The pharmacogenetics of treatment with olanzapine

Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: focus on antipsychotics

BACKGROUND

For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialized tools are used. Three tools have been proven useful to personalize drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging.

METHODS

In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 50 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)).

RESULTS

Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings.

CONCLUSION

All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimize treatment effects, minimize side effects and ultimately reduce the global burden of diseases, personalized drug treatment has not yet become the standard of care in psychiatry.

Case report: Avoiding intolerance to antipsychotics through a personalized treatment approach based on pharmacogenetics

Introduction

The standard approach to treatment in psychiatry is known as "treatment as usual" (TAU), in which the same types of treatment are administered to a group of patients. TAU often requires numerous dose adjustments and medication changes due to ineffectiveness and/or the occurrence of adverse drug reactions (ADRs). This process is not only time-consuming but also costly. Antipsychotic medications are commonly used to treat various psychiatric disorders such as schizophrenia and mood disorders. Some of the inter-individual differences in efficacy and ADRs observed in psychopharmacotherapy can be explained by genetic variability in the pharmacokinetics and pharmacodynamics of antipsychotics. A better understanding of (in)efficacy and possible ADRs can be achieved by pharmacogenetic analysis of genes involved in the metabolism of antipsychotics. Most psychotropic drugs are metabolized by genetically variable CYP2D6, CYP1A2, CYP3A4, and CYP2C19 enzymes. To demonstrate the utility of pharmacogenetic testing for tailoring antipsychotic treatment, in this paper, we present the case of a patient in whom a pharmacogenetic approach remarkably altered an otherwise intolerant or ineffective conventional TAU with antipsychotics.

Methods

In this case report, we present a 60-year-old patient with psychotic symptoms who suffered from severe extrapyramidal symptoms and a malignant neuroleptic syndrome during treatment with risperidone, fluphenazine, aripiprazole, brexpiprazole, and olanzapine. Therefore, we performed a pharmacogenetic analysis by genotyping common functional variants in genes involved in the pharmacokinetic pathways of prescribed antipsychotics, namely, CYP2D6, CYP3A4, CYP3A5, CYP1A2, ABCB1, and ABCG2. Treatment recommendations for drug-gene pairs were made according to available evidence-based pharmacogenetic recommendations from the Dutch Pharmacogenetics Working Group (DPWG) or Clinical Pharmacogenetics Implementation Consortium (CPIC).

Results

Pharmacogenetic testing revealed a specific metabolic profile and pharmacokinetic phenotype of the patient, which in retrospect provided possible explanations for the observed ADRs. Based on the pharmacogenetic results, the choice of an effective and safe medication proved to be much easier. The psychotic symptoms disappeared after treatment, while the negative symptoms persisted to a lesser extent.

Conclusion

With the case presented, we have shown that taking into account the pharmacogenetic characteristics of the patient can explain the response to antipsychotic treatment and associated side effects. In addition, pharmacogenetic testing enabled an informed choice of the most appropriate drug and optimal dose adjustment. This approach makes it possible to avoid or minimize potentially serious dose-related ADRs and treatment ineffectiveness. However, due to the complexity of psychopathology and the polypharmacy used in this field, it is of great importance to conduct further pharmacokinetic and pharmacogenetic studies to better assess gene-drug and gene-gene-drug interactions.

Human Data on Pharmacokinetic Interactions of Cannabinoids: A Narrative Review

Concomitant use of cannabinoids with other drugs may result in pharmacokinetic drug-drug interactions, mainly due to the mechanism involving Phase I and Phase II enzymes and/or efflux transporters. Cannabinoids are not only substrates but also inhibitors or inducers of some of these enzymes and/or transporters. This narrative review aims to provide the available information reported in the literature regarding human data on the pharmacokinetic interactions of cannabinoids with other medications. A search on Pubmed/Medline, Google Scholar, and Cochrane Library was performed. Some studies were identified with Google search. Additional articles of interest were obtained through cross-referencing of published literature. All original research papers discussing interactions between cannabinoids, used for medical or recreational/adult-use purposes, and other medications in humans were included. Thirty-two studies with medicinal or recreational/adult-use cannabis were identified (seventeen case reports/series, thirteen clinical trials, and two retrospective analyses). In three of these studies, a bidirectional pharmacokinetic drug-drug interaction was reported. In the rest of the studies, cannabinoids were the perpetrators, as in most of them, concentrations of cannabinoids were not measured. In light of the widespread use of prescribed and non-prescribed cannabinoids with other medications, pharmacokinetic interactions are likely to occur. Physicians should be aware of these potential interactions and closely monitor drug levels and/or responses. The existing literature regarding pharmacokinetic interactions is limited, and for some drugs, studies have relatively small cohorts or are only case reports. Therefore, there is a need for high-quality pharmacological studies on cannabinoid-drug interactions.

Olanzapine Pharmacokinetics: A Clinical Review of Current Insights and Remaining Questions

Olanzapine is one of the most widely used antipsychotics since its initial approval by the US Food and Drug Administration in 1996 and has undergone extensive pharmacokinetic study. Despite being utilized in clinical psychiatry for decades, there remain questions regarding the variety of available formulations, the utility of therapeutic drug monitoring, altered kinetic properties in special populations/medical illnesses, the use of high-dose olanzapine, and drug interactions, among many others. We performed a narrative literature review of olanzapine pharmacokinetics in June 2023 using the US National Library of Medicine's PubMed.gov resource (https://www.ncbi.nlm.nih.gov/pubmed) and Google Scholar. Herein, we review clinically relevant aspects of olanzapine pharmacokinetic data while highlighting knowledge gaps and potential areas of future study.

Utility of pharmacogenetic testing to optimise antidepressant pharmacotherapy in youth: a narrative literature review

Pharmacogenetics (PGx) is the study and application of how interindividual differences in our genomes can influence drug responses. By evaluating individuals' genetic variability in genes related to drug metabolism, PGx testing has the capabilities to individualise primary care and build a safer drug prescription model than the current "one-size-fits-all" approach. In particular, the use of PGx testing in psychiatry has shown promising evidence in improving drug efficacy as well as reducing toxicity and adverse drug reactions. Despite randomised controlled trials demonstrating an evidence base for its use, there are still numerous barriers impeding its implementation. This review paper will discuss the management of mental health conditions with PGx-guided treatment with a strong focus on youth mental illness. PGx testing in clinical practice, the concerns for its implementation in youth psychiatry, and some of the barriers inhibiting its integration in clinical healthcare will also be discussed. Overall, this paper provides a comprehensive review of the current state of knowledge and application for PGx in psychiatry and summarises the capabilities of genetic information to personalising medicine for the treatment of mental ill-health in youth.

DRD2, DRD3, and HTR2A Single-Nucleotide Polymorphisms Involvement in High Treatment Resistance to Atypical Antipsychotic Drugs

BACKGROUND

The objective of this study was to investigate the DRD2 rs1800497, rs1799732, rs1801028, DRD3 rs6280, and HTR2A rs6314, rs7997012, and rs6311 single-nucleotide polymorphism (SNP) correlations with resistance to second-generation antipsychotics (SGAs) in a real-world sample of patients with treatment-resistant mental disorders.

METHODS

We divided 129 participants into a high treatment resistance (HTR) group (current treatment with two SGAs, or clozapine, or classic neuroleptics for a failure of previous SGAs trials) and a low treatment resistance (LTR) group (current treatment with one atypical antipsychotic). We used Next-Generation Sequencing on DNA isolated from peripheral blood samples to analyze the polymorphisms. We performed logistic regression to search for predictors of HTR membership.

RESULTS

A diagnosis of schizophrenia significantly predicted the HTR membership compared to other diagnoses. Other predictors were the DRD3 rs6280 C|T (OR = 22.195) and T|T (OR = 18.47) vs. C|C, HTR2A rs7997012 A|G vs. A|A (OR = 6.859) and vs. G|G (OR = 2.879), and DRD2 rs1799732 I|I vs. D|I (OR = 12.079) genotypes.

CONCLUSIONS

A diagnosis of schizophrenia and the DRD2 rs1799732, DRD3 rs6280, and HTR2A rs7997012 genotypes can predict high treatment resistance to SGAs.

Pharmacogenetics in the Treatment of Huntington’s Disease: Review and Future Perspectives

Huntington’s disease (HD) is an autosomal dominant progressive brain disorder, caused by a pathological expansion of a CAG repeat that encodes the huntingtin gene. This genetic neurodegenerative rare disease is characterized by cognitive, motor, and neuropsychiatric manifestations. The aim of the treatment is symptomatic and addresses the hyperkinetic disorders (chorea, dystonia, myoclonus, tics, etc.) and the behavioural and cognitive disturbances (depression, anxiety, psychosis, etc.) associated with the disease. HD is still a complex condition in need of innovative and efficient treatment. The long-term goal of pharmacogenetic studies is to use genotype data to predict the effective treatment response to a specific drug and, in turn, prevent potential undesirable effects of its administration. Chorea, depression, and psychotic symptoms have a substantial impact on HD patients’ quality of life and could be better controlled with the help of pharmacogenetic knowledge. We aimed to carry out a review of the available publications and evidence related to the pharmacogenetics of HD, with the objective of compiling all information that may be useful in optimizing drug administration. The impact of pharmacogenetic information on the response to antidepressants and antipsychotics is well documented in psychiatric patients, but this approach has not been investigated in HD patients. Future research should address several issues to ensure that pharmacogenetic clinical use is appropriately supported, feasible, and applicable.

[The relationship of cytochrome P450 isoforms with the efficacy and safety of antipsychotic and antidepressant therapy]

Cytochrome P450 (CYP450) is the leading enzyme in the biotransformation of most psychotropic drugs. CYP450 gene polymorphisms determine a patient's endophenotype with respect to the activity of enzymes of the family and affect the metabolism of prescribed antipsychotics and antidepressants. Categorizing patients by endophenotype during genotyping is likely to help simplify the selection of therapy in clinical practice. Co-prescribing drugs that may be inhibitors or inducers of CYP450 isoforms, in turn, may lead to adverse reactions or no effect of therapy. The article presents a compilation of known pharmacogenetic recommendations regarding the four major endophenotypes of metabolizers.

Association Studies in Clinical Pharmacogenetics

In recent times, the progress of Clinical Pharmacogenetics has been remarkable [...].

Metabolic, genetic, and pharmacokinetic parameters for the prediction of olanzapine efficacy

Clinical use of the a olanzapine has significantly different individual-to-individual outcomes. Accordingly, this study aimed to develop a means of predicting response to olanzapine using a combined approach based on pharmacokinetics, pharmacometabonomics, and genetic polymorphism. The olanzapine pharmacokinetics of 19 healthy volunteers treated with orally disintegrating tablets were determined using high-performance liquid chromatography-tandem mass spectrometry. Metabolic profiling and phenotyping were performed on the blood samples that remained after pharmacokinetic analysis using ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry. Uridine diphosphate-glucuronosyltransferase (UGT), tyrosine hydroxylase (TH), γ-aminobutyric acid transaminase (GABA-T), and succinic semialdehyde dehydrogenase (SSADH) were identified as key genes. The single nucleotide polymorphism genotypes most related to drug metabolism were investigated by polymerase chain reaction and Sanger sequencing. Forty-one metabolites (p < 0.05) are increased or decreased after treatment with olanzapine. Tryptophan metabolism, norepinephrine metabolism, and γ-aminobutyric acid metabolism were identified as being related to the effects of olanzapine. Subjects carrying rs1641031 AC and CC exhibited a 59.2% increase in the mean peak concentration (C_max) value and a 25.33% decrease in the mean oral clearance rate (CL/F) value, compared to that in subjects with the GABA-T rs1641031 AA genotype (p < 0.05). Moreover, polymorphism of the GABA-T gene has an impact on the metabolism of 5-hydroxytryptamine. Lysophosphatidylethanolamine (0:0/18:3), lysophosphatidylethanolamine (0:0/22:5), and octadecatrienoic acid distinguish subjects with high and low olanzapine drug oral clearance and are thus identified as biomarkers for predicting its efficacy.