differences in protease cleavage specificity, chromatographic behavior, and charge-state distributions.

Understanding variability in the pharmacokinetics of atypical antipsychotics - focus on clozapine, olanzapine and aripiprazole population models

Antipsychotic medicines are widely used for the management of psychotic symptoms regardless of the underlying diagnosis. Most atypical antipsychotics undergo extensive metabolism prior to excretion. Various factors may influence their pharmacokinetics, particularly elimination, leading to highly variable drug concentrations between individual patients following the same dosing regimen. Population pharmacokinetic approach, based on nonlinear mixed effects modeling, is a useful tool to identify covariates explaining pharmacokinetic variability, as well as to characterize and distinguish unexplained residual and between-subject (interindividual) variability. In addition, this approach allows the use of both sparsely and intensively sampled data. In this paper, we reviewed the pharmacokinetic characteristics of clozapine, olanzapine and aripiprazole, focusing on a population modeling approach. In particular, models based on a nonlinear mixed effects approach performed by NONMEM^® software in order to identify and quantify sources of pharmacokinetic variability are presented. Population models were identified through systematic searches of PubMed and sixteen studies were selected. Some of the factors identified that significantly contribute to variability in elimination among clozapine, olanzapine, and aripiprazole are demographic characteristics, body weight, genetic polymorphism, smoking and in some cases drug interactions. Scientific research based on pharmacometric modeling is useful to further characterize sources of variability and their combined effect.

Revolutionizing Therapeutic Drug Monitoring with the Use of Interstitial Fluid and Microneedles Technology

While therapeutic drug monitoring (TDM) that uses blood as the biological matrix is the traditional gold standard, this practice may be impossible, impractical, or unethical for some patient populations (e.g., elderly, pediatric, anemic) and those with fragile veins. In the context of finding an alternative biological matrix for TDM, this manuscript will provide a qualitative review on: (1) the principles of TDM; (2) alternative matrices for TDM; (3) current evidence supporting the use of interstitial fluid (ISF) for TDM in clinical models; (4) the use of microneedle technologies, which is potentially minimally invasive and pain-free, for the collection of ISF; and (5) future directions. The current state of knowledge on the use of ISF for TDM in humans is still limited. A thorough literature review indicates that only a few drug classes have been investigated (i.e., anti-infectives, anticonvulsants, and miscellaneous other agents). Studies have successfully demonstrated techniques for ISF extraction from the skin but have failed to demonstrate commercial feasibility of ISF extraction followed by analysis of its content outside the ISF-collecting microneedle device. In contrast, microneedle-integrated biosensors built to extract ISF and perform the biomolecule analysis on-device, with a key feature of not needing to transfer ISF to a separate instrument, have yielded promising results that need to be validated in pre-clinical and clinical studies. The most promising applications for microneedle-integrated biosensors is continuous monitoring of biomolecules from the skin's ISF. Conducting TDM using ISF is at the stage where its clinical utility should be investigated. Based on the advancements described in the current review, the immediate future direction for this area of research is to establish the suitability of using ISF for TDM in human models for drugs that have been found suitable in pre-clinical experiments.

In Vitro Characterization of the Human Liver Microsomal Kinetics and Reaction Phenotyping of Olanzapine Metabolism

Olanzapine (OLZ) is an atypical antipsychotic used in the treatment of schizophrenia and related psychoses. The metabolism of OLZ is complex and incompletely characterized. This study aimed to elucidate the enzymes and pathways involved in the metabolism of OLZ and to determine the kinetics of OLZ oxidation and glucuronidation by human liver microsomes, recombinant cytochrome P450 (rP450) enzymes, and recombinant UDP-glucuronosyltransferase (rUGT) enzymes. An ultra-performance liquid chromatography-mass spectrometry method was developed and validated to quantify OLZ, its four oxidative metabolites (N-desmethyl-OLZ, 2-hydroxymethyl-OLZ, 7-hydroxy-OLZ, and OLZ-N-oxide), and two N-glucuronides (OLZ-10-N-glucuronide and OLZ-4'-N-glucuronide). Consistent with previous reports, UGT1A4, CYP1A2, and flavin-containing monooxygenase 3 play major roles in catalyzing the formation of OLZ-10-N-glucuronide, 7-hydroxy-OLZ, and OLZ-N-oxide, respectively. In addition, a previously uncharacterized major contribution of CYP2C8 to OLZ-N-demethylation was demonstrated. The kinetics of OLZ metabolite formation (Km and Vmax) by human liver microsomes, rP450 enzymes, and rUGT enzymes were characterized in the presence of bovine serum albumin [2% (w/v)]. Consistent with the known effect of bovine serum albumin on CYP1A2, CYP2C8, and UGT1A4 activities, Km values reported here are lower than previously reported values for OLZ metabolic pathways. In addition to CYP1A2-mediated OLZ-N-demethylation, these results suggest that other P450 enzymes, particularly CYP2C8, contribute significantly to oxidative OLZ metabolism through catalysis of OLZ-N-demethylation.

Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice

AIM

To determine optimal sampling strategies to allow the calculation of clinical pharmacokinetic parameters for selected antipsychotic medicines using a pharmacometric approach.

METHODS

This study utilized previous population pharmacokinetic parameters of the antipsychotic medicines aripiprazole, clozapine, olanzapine, perphenazine, quetiapine, risperidone (including 9-OH risperidone) and ziprasidone. d-optimality was utilized to identify time points which accurately predicted the pharmacokinetic parameters (and expected error) of each drug at steady-state. A standard two stage population approach (STS) with MAP-Bayesian estimation was used to compare area under the concentration-time curves (AUC) generated from sparse optimal time points and rich extensive data. Monte Carlo Simulation (MCS) was used to simulate 1000 patients with population variability in pharmacokinetic parameters. Forward stepwise regression analysis was used to determine the most predictive time points of the AUC for each drug at steady-state.

RESULTS

Three optimal sampling times were identified for each antipsychotic medicine. For aripiprazole, clozapine, olanzapine, perphenazine, risperidone, 9-OH risperidone, quetiapine and ziprasidone the CV% of the apparent clearance using optimal sampling strategies were 19.5, 8.6, 9.5, 13.5, 12.9, 10.0, 16.0 and 10.7, respectively. Using the MCS and linear regression approach to predict AUC, the recommended sampling windows were 16.5-17.5 h, 10-11 h, 23-24 h, 19-20 h, 16.5-17.5 h, 22.5-23.5 h, 5-6 h and 5.5-6.5 h, respectively.

CONCLUSION

This analysis provides important sampling information for future population pharmacokinetic studies and clinical studies investigating the pharmacokinetics of antipsychotic medicines.

Abnormal olanzapine toxicokinetic profiles--population pharmacokinetic analysis

CONTEXT

Olanzapine is widely used in the treatment of schizophrenia and it is becoming more frequently responsible for overdoses. Standard pharmacokinetic models do not fit to the toxic concentration data.

OBJECTIVE

The aim of present study is to investigate the reasons for an abnormal olanzapine plasma concentration time curve in the range of toxic concentrations. Two hypotheses were verified: entering the enterohepatic cycle, and drug deposition and its desorption from activated charcoal used for gastrointestinal decontamination.

MATERIALS AND METHODS

One-hundred thirty-five plasma concentration data from 21 patients hospitalized for acute olanzapine poisoning were analyzed with the use of the population pharmacokinetic approach. A non-linear mixed-effects modeling approach with Monolix 4.3.1 was employed.

RESULTS

A model assuming gallbladder emptying at irregular intervals was developed. Also, a model that describes desorption of olanzapine from the charcoal surface, in which the dose is divided into two absorbed fractions, was constructed. The analysis has found gastrointestinal decontamination and previous olanzapine treatment, as the significant covariates for toxicokinetic parameters of olanzapine.

CONCLUSION

Our study provides interesting models for investigation of toxic concentration of olanzapine, which may also be used as the basis for further model development for other drugs as well. The investigated population was not large enough to reliably confirm any of the proposed models. It would be well worth continuing this study with more substantial data. Also, any additional information about olanzapine metabolite concentration could be vital.

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.

Interactions between valproic acid and quetiapine/olanzapine in the treatment of bipolar disorder and the role of therapeutic drug monitoring

OBJECTIVES

The anticonvulsant valproic acid and the atypical antipsychotics olanzapine and quetiapine provide synergistic mood-stabilising, antidepressant and antipsychotic activities in the treatment of bipolar and schizoaffective disorders. Existing literature shows that pharmacokinetic and pharmacodynamics drug-drug interactions (DDIs) possibly occur with the use of such a combination. Clinical reports of a possible interaction between the drugs leading to an increased risk of adverse drug reactions have also emerged. The main objective of this paper is to review the incidence of DDIs between the anticonvulsant and the antipsychotics, to postulate the possible mechanisms of the interaction and to establish whether certain target populations are at an increased susceptibility to such interactions. The usefulness of therapeutic drug monitoring (TDM) of the antipsychotics to monitor for an interaction was also assessed. A systematic database search was carried out using the search engine provided by PubMed using the following key words: olanzapine, quetiapine, valproic acid, pharmacokinetic drug-drug interaction, bipolar disorder, therapeutic drug monitoring.

KEY FINDINGS

Evidence of a possible clinically relevant DDI between valproic acid and both antipsychotics has been uncovered. A possible mechanism for the interactions has been postulated, and the importance of TDM has been discussed.

SUMMARY

Further research is required to determine whether DDIs occur with the concurrent use of valproic acid and olanzapine or quetiapine, and to investigate the potential of TDM as a clinical tool in improving pharmacotherapy and preventing toxicity.

Determination of olanzapine and N-desmethyl-olanzapine in plasma using a reversed-phase HPLC coupled with coulochemical detection: correlation of olanzapine or N-desmethyl-olanzapine concentration with metabolic parameters

BACKGROUND

Olanzapine (OLZ) is one of the most prescribed atypical antipsychotic drugs but its use is associated with unfavorable metabolic abnormalities. N-desmethyl-olanzapine (DMO), one of the OLZ metabolites by CYP1A2, has been reported to have a normalizing action on metabolic abnormalities, but this remains unclear. Our aim was to explore the correlation between the concentrations of OLZ or DMO with various metabolic parameters in schizophrenic patients.

METHODS

The chromatographic analysis was carried out with a solvent delivery system coupled to a Coulochem III coulometric detector to determine OLZ and DMO simultaneously in OLZ-treated patients. The correlation between the concentration of OLZ or DMO and the metabolic parameters was analyzed by the Spearman rank order correlation method (r s).

PRINCIPAL FINDINGS

The established analytical method met proper standards for accuracy and reliability and the lower limitation of quantification for each injection of DMO or OLZ was 0.02 ng. The method was successfully used for the analysis of samples from nonsmoking patients (n = 48) treated with OLZ in the dosage range of 5-20 mg per day. There was no correlation between OLZ concentrations and tested metabolic parameters. DMO concentrations were negatively correlated with glucose (r s = -0.45) and DMO concentrations normalized by doses were also negatively correlated with insulin levels (r s = -0.39); however, there was a marginally positive correlation between DMO and homocysteine levels (r s = +0.38).

CONCLUSIONS

The observed negative correlations between levels of DMO and glucose or insulin suggest a metabolic normalization role for DMO regardless of its positive correlation with a known cardiovascular risk factor, homocysteine. Additional studies of the mechanisms underlying DMO's metabolic effects are warranted.

Considering CYP1A2 phenotype and genotype for optimizing the dose of olanzapine in the management of schizophrenia

INTRODUCTION

Schizophrenia, a mental disorder, is a debilitating condition which typically strikes young people in their early 20's. Antipsychotic medications are widely prescribed for the treatment of schizophrenia however a balancing act is necessary to provide the correct dose to each patient. It is suggested that a large number of patients discontinue antipsychotic pharmacotherapy because the treatments provided do not always reduce the positive symptoms of the disease, while many have adverse effects on the patients. This implies that neither the incorrect drug nor the optimal dosage for that patient is achieved.

AREAS COVERED

The current review investigates variability in response to olanzapine with a specific focus on the common intrinsic and extrinsic factors that influence both olanzapine and CYP1A2 activity. Furthermore, the authors discuss the utilization of phenotyping and genotyping of CYP1A2 and their potential utility in clinical practice for olanzapine dosing regimens. The authors also consider the potential of pharmacometrics compared to pharmacogenomics as a tool to personalize medicine.

EXPERT OPINION

Careful consideration must be given to the impact of a genetic variant on the disposition of a drug prior to implementing genetic 'tests' to determine response. CYP1A2 phenotypic assessment can yield important information regarding the disposition of olanzapine; however, it relies on the accuracy of the metric and the minimal impact of other metabolic pathways. The application of pharmacometrics provides an effective method to establish covariates that significantly influence olanzapine disposition which can incorporate phenotype and/or genotype.

Clozapine and therapeutic drug monitoring: is there sufficient evidence for an upper threshold?

RATIONALE

Clozapine levels are advocated in the monitoring of patients on this drug and have now been used for a number of years. A safety-related threshold has also been proposed, as well as therapeutic lower and upper thresholds. While there has been reasonable consensus regarding a lower therapeutic threshold, this is not the case for the upper thresholds.

OBJECTIVES

Our aim was to review available evidence related to upper thresholds.

METHODS

We carried out an electronic search of different databases and a manual search of articles between 1960 and 2011, cross-referencing the following terms with clozapine-interactions, monitoring, pharmacokinetics, plasma levels, serum levels, and toxicity.

RESULTS

Sixty-nine articles met our search criteria and these could be divided into reviews (11), studies (24), and case reports (35). Study quality was evaluated, and none met criteria for a prospective, randomized controlled trial specifically addressing higher plasma levels, e.g., >500 ng/ml. Case reports emphasize in particular the impact of interactions, e.g., antidepressants and smoking. There is clear evidence indicating a dose-related increased risk of seizures, at least to 500-600 mg/day, but a lack of data to suggest such a relationship between plasma levels, dose, and side effects linked to safety, e.g., seizures, myocarditis, and agranulocytosis. The very limited evidence addressing an upper threshold related to clinical response suggests a "ceiling effect" in the range of 600-838 ng/ml.

CONCLUSIONS

It appears that the current safety-related threshold is not supported by evidence. There may be an upper threshold for clinical response, beyond which chance of response falls off, although further studies are warranted.