Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment.

BACKGROUND: Treatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population (n = 1286) was recruited from a routine therapeutic drug monitoring (TDM) service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone (without TDM history of clozapine) defined the TRS (n = 478) and non-TRS (n = 808) group, respectively. RESULTS: We identified a suggestive association between TRS and a common variant within the LINC00523 gene with a significance just below the genome-wide threshold (rs79229764 C > T, OR = 4.89; p = 1.8 × 10-7). Polygenic risk score for schizophrenia was significantly associated with TRS (OR = 1.4, p = 2.1 × 10-6). In a large post-mortem brain sample from schizophrenia donors (n = 214; CommonMind Consortium), gene expression analysis indicated that the rs79229764 variant allele might be involved in the regulation of GPR88 and PUDP, which plays a role in striatal neurotransmission and intellectual disability, respectively. CONCLUSIONS: We report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction.

Pharmacogenetic Variants and Plasma Concentrations of Antiseizure Drugs: A Systematic Review and Meta-Analysis.

Importance: Precise estimation of a patient's drug metabolism capacity is important for antiseizure dose personalization. Objective: To quantify the differences in plasma concentrations for antiseizure drugs associated with variants of genes encoding drug metabolizing enzymes. Data Sources: PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to September 30, 2023, without language restrictions. Study Selection: Two reviewers performed independent study screening and assessed the following inclusion criteria: appropriate genotyping was performed, genotype-based categorization into subgroups was possible, and each subgroup contained at least 3 participants. Data Extraction and Synthesis: The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for data extraction and subsequent quality, validity, and risk-of-bias assessments. The results from the included studies were pooled with random-effect meta-analysis. Main Outcomes and Measures: Plasma concentrations of antiseizure drugs were quantified with the dose-normalized area under the concentration-time curve, the dose-normalized steady state concentration, or the concentrations after a single dose at standardized dose and sampling time. The ratio of the means was calculated by dividing the mean drug plasma concentrations of carriers and noncarriers of the pharmacogenetic variant. Results: Data from 98 studies involving 12 543 adult participants treated with phenytoin, valproate, lamotrigine, or carbamazepine were analyzed. Studies were mainly conducted within East Asian (69 studies) or White or European (15 studies) cohorts. Significant increases of plasma concentrations compared with the reference subgroup were observed for phenytoin, by 46% (95% CI, 33%-61%) in CYP2C9 intermediate metabolizers, 20% (95% CI, 17%-30%) in CYP2C19 intermediate metabolizers, and 39% (95% CI, 24%-56%) in CYP2C19 poor metabolizers; for valproate, by 12% (95% CI, 4%-20%) in CYP2C9 intermediate metabolizers, 12% (95% CI, 2%-24%) in CYP2C19 intermediate metabolizers, and 20% (95% CI, 2%-41%) in CYP2C19 poor metabolizers; and for carbamazepine, by 12% (95% CI, 3%-22%) in CYP3A5 poor metabolizers. Conclusions and Relevance: This systematic review and meta-analysis found that CYP2C9 and CYP2C19 genotypes encoding low enzymatic capacity were associated with a clinically relevant increase in phenytoin plasma concentrations, several pharmacogenetic variants were associated with statistically significant but only marginally clinically relevant changes in valproate and carbamazepine plasma concentrations, and numerous pharmacogenetic variants were not associated with statistically significant differences in plasma concentrations of antiseizure drugs.

Impact of CYP2D6*2, CYP2D6*35, rs5758550, and related haplotypes on risperidone clearance in vivo.

PURPOSE: The CYP2D6 gene exhibits significant polymorphism, contributing to variability in responses to drugs metabolized by CYP2D6. While CYP2D6*2 and CYP2D6*35 are presently designated as alleles encoding normal metabolism, this classification is based on moderate level evidence. Additionally, the role of the formerly called "enhancer" single nucleotide polymorphism (SNP) rs5758550 is unclear. In this study, the impacts of CYP2D6*2, CYP2D6*35 and rs5758550 on CYP2D6 activity were investigated using risperidone clearance as CYP2D6 activity marker. METHODS: A joint parent-metabolite population pharmacokinetic model was used to describe 1,565 serum concentration measurements of risperidone and 9-hydroxyrisperidone in 512 subjects. Risperidone population clearance was modeled as the sum of a CYP2D6-independent clearance term and the partial clearances contributed from each individually expressed CYP2D6 allele or haplotype. In addition to the well-characterized CYP2D6 alleles (*3-*6, *9, *10 and *41), *2, *35 and two haplotypes assigned as CYP2D6*2-rs5758550G and CYP2D6*2-rs5758550A were evaluated. RESULTS: Each evaluated CYP2D6 allele was associated with significantly lower risperidone clearance than the reference normal function allele CYP2D6*1 (p < 0.001). Further, rs5758550 differentiated the effect of CYP2D6*2 (p = 0.005). The haplotype-specific clearances for CYP2D6*2-rs5758550A, CYP2D6*2-rs5758550G and CYP2D6*35 were estimated to 30%, 66% and 57%, respectively, relative to the clearance for CYP2D6*1. Notably, rs5758550 is in high linkage disequilibrium (R2 > 0.85) with at least 24 other SNPs and cannot be assigned as a functional SNP. CONCLUSION: CYP2D6*2 and CYP2D6*35 encode reduced risperidone clearance, and the extent of reduction for CYP2D6*2 is differentiated by rs5758550. Genotyping of these haplotypes might improve the precision of genotype-guided prediction of CYP2D6-mediated clearance.

Combined effect of CYP2C19 and CYP2D6 genotypes on escitalopram serum concentration and its metabolic ratio in a European patient population.

AIMS: The aim of the present study was to investigate the impact of CYP2D6 genotype on exposure and metabolism of escitalopram in patients stratified by CYP2C19 genotype in a large real-world population. METHODS: Patients were included from a therapeutic drug monitoring service if they had measured serum concentration of escitalopram and the metabolite, N-desmethyl escitalopram, and performed CYP2C19 and CYP2D6 genotyping. Patients were divided into 16 combined genotype-predicted phenotype subgroups (poor [PM], intermediate [IM], normal [NM] and ultrarapid metabolizers [UM]) of CYP2C19/CYP2D6. The concentration-to-dose (CD) ratio and metabolite-to-parent ratio (metabolic ratio) of escitalopram were compared across subgroups using the Kruskal-Wallis test followed by Dunn's test with CYP2D6 NMs as the reference group. RESULTS: A total of 5067 patients were included in the study. A stepwise increase in escitalopram CD ratio by decreasing CYP2D6 activity was observed in all CYP2C19 subgroups, except for in CYP2C19 UMs. The percentage differences in escitalopram CD ratio between CYP2D6 PMs and NMs were 24% in CYP2C19 NMs (P < .001), 28% in CYP2C19 IMs (P < .001) and 31% in CYP2C19 PMs (P = .04). As for the CD ratio, CYP2D6 genotype effect on metabolic ratio increased stepwise by decreasing CYP2C19 metabolism. CONCLUSIONS: CYP2D6 genotype is of significant importance for the individual variation in escitalopram pharmacokinetics. The most relevant increase in escitalopram concentration is seen in individuals with decreased and/or absent CYP2C19 activity. By combining CYP2C19 and CYP2D6 genotypes, the optimal dose for patients may be predicted with greater precision than for CYP2C19 genotype alone.

Development and external validation of a prognostic model for time to readmission or death in multimorbid patients.

OBJECTIVE: To develop and externally validate a prognostic model built on important factors predisposing multimorbid patients to all-cause readmission and/or death. In addition to identify patients who may benefit most from a comprehensive clinical pharmacist intervention. METHODS: A multivariable prognostic model was developed based on data from a randomised controlled trial investigating the effect of pharmacist-led medicines management on readmission rate in multimorbid, hospitalised patients. The derivation set comprised 386 patients randomised in a 1:1 manner to the intervention group, i.e. with a pharmacist included in their multidisciplinary treatment team, or the control group receiving standard care at the ward. External validation of the model was performed using data from an independent cohort, in which 100 patients were randomised to the same intervention, or standard care. The setting was an internal medicines ward at a university hospital in Norway. RESULTS: The number of patients who were readmitted or had died within 18 months after discharge was 297 (76.9 %) in the derivation set, i.e. the randomized controlled trial, and 69 (71.1 %) in the validation set, i.e. the independent cohort. Charlson comorbidity index (CCI; low, moderate or high), previous hospital admissions within the previous six months and heart failure were the strongest prognostic factors and were included in the final model. The efficacy of the pharmaceutical intervention did not prove significant in the model. A prognostic index (PI) was constructed to estimate the hazard of readmission or death (low, intermediate or high-risk groups). Overall, the external validation replicated the result. We were unable to identify a subgroup of the multimorbid patients with better efficacy of the intervention. CONCLUSIONS: A prognostic model including CCI, previous admissions and heart failure can be used to obtain valid estimates of risk of readmission and death in patients with multimorbidity.

Does in vitro hemolysis affect measurements of plasma apixaban concentration by UPLC-MS and anti-Xa assay?

INTRODUCTION: Hemolytic interference may impact various laboratory tests, including coagulation analyses. Apixaban is the most commonly used direct oral anticoagulant in Norway, and there is lacking knowledge on how apixaban concentration measurements might be influenced by hemolysis. Moreover, hemolysis-induced alterations in apixaban levels could potentially impact the risk of bleeding in specific clinical scenarios. We wanted to study whether hemolysis would increase apixaban concentration and investigate the impact of hemolytic interference on apixaban concentration measurements. METHODS: Blood samples from 20 apixaban-treated patients and 8 healthy controls were hemolyzed in vitro by a freeze method. The degree of hemolysis was measured with plasma free hemoglobin (PfHb) at baseline and two levels of hemolysis. Apixaban concentration was measured in plasma using both the chromogenic anti-Xa method and the ultraperformance liquid chromatography mass spectrometry (UPLC-MS). Thrombin generation assay was performed to assess coagulability. RESULTS: UPLC-MS measurements showed a mean concentration change of -1.66% (±3.2%, p = 0.005) and anti-Xa assay showed a mean concentration change of 3.37% (±6.5%, p = 0.09) with increasing hemolysis. Thrombin generation lagtime decreased, and endogenous thrombin potential and peak thrombin increased with increasing hemolysis in both the control group and the apixaban group. CONCLUSION: Apixaban concentration measurements by anti-Xa assay and UPLC-MS were not affected by hemolysis to a clinically relevant extent. Furthermore, hemolysis did not lead to hypocoagulability when assessed by thrombin generation.

Rapid Metabolism Underlying Subtherapeutic Serum Levels of Atypical Antipsychotics Preceding Clozapine Treatment: A Retrospective Analysis of Real-World Data.

INTRODUCTION: Adequate antipsychotic treatment intensity is required before diagnosing resistant schizophrenia and initiating clozapine treatment. We aimed to investigate potential rapid drug metabolism underlying low dose-adjusted serum concentration (CD) of non-clozapine atypical antipsychotics preceding clozapine treatment. METHODS: Patients using non-clozapine, atypical antipsychotics (aripiprazole, risperidone, olanzapine, or quetiapine) within 1 year before starting clozapine were included in this study from a therapeutic drug monitoring service in Oslo, Norway, between 2005 and 2023. Patients were assigned into low CD (LCD) and normal CD (NCD) subgroups. Using a reference sample with 147,964 antipsychotic measurements, LCD was defined as CDs below the 25th percentile, while patients with NCD exhibited CDs between the 25th and 75th percentile of the respective reference measurements. Metabolic ratios, doses, and frequency of subtherapeutic levels of non-clozapine antipsychotics were compared between LCD and NCD groups. RESULTS: Preceding clozapine treatment, 110 out of 272 included patients (40.4%) were identified with LCD. Compared with the NCD group, LCD patients exhibited higher metabolic ratios of olanzapine (1.5-fold; p < 0.001), quetiapine (3.0-fold; p < 0.001), and risperidone (6.0-fold; p < 0.001). Metabolic ratio differences were independent of smoking and CYP2D6 genotype for olanzapine (p = 0.008) and risperidone (p = 0.016), respectively. Despite higher doses of olanzapine (1.25-fold; p = 0.054) and quetiapine (1.6-fold; p = 0.001) in LCD versus NCD patients, faster metabolism among the former was accompanied by higher frequencies of subtherapeutic levels of olanzapine (3.3-fold; p = 0.044) and quetiapine (1.8-fold; p = 0.005). CONCLUSION: LCD and associated rapid metabolism of non-clozapine antipsychotics is frequent before starting clozapine treatment. For olanzapine and quetiapine, this is associated with significantly increased risk of having subtherapeutic concentrations.

Placental efflux transporters and antiseizure or antidepressant medication use impact birth weight in MoBa cohort.

Low birth weight raises neonatal risks and lifelong health issues and is linked to maternal medication use during pregnancy. We examined data from the Norwegian Mother, Father, and Child Cohort Study and the Medical Birth Registry of Norway, including 69,828 offspring with genotype data and 81,189 with maternal genotype data. We identified genetic risk variants in placental efflux transporters, calculated genetic scores based on alleles related to transporter activity, and assessed their interaction with prenatal use of antiseizure or antidepressant medication on offspring birth weight. Our study uncovered possible genetic variants in both offspring (rs3740066) and mothers (rs10248420; rs2235015) in placental efflux transporters (MRP2-ABCC2 and MDR1-ABCB1) that modulated the association between prenatal exposure to antiseizure medication and low birth weight in the offspring. Antidepressant exposure was associated with low birth weight, but there were no gene-drug interactions. The interplay between MRP2-ABCC2 and MDR1-ABCB1 variants and antiseizure medication may impact neonatal birth weight.

Therapeutic drug monitoring, liquid biopsies or pharmacogenomics for prediction of human drug metabolism and response.

Pharmacokinetics plays a central role in understanding the significant interindividual differences that exist in drug metabolism and response. Effectively addressing these differences requires a multi-faceted approach that encompasses a variety of tools and methods. In this review, we examine three key strategies to achieve this goal, namely pharmacogenomics, therapeutic drug monitoring (TDM) and liquid biopsy-based monitoring of hepatic ADME gene expression and highlight their advantages and limitations. We note that larger cohort studies are needed to validate the utility of liquid biopsy-based assessment of hepatic ADME gene expression, which includes prediction of drug metabolism in the clinical setting. Modern mass spectrometers have improved traditional TDM methods, offering versatility and sensitivity. In addition, the identification of endogenous or dietary markers for CYP metabolic traits offers simpler and more cost-effective alternatives to determine the phenotype. We believe that future pharmacogenomic applications in clinical practice should prioritize the identification of missing heritable factors, using larger, well-characterized patient studies and controlling for confounding factors such as diet, concomitant medication and physical health. The intricate regulation of ADME gene expression implies that large-scale studies combining long-read next-generation sequencing (NGS) of complete genomes with phenotyping of patients taking different medications are essential to identify these missing heritabilities. The continuous integration of such data into AI-driven analytical systems could provide a comprehensive and useful framework. This could lead to the development of highly effective algorithms to improve genetics-based precision treatment by predicting drug metabolism and response, significantly improving clinical outcomes.

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.

Dose-dependent effect of lamotrigine on quetiapine serum concentration in patients using instant release tablets.

PURPOSE: Lamotrigine was previously reported to reduce serum concentration of quetiapine. The aim of this study was to investigate whether lamotrigine dose or quetiapine formulation was of importance for the drug interaction. METHODS: Patients combining lamotrigine with quetiapine (cases) were included retrospectively from a routine therapeutic drug monitoring (TDM) service, as were a control group of patients using quetiapine without any interacting drugs. The case and control groups were divided into groups using immediate release (IR) and extended release (XR) quetiapine. The case group was further split into high-dose (> 200 mg/day) and low-dose (≤ 200 mg/day) lamotrigine users. Quetiapine concentration-to-dose (C/D) ratio and metabolite-to-parent ratio (MPR) were compared between the control group and dose-separated case groups using ANOVA test and t-tests. RESULTS: In total, 406 patients were included. The mean C/D ratio of IR quetiapine was 46% lower in the high-dose lamotrigine group compared with the control group (P < 0.001), while no interaction effect was present in the low dose lamotrigine group (P = 0.7). Regardless of lamotrigine dose, there was no difference in quetiapine C/D ratio for patients using the XR formulation (P = 0.4). The quetiapine MPR was unaffected regardless of formulation and lamotrigine dose (P ≥ 0.06). CONCLUSION: The effect of lamotrigine in reducing quetiapine concentration is only significant for patients using quetiapine IR tablets who are treated with lamotrigine doses > 200 mg/day. Because of high variability in the interaction effect, TDM of quetiapine should be recommended during co-prescription of high-dose lamotrigine.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

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.

Novel Identification of Cysteinyl Derivatives of Toxic Clozapine Nitrenium Ions and the Effect of Valproic Acid on Metabolite Formation: A Study Using Reprocessed High-Resolution Mass Spectra of Analyzed Therapeutic Drug Monitoring Samples.

BACKGROUND: Clozapine (CLZ) use is hampered by the risk of granulocyte toxicity, which is associated with the formation of nitrenium ions and the concurrent use of valproic acid (VPA). These highly reactive nitrenium ions cannot be measured in vivo. Instead, deactivated cysteinyl conjugates may potentially be detected. The aim of this study was to develop a novel method for identifying cysteinylated derivates of CLZ nitrenium ions to investigate the effect of VPA on their formation using therapeutic drug monitoring data. METHODS: A population comprising 93 VPA comedicated and 162 control patients from a therapeutic drug monitoring (TDM) service in Oslo, Norway, was included. Reprocessing of ultraperformance liquid chromatography high-resolution mass spectra (UHPLC-HR-MS) of previously analyzed TDM samples, combined with the assessment of MS/MS fragmentation patterns, was performed to identify the CLZ cysteinyl conjugates. Smoking, which induces CLZ metabolism, was assessed by detecting cotinine in the reprocessed mass spectra. RESULTS: By reprocessing the UHPLC-HR-MS files of the TDM analyses and reviewing the MS/MS fragment profiles, four cysteinyl conjugates of CLZ were identified. The formations of CLZ cysteinyl (CLZ-Cys 1+ ) and CLZ- N -oxide cysteinyl (CLZ-NOX-Cys 1+ ) were 1.5-fold ( P = 0.038) and 2.1-fold ( P < 0.001) higher in VPA-treated patients than those in the controls. In agreement with previous studies, a 45% reduction in N -desmethylclozapine formation was observed in VPA-treated patients ( P < 0.001). CONCLUSIONS: A novel method for detecting cysteinyl conjugates of CLZ was developed. Application of this method indicated that VPA significantly increased the formation of CLZ-Cys 1+ metabolites, which might explain the granulocyte toxicity reported after adding VPA to CLZ treatment. The developed method opens new avenues for investigating CLZ toxicity, e.g. by correlating cysteinyl conjugates and granulocyte counts in patients.

Age of onset for increased dose-adjusted serum concentrations of antidepressants and association with sex and genotype: An observational study of 34,777 individuals.

PURPOSE: The aim of this study was to examine the age of onset for increased dose-adjusted serum concentrations (C/D ratio) of common antidepressant drugs and to explore the potential association with sex and CYP2C19/CYP2D6 genotype. METHODS: Serum concentrations and prescribed daily doses for citalopram, escitalopram, sertraline, venlafaxine and mirtazapine, and CYP genotypes, were obtained from a therapeutic drug monitoring (TDM) service. Segmented linear regression analysis was used to examine the relationship between age and antidepressant log C/D ratio in (i) all individuals, (ii) men and women, and (iii) CYP2D6/CYP2C19 normal metabolizers (NMs) and CYP2D6/CYP2C19 intermediate or poor metabolizers (IMs/PMs). RESULTS: A total of 34,777 individuals were included in the study; CYP genotype was available for 21.3%. An increase in C/D ratio started at 44‒55 years of age. Thereafter, the increase progressed more rapidly for citalopram and escitalopram than for venlafaxine and mirtazapine. A doubled C/D ratio was estimated to occur at 79 (citalopram), 81 (escitalopram), 86 (venlafaxine), and 90 years (mirtazapine). For sertraline, only modest changes in C/D ratio were observed. For escitalopram and venlafaxine, the observed increase in C/D ratio started earlier in women than in men. The results regarding CYP genotype were inconclusive. CONCLUSION: The age-related increase in C/D ratio starts in middle-aged adults and progresses up to more than twofold higher C/D ratio in the oldest old. Sertraline seems to be less prone to age-related changes in C/D ratio than the other antidepressants.

Effect of CYP2D6 genotype on duloxetine serum concentration.

Duloxetine is metabolized by cytochrome P450 (CYP)1A2 and CYP2D6. The aim of this study was to investigate the effect of the CYP2D6 genotype on duloxetine serum concentration adjusting for age and sex. Patients were included retrospectively from a therapeutic drug monitoring service. Multiple linear regression analysis was used to investigate the effect of CYP2D6 genotype, age and sex on the duloxetine concentration-to-dose (C/D) ratio. In total, 269 patients were included and assigned to the following genotype-predicted phenotype subgroups: CYP2D6 poor metabolizers (PMs, n = 23), intermediate metabolizers (IMs, n = 121), normal metabolizers (NMs, n = 120) and ultrarapid metabolizers (UMs, n = 5). Multiple linear regression analysis revealed a 95% higher duloxetine C/D ratio in PMs compared with NMs (p = 0.009). Patients ≥65 years had a 56% higher C/D ratio than younger patients (p = 0.01), while women had a 46% higher C/D ratio than men (p = 0.04). In conclusion, the CYP2D6 PM phenotype is associated with a twofold higher concentration at recommended dosing compared with the NM phenotype. CYP2D6 PM females above 65 years are at particular risk of high duloxetine levels as they may obtain a threefold higher C/D ratio compared with younger, male NMs.

Evidence for solanidine as a dietary CYP2D6 biomarker: Significant correlation with risperidone metabolism.

AIMS: The extensive variability in cytochrome P450 2D6 (CYP2D6) metabolism is mainly caused by genetic polymorphisms. However, there is large, unexplained variability in CYP2D6 metabolism within CYP2D6 genotype subgroups. Solanidine, a dietary compound found in potatoes, is a promising phenotype biomarker predicting individual CYP2D6 metabolism. The aim of this study was to investigate the correlation between solanidine metabolism and the CYP2D6-mediated metabolism of risperidone in patients with known CYP2D6 genotypes. METHODS: The study included therapeutic drug monitoring (TDM) data from CYP2D6-genotyped patients treated with risperidone. Risperidone and 9-hydroxyrisperidone levels were determined during TDM, and reprocessing of the respective TDM full-scan high-resolution mass spectrometry files was applied for semi-quantitative measurements of solanidine and five metabolites (M402, M414, M416, M440 and M444). Spearman's tests determined the correlations between solanidine metabolic ratios (MRs) and the 9-hydroxyrisperidone-to-risperidone ratio. RESULTS: A total of 229 patients were included. Highly significant, positive correlationswere observed between all solanidine MRs and the 9-hydroxyrisperidone-to-risperidone ratio (ρ > 0.6, P < .0001). The strongest correlation was observed for the M444-to-solanidine MR in patients with functional CYP2D6 metabolism, i.e., genotype activity scores of 1 and 1.5 (ρ 0.72-0.77, P < .0001). CONCLUSION: The present study shows strong, positive correlations between solanidine metabolism and CYP2D6-mediated risperidone metabolism. The strong correlation within patients carrying CYP2D6 genotypes encoding functional CYP2D6 metabolism suggests that solanidine metabolism may predict individual CYP2D6 metabolism, and hence potentially improve personalized dosing of drugs metabolized by CYP2D6.

Revealing the reporting disparity: VigiBase highlights underreporting of clozapine in other Western European countries compared to the UK.

BACKGROUND: Pharmacovigilance studies indicate clozapine history is marked by adverse drug reactions (ADRs). OBJECTIVE: In a 2021 article, the United Kingdom (UK) had >90 % of European clozapine-related fatal outcomes in VigiBase, the World Health Organization's pharmacovigilance database. Two possibly opposing hypotheses could explain this disparity: 1) fewer reported fatal outcomes in other Western European countries mainly reflect underreporting to VigiBase, and 2) the higher number of UK reports reflects higher real relative mortality. METHODS: VigiBase reports from clozapine's introduction to December 31, 2022, were studied for ADRs and the top 10 causes of fatal outcomes. The UK was compared with 11 other top reporting Western countries (Germany, Denmark, France, Finland, Ireland, Italy, Netherlands, Norway, Spain, Sweden and Switzerland). Nine countries (except Ireland and Switzerland) were compared after controlling for population and clozapine prescriptions. RESULTS: The UK accounted for 29 % of worldwide clozapine-related fatal outcomes, Germany 2 % and <1 % in each of the other countries. The nonspecific label "death" was the top cause in the world (46 %) and in the UK (33 %). "Pneumonia" was second in the world (8 %), the UK (12 %), Ireland (8 %) and Finland (14 %). Assuming that our corrections for population and clozapine use are correct, other countries underreported only 1-10 % of the UK clozapine fatal outcome number. CONCLUSIONS: Different Western European countries consistently underreport to VigiBase compared to the UK, but have different reporting/publishing styles for clozapine-related ADRs/fatal outcomes. Three Scandinavian registries suggest lives are saved as clozapine use increases, but this cannot be studied in pharmacovigilance databases.