Identification of a novel polymorphism associated with reduced clozapine concentration in schizophrenia patients-a genome-wide association study adjusting for smoking habits

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.

The potential influence of estrogen-containing oral contraception on clozapine metabolism in a patient with known pharmacogenomic status

Clozapine is primarily metabolized via cytochrome P450(CYP)1A2 and to a lesser extent CYP3A4, CYP2C19, and CYP2D6. Metabolic inhibitors of clozapine, such as fluvoxamine and ciprofloxacin, are important to recognize to avoid adverse drug events. Estrogen-containing oral contraceptives (eOCPs) are weaker CYP1A2 and CYP2C19 inhibitors but are associated with a 2-fold increase of clozapine concentrations. The potential for phenoconversion due to a CYP genetic polymorphism can add additional complexities when considering drug interactions. A case report is presented of a suspected interaction between newly initiated clozapine and a prescribed eOCP for which the patient's pharmacogenomic status was known. A 17-year-old, nonsmoking, White female with a history of schizophrenia was initiated on clozapine 12.5 mg at bedtime with a plan to increase by 25 mg every 4 days in the outpatient setting. The patient was a known rapid CYP1A2 metabolizer without identified sources of CYP1A2 induction and a CYP2C19 rapid metabolizer. Based on pharmacogenomic testing, there was no suspicion for significant gene-drug interactions. Yet, as the patient was prescribed an eOCP, a clozapine concentration was obtained after reaching 150 mg at bedtime. This steady-state clozapine concentration was found to be 560 ng/mL, correlating with worsening sedation and constipation. Given ongoing side effects, clozapine was lowered to 100 mg at bedtime; however, ongoing intolerance ultimately led to clozapine discontinuation. This case highlights the potential interaction between clozapine and eOCP in a CYP1A2 and CYP2C19 rapid metabolizer, leading to clozapine intolerance and discontinuation. The concomitant use of clozapine and eOCPs should be undertaken judiciously.

Prediction of antipsychotics efficacy based on a polygenic risk score: a real-world cohort study

Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.

Solanidine is a sensitive and specific dietary biomarker for CYP2D6 activity

BACKGROUND

Individual assessment of CYP enzyme activities can be challenging. Recently, the potato alkaloid solanidine was suggested as a biomarker for CYP2D6 activity. Here, we aimed to characterize the sensitivity and specificity of solanidine as a CYP2D6 biomarker among Finnish volunteers with known CYP2D6 genotypes.

RESULTS

Using non-targeted metabolomics analysis, we identified 9152 metabolite features in the fasting plasma samples of 356 healthy volunteers. Machine learning models suggested strong association between CYP2D6 genotype-based phenotype classes with a metabolite feature identified as solanidine. Plasma solanidine concentration was 1887% higher in genetically poor CYP2D6 metabolizers (gPM) (n = 9; 95% confidence interval 755%, 4515%; P = 1.88 × 10-11), 74% higher in intermediate CYP2D6 metabolizers (gIM) (n = 89; 27%, 138%; P = 6.40 × 10-4), and 35% lower in ultrarapid CYP2D6 metabolizers (gUM) (n = 20; 64%, - 17%; P = 0.151) than in genetically normal CYP2D6 metabolizers (gNM; n = 196). The solanidine metabolites m/z 444 and 430 to solanidine concentration ratios showed even stronger associations with CYP2D6 phenotypes. Furthermore, the areas under the receiver operating characteristic and precision-recall curves for these metabolic ratios showed equal or better performances for identifying the gPM, gIM, and gUM phenotype groups than the other metabolites, their ratios to solanidine, or solanidine alone. In vitro studies with human recombinant CYP enzymes showed that solanidine was metabolized mainly by CYP2D6, with a minor contribution from CYP3A4/5. In human liver microsomes, the CYP2D6 inhibitor paroxetine nearly completely (95%) inhibited the metabolism of solanidine. In a genome-wide association study, several variants near the CYP2D6 gene associated with plasma solanidine metabolite ratios.

CONCLUSIONS

These results are in line with earlier studies and further indicate that solanidine and its metabolites are sensitive and specific biomarkers for measuring CYP2D6 activity. Since potato consumption is common worldwide, this biomarker could be useful for evaluating CYP2D6-mediated drug-drug interactions and to improve prediction of CYP2D6 activity in addition to genotyping.

Effect of the NFIB rs28379954 T>C polymorphism on CYP2D6-catalyzed metabolism of solanidine

Cytochrome P450 2D6 (CYP2D6) is important for metabolism of 20%-25% of all clinically used drugs. Many known genetic variants contribute to the large interindividual variability in CYP2D6 metabolism, but much is still unexplained. We recently described that nuclear factor 1B (NFIB) regulates hepatic CYP2D6 expression with the minor allele of NFIB rs28379954 T>C significantly increasing CYP2D6-mediated risperidone metabolism. In this study, we investigated the effect of NFIB T>C on metabolism of solanidine, a dietary CYP2D6 substrate. Analyses of solanidine and metabolites (M414, M416, and M444) were performed by ultra-high performance liquid chromatography-high-resolution mass spectrometry in a cohort of 463 CYP2D6-genotyped patients of which with 58 (12.5%) carried NFIB TC (n = 56) or CC (n = 2). Increased metabolism of solanidine was found in CYP2D6 normal metabolizers (NMs; n = 258, 55.7%) carrying the NFIB C variant (n = 27, 5.8%) with 2.83- and 3.38-fold higher M416-to-solanidine (p = 0.039) and M444-to-solanidine (p = 0.046) ratios, respectively, whereas this effect was not significant among intermediate metabolizers (n = 166, 35.9%) (p ≥ 0.09). Importantly, no effect of the NFIB polymorphism on solanidine metabolism was seen in TC or CC carriers lacking CYP2D6 activity (poor metabolizers, n = 30, 6.5%, p ≥ 0.74). Furthermore, the NFIB polymorphism significantly explained variability in solanidine metabolism (M414 p = 0.013, M416 p = 0.020, and M416 and M444 p = 0.009) in multiple linear regression models for each metabolic ratio in the entire population, correcting for covariates (including CYP2D6 genotypes). Thus, the study confirms the effect of NFIB in regulating CYP2D6 activity, suggesting an about 200% increase in CYP2D6-mediated clearance in NMs being NFIB CT or CC carriers, comprising around 6% of Europeans.

How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.

Predicting clozapine dose required to achieve a therapeutic plasma concentration - A comparison of a population algorithm and three algorithms based on gene variant models

BACKGROUND

Clozapine is the most effective antipsychotic but requires careful titration to therapeutic blood levels. Methods to predict therapeutic doses are based on population data.

AIMS

We aimed to construct a model based on genetic variants which accurately predicted plasma levels for clozapine.

METHOD

We measured clozapine plasma levels in patients on a stable dose of clozapine who were known to be fully compliant. Measured plasma levels were adjusted for sampling time and dose. Hepatic enzyme variants were analysed and models were constructed to predict the required dose. These predictions were compared with a standard population-based algorithm.

RESULTS

We measured plasma clozapine concentrations in 18 adherent patients on stable doses of clozapine and recorded the exact timing of sampling. For the algorithm-predicted dose, the mean difference was -49.9 mg/day ((SD 155.9), r = 0.36) from the actual dose required to give a plasma concentration of 0.35 ng/ml. The gene variant activity score predicted a dose for which the mean difference was -43.5 mg/day ((SD 140.1), r = 0.55). For the gene variant activity score with omeprazole correction predicted dose, the mean difference was -31.0 mg/day ((SD 140.8), r = 0.54), and with the gene variant CYP1A2 inducibility predicted dose the mean difference was 44.9 mg/day ((SD 160.8), r = 0.32).

CONCLUSION

Our gene variant activity score with omeprazole correction gave the best estimate of the clozapine dose required to achieve a minimum therapeutic plasma concentration. The use of this model will allow safer titration of clozapine and may reduce the need for plasma-level monitoring during titration.

Treatment-Resistant Schizophrenia, Clozapine Resistance, Genetic Associations, and Implications for Precision Psychiatry: A Scoping Review

Treatment-resistant schizophrenia (TRS) is often associated with severe burden of disease, poor quality of life and functional impairment. Clozapine is the gold standard for the treatment of TRS, although it is also known to cause significant side effects in some patients. In view of the burgeoning interest in the role of genetic factors in precision psychiatry, we conducted a scoping review to narratively summarize the current genetic factors associated with TRS, clozapine resistance and side effects to clozapine treatment. We searched PubMed from inception to December 2022 and included 104 relevant studies in this review. Extant evidence comprised associations between TRS and clozapine resistance with genetic factors related to mainly dopaminergic and serotoninergic neurotransmitter systems, specifically, TRS and rs4680, rs4818 within COMT, and rs1799978 within DRD2; clozapine resistance and DRD3 polymorphisms, CYP1A2 polymorphisms; weight gain with LEP and SNAP-25 genes; and agranulocytosis risk with HLA-related polymorphisms. Future studies, including replication in larger multi-site samples, are still needed to elucidate putative risk genes and the interactions between different genes and their correlations with relevant clinical factors such as psychopathology, psychosocial functioning, cognition and progressive changes with treatment over time in TRS and clozapine resistance.

Pharmacokinetics and pharmacogenomics of clozapine in an ancestrally diverse sample: a longitudinal analysis and genome-wide association study using UK clinical monitoring data

BACKGROUND

The antipsychotic, clozapine, is the only licensed drug against the treatment-resistant symptoms that affect 20-30% of people with schizophrenia. Clozapine is markedly underprescribed, partly because of concerns about its narrow therapeutic range and adverse drug reaction profile. Both concerns are linked to drug metabolism, which varies across populations globally and is partly genetically determined. Our study aimed to use a cross-ancestry genome-wide association study (GWAS) design to investigate variations in clozapine metabolism within and between genetically inferred ancestral backgrounds, to discover genomic associations to clozapine plasma concentrations, and to assess the effects of pharmacogenomic predictors across different ancestries.

METHODS

In this GWAS, we analysed data from the UK Zaponex Treatment Access System clozapine monitoring service as part of the CLOZUK study. We included all available individuals with clozapine pharmacokinetic assays requested by their clinicians. We excluded people younger than 18 years, or whose records contained clerical errors, or with blood drawn 6-24 h after dose, a clozapine or norclozapine concentration less than 50 ng/mL, a clozapine concentration of more than 2000 ng/mL, a clozapine-to-norclozapine ratio outside of the 0·5-3·0 interval, or a clozapine dose of more than 900 mg/day. Using genomic information, we identified five biogeographical ancestries: European, sub-Saharan African, north African, southwest Asian, and east Asian. We did pharmacokinetic modelling, a GWAS, and a polygenic risk score association analysis using longitudinal regression analysis with three primary outcome variables: two metabolite plasma concentrations (clozapine and norclozapine) and the clozapine-to-norclozapine ratio.

FINDINGS

19 096 pharmacokinetic assays were available for 4760 individuals in the CLOZUK study. After data quality control, 4495 individuals (3268 [72·7%] male and 1227 [27·3%] female; mean age 42·19 years [range 18-85]) linked to 16 068 assays were included in this study. We found a faster average clozapine metabolism in people of sub-Saharan African ancestry than in those of European ancestry. By contrast, individuals with east Asian or southwest Asian ancestry were more likely to be slow clozapine metabolisers than those with European ancestry. Eight pharmacogenomic loci were identified in the GWAS, seven with significant effects in non-European groups. Polygenic scores generated from these loci were associated with clozapine outcome variables in the whole sample and within individual ancestries; the maximum variance explained was 7·26% for the metabolic ratio.

INTERPRETATION

Longitudinal cross-ancestry GWAS can discover pharmacogenomic markers of clozapine metabolism that, individually or as polygenic scores, have consistent effects across ancestries. Our findings suggest that ancestral differences in clozapine metabolism could be considered for optimising clozapine prescription protocols for diverse populations.

FUNDING

UK Academy of Medical Sciences, UK Medical Research Council, and European Commission.

Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores

BACKGROUND

Treatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework.

METHODS

We used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high.

RESULTS

After controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (β = 12.22, SE = 3.78, p = .001), CLOZUK3 (β = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (β = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006).

CONCLUSIONS

The schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia.

Pharmacogenomics in treatment of depression and psychosis: an update

Genetic factors can, to a certain extent, successfully predict the therapeutic effects, metabolism, and adverse reactions of drugs. This research field, pharmacogenomics, is well developed in oncology and is currently expanding in psychiatry. Here, we summarize the latest development in pharmacogenomic psychiatry, where results of several recent large studies indicate a true benefit and cost-effectiveness of pre-emptive genotyping for more successful psychotherapy. However, it is apparent that we still lack knowledge of many additional heritable genetic factors of importance for explanation of the interindividual differences in response to psychiatric drugs. Thus, more effort to further develop pharmacogenomic psychiatry should be invested to achieve a broader clinical implementation.

Challenges and opportunities associated with rare-variant pharmacogenomics

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

Cytochrome P450 polymorphism: From evolution to clinical use

The cytochromes P450s can be divided in two groups, those of high importance for endogenous functions being evolutionary quite stable and those participating in detoxification of drugs and other xenobiotics having less important endogenous functions. In the latter group extensive genetic diversity has been allowed and in addition this is of high importance for survival in different environments. The genetic polymorphisms in these genes have evolved to some extent based on dietary restrictions and environmental factors and have not been subject of conservation due to less importance for survival. In cases of high dietary selection events, gene multiplication and amplification events have been seen. The different variants in genes encoding drug metabolizing enzymes can be used as genetic biomarkers (pharmacogenomic labels) for adjustment of drug treatment leading to less adverse drug reactions and better response. Indeed, this has improved the use of personalized medicine, although the missing heredity seen based on twin studies indicates that there are indeed many more genetic variants to be discovered before one can achieve a satisfactory relationship between genotype and phenotype with respect to drug metabolism and toxicity.

The Polymorphic Nuclear Factor NFIB Regulates Hepatic CYP2D6 Expression and Influences Risperidone Metabolism in Psychiatric Patients

The genetic background for interindividual variability of the polymorphic CYP2D6 enzyme activity remains incompletely understood and the role of NFIB genetic polymorphism for this variability was evaluated in this translational study. We investigated the effect of NFIB expression in vitro using 3D liver spheroids, Huh7 cells, and the influence of the NFIB polymorphism on metabolism of risperidone in patients in vivo. We found that NFIB regulates several important pharmacogenes, including CYP2D6. NFIB inhibited CYP2D6 gene expression in Huh7 cells and NFIB expression in livers was predominantly nuclear and reduced at the mRNA and protein level in carriers of the NFIB rs28379954 T>C allele. Based on 604 risperidone treated patients genotyped for CYP2D6 and NFIB, we found that the rate of risperidone hydroxylation was elevated in NFIB rs28379954 T>C carriers among CYP2D6 normal metabolizers, resulting in a similar rate of drug metabolism to what is observed in CYP2D6 ultrarapid metabolizers, with no such effect observed in CYP2D6 poor metabolizers lacking functional enzyme. The results indicate that NFIB constitutes a novel nuclear factor in the regulation of cytochrome P450 genes, and that its polymorphism is a predictor for the rate of CYP2D6 dependent drug metabolism in vivo.

Genome-wide association analyses of symptom severity among clozapine-treated patients with schizophrenia spectrum disorders

Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10^-3; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10^-4) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10^-3). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10^-7) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia.

The role of alcohol intake in the pharmacogenetics of treatment with clozapine

Clozapine (CLZ) is an atypical antipsychotic reserved for patients with refractory psychosis, but it is associated with a significant risk of severe adverse reactions (ADRs) that are potentiated with the concomitant use of alcohol. Additionally, pharmacogenetic studies have explored the influence of several genetic variants in CYP450, receptors and transporters involved in the interindividual response to CLZ. Herein, we systematically review the current multiomics knowledge behind the interaction between CLZ and alcohol intake, and how its concomitant use might modulate the pharmacogenetics. CYP1A2*1F, *1C and other alleles not yet discovered could support a precision medicine approach for better therapeutic effects and fewer CLZ ADRs. CLZ monitoring systems should be amended and include alcohol intake to protect patients from severe CLZ ADRs.

Effects of a novel UGT2B haplotype and UGT1A4*3 allele variants on glucuronidation of clozapine in vivo

BACKGROUND

Glucuronidation is an important metabolic pathway of clozapine (CLZ), but the impact of various uridine 5'diphospho-glucuronosyltransferases (UGT) polymorphisms on the exposure and metabolism of CLZ in vivo is unclear.

OBJECTIVE

The objective of this study was to investigate the impact of UGT2B haplotype and UGT1A4*3 allele variants on the formation of CLZ glucuronide metabolites (5N- and N+-glucuronide) and CLZ exposure in patients' serum after adjusting for sex, age and smoking habits.

METHODS

The study was based on serum samples from CLZ-treated patients (n=79) subjected to routine therapeutic drug monitoring (TDM) at Diakonhjemmet Hospital, Oslo, Norway. From the same patients the following UGT variants were genotyped using Real-Time PCR: UGT2B:GA haplotype (defined as UGT2B:GA; rs1513559A>G and rs416593T>A) and UGT1A4*3 (rs2011425T>G). Serum concentrations of CLZ 5N- and N+-glucuronide were measured by UPLC high-resolution mass spectrometry.

RESULTS

None of the genotypes had significant impact on CLZ exposure (p>0.05). However, compared to UGT2B:AT/AT and UGT1A4*1/*1, the 5N-glucuronide exposure was reduced in UGT2B:GA/GA carriers (-75%, p=0.03) while the exposure was non-significantly increased in UGT1A4*3 carriers (+100%, p=0.14), respectively. The N+-glucuronide exposure was unchanged in UGT1A4*3 vs noncarriers (p=0.28), but significantly reduced in heterozygous (-50%, p=0.016) and homozygous carriers (-70%, p=0.021) of UGT2B:GA compared to UGT2B:AT/AT carriers, respectively.

CONCLUSION

The UGT2B:GA and UGT1A4*3 variants had no impact on CLZ exposure, but were associated with differences and preferences in CLZ glucuronidation. The latter might be of potential relevance for CLZ tolerability, since levels of the N+-glucuronide metabolite may reflect the generation and trapping of reactive metabolites involved in CLZ-induced toxicity.

Effect of Valproic Acid on the Metabolic Spectrum of Clozapine in Patients With Schizophrenia

BACKGROUND

Valproic acid (VPA) is frequently used with clozapine (CLZ) as mood stabilizer and/or seizure prophylaxis. Valproic acid is known to reduce N-desmethylclozapine (N-DMC) but not CLZ levels. This leads to the hypothesis that VPA induces the CLZ metabolism via non-N-desmethylation pathways. Therefore, we aimed to investigate the effect of concurrent VPA use on the serum concentrations of a spectrum of CLZ metabolites in patients, adjusting for smoking.

METHODS

In total, 288 patients with an overall number of 737 serum concentration measurements of CLZ and metabolites concurrently using VPA (cases, n = 22) or no interacting drugs (controls, n = 266) were included from a routine therapeutic drug monitoring service. Linear mixed model analyses were performed to compare the dose-adjusted concentrations (C/D) of CLZ, N-DMC, CLZ 5N/N+-glucuronides, and metabolite-to-parent ratios in cases versus controls.

RESULTS

After adjusting for covariates, the N-DMC (-40%, P < 0.001) and N+-glucuronide C/Ds (-78%, P < 0.001) were reduced in cases versus controls, while the CLZ C/D was unchanged (P > 0.7). In contrast, the 5N-glucuronide C/D (+250%, P < 0.001) and 5N-glucuronide-to-CLZ ratios (+120%, P = 0.01) were increased in cases versus controls.

CONCLUSIONS

Our findings show that complex changes in CLZ metabolism underly the pharmacokinetic interaction with VPA. The lower levels of N-DMC seem to be caused by VPA-mediated induction of CLZ 5N-glucuronide formation, subsequently leading to reduced substrate availability for N-desmethylation. Whether the changes in CLZ metabolism caused by VPA affects the clinical outcome warrants further investigation.

Pharmacogenomics: A road ahead for precision medicine in psychiatry

Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic ("what the body does to a drug") and pharmacodynamic ("what the drug does to the body") effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.

Therapeutic Drug Monitoring of Second- and Third-Generation Antipsychotic Drugs-Influence of Smoking Behavior and Inflammation on Pharmacokinetics

Both inflammation and smoking can influence a drug’s pharmacokinetic properties, i.e., its liberation, absorption, distribution, metabolism, and elimination. Depending on, e.g., pharmacogenetics, these changes may alter treatment response or cause serious adverse drug reactions and are thus of clinical relevance. Antipsychotic drugs, used in the treatment of psychosis and schizophrenia, should be closely monitored due to multiple factors (e.g., the narrow therapeutic window of certain psychotropic drugs, the chronicity of most mental illnesses, and the common occurrence of polypharmacotherapy in psychiatry). Therapeutic drug monitoring (TDM) aids with drug titration by enabling the quantification of patients’ drug levels. Recommendations on the use of TDM during treatment with psychotropic drugs are presented in the Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology; however, data on antipsychotic drug levels during inflammation or after changes in smoking behavior—both clinically relevant in psychiatry—that can aid clinical decision making are sparse. The following narrative review provides an overview of relevant literature regarding TDM in psychiatry, particularly in the context of second- and third-generation antipsychotic drugs, inflammation, and smoking behavior. It aims to spread awareness regarding TDM (most pronouncedly of clozapine and olanzapine) as a tool to optimize drug safety and provide patient-tailored treatment.

Therapeutic Drug Monitoring of Second- and Third-Generation Antipsychotic Drugs—Influence of Smoking Behavior and Inflammation on Pharmacokinetics

Both inflammation and smoking can influence a drug’s pharmacokinetic properties, i.e., its liberation, absorption, distribution, metabolism, and elimination. Depending on, e.g., pharmacogenetics, these changes may alter treatment response or cause serious adverse drug reactions and are thus of clinical relevance. Antipsychotic drugs, used in the treatment of psychosis and schizophrenia, should be closely monitored due to multiple factors (e.g., the narrow therapeutic window of certain psychotropic drugs, the chronicity of most mental illnesses, and the common occurrence of polypharmacotherapy in psychiatry). Therapeutic drug monitoring (TDM) aids with drug titration by enabling the quantification of patients’ drug levels. Recommendations on the use of TDM during treatment with psychotropic drugs are presented in the Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology; however, data on antipsychotic drug levels during inflammation or after changes in smoking behavior—both clinically relevant in psychiatry—that can aid clinical decision making are sparse. The following narrative review provides an overview of relevant literature regarding TDM in psychiatry, particularly in the context of second- and third-generation antipsychotic drugs, inflammation, and smoking behavior. It aims to spread awareness regarding TDM (most pronouncedly of clozapine and olanzapine) as a tool to optimize drug safety and provide patient-tailored treatment.

Therapeutic Drug Monitoring of Second- and Third-Generation Antipsychotic Drugs-Influence of Smoking Behavior and Inflammation on Pharmacokinetics

Both inflammation and smoking can influence a drug's pharmacokinetic properties, i.e., its liberation, absorption, distribution, metabolism, and elimination. Depending on, e.g., pharmacogenetics, these changes may alter treatment response or cause serious adverse drug reactions and are thus of clinical relevance. Antipsychotic drugs, used in the treatment of psychosis and schizophrenia, should be closely monitored due to multiple factors (e.g., the narrow therapeutic window of certain psychotropic drugs, the chronicity of most mental illnesses, and the common occurrence of polypharmacotherapy in psychiatry). Therapeutic drug monitoring (TDM) aids with drug titration by enabling the quantification of patients' drug levels. Recommendations on the use of TDM during treatment with psychotropic drugs are presented in the Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology; however, data on antipsychotic drug levels during inflammation or after changes in smoking behavior-both clinically relevant in psychiatry-that can aid clinical decision making are sparse. The following narrative review provides an overview of relevant literature regarding TDM in psychiatry, particularly in the context of second- and third-generation antipsychotic drugs, inflammation, and smoking behavior. It aims to spread awareness regarding TDM (most pronouncedly of clozapine and olanzapine) as a tool to optimize drug safety and provide patient-tailored treatment.

Clozapine Metabolism is Associated With Absolute Neutrophil Count in Individuals With Treatment-Resistant Schizophrenia

Up to one-third of those with schizophrenia fail to respond to standard antipsychotics and are considered to have treatment-resistant schizophrenia, a condition for which clozapine is the only evidence-based medication. While up to 60% of treated individuals obtain therapeutic benefits from clozapine, it is currently underprescribed worldwide, partly because of concerns related to its broad adverse effect profile. In particular, the potential effects of clozapine on the immune system have gained relevance after a recent study showed that drug plasma concentrations were inversely correlated with neutrophil counts in individuals routinely undergoing treatment. Seeking to investigate this relationship in more detail, we extracted metabolic, immune, and genetic data from a UK cohort of long-term clozapine users linked to a clozapine monitoring service, CLOZUK2 (N = 208). Whilst a correlation analysis was compatible with the original results, a multiple linear regression accounting for dose and other confounding factors additionally allowed us to estimate the decrease in absolute neutrophil counts to approximately 141 cells/mm3 for every 0.1 mg/L increase in clozapine concentration. However, this association was attenuated after controlling for the metabolic ratio between clozapine and its main metabolite, norclozapine, which was itself negatively associated with neutrophil concentrations. Further analyses revealed that these relationships are likely moderated by genetic factors, as three pharmacogenomic SNPs previously associated to norclozapine plasma concentrations and the metabolic ratio (rs61750900, rs2011425 and rs1126545) were shown to be independently associated with a variation in neutrophil counts of about 400 cells/mm3 per effect allele. Such results are compatible with an effect of norclozapine, but not necessarily clozapine, on immune cell counts, and highlight the need for further investigations into the potential role of genetic determinants of clozapine pharmacokinetics in the occurrence of adverse effects during treatment.

Self-Report for Measuring and Predicting Medication Adherence: Experts' Experience in Predicting Adherence in Stable Psychiatric Outpatients and in Pharmacokinetics

THE PROBLEM

Poor adherence to appropriately prescribed medication is a global challenge for psychiatrists.

PRIOR STUDIES

Measuring adherence is complicated. In our recent three-country naturalistic study including more than 1000 patients and their adherence to multiple medication prescriptions at the same time, patients' self-report of adherence to each specific drug was the only practical option for measuring adherence. Systematic literature reviews provide inconsistent results for sociodemographic, clinical and medication variables as predictors of adherence to psychiatric drugs. Our studies over the last 10 years in relatively stable psychiatric outpatients have shown that some self-reported health beliefs had consistent, strong effects and a better predictive role. Three dimensions of these health beliefs are characteristics of the individual: 1) attitudes toward psychiatric medication such as pharmacophobia (fear of taking drugs or medicines), 2) health locus of control (the belief patients have about who or what agent determines the state of their health), 3) psychological reactance (an emotional reaction in direct contradiction to rules or regulations that threaten or suppress certain freedoms in behavior). They can be measured by the Patient Health Beliefs Questionnaire on Psychiatric Treatment. The attitude toward each specific medication can be measured by the necessity-concern framework and summarized as the presence or absence of skepticism about that drug. After 25 years conducting pharmacokinetic studies in psychiatric drugs, particularly antipsychotics, we have limited understanding of how to use blood levels to predict the effects of non-adherence or to establish it.

EXPERT OPINION ON FUTURE STUDIES

Future studies to predict adherence should include the inpatient setting and explore insight. Studying the pharmacokinetics associated with non-adherence in each psychiatric drug is a major challenge. Medication adherence is a complex and dynamic process changing over time in the same patient. Personalizing adherence using psychological or pharmacological variables are in their initial stages.