Identification of four novel loci associated with psychotropic drug-induced weight gain in a Swiss psychiatric longitudinal study: A GWAS analysis.

Patients suffering from mental disorders are at high risk of developing cardiovascular diseases, leading to a reduction in life expectancy. Genetic variants can display greater influence on cardiometabolic features in psychiatric cohorts compared to the general population. The difference is possibly due to an intricate interaction between the mental disorder or the medications used to treat it and metabolic regulations. Previous genome wide association studies (GWAS) on antipsychotic-induced weight gain included a low number of participants and/or were restricted to patients taking one specific antipsychotic. We conducted a GWAS of the evolution of body mass index (BMI) during early (i.e., ≤ 6) months of treatment with psychotropic medications inducing metabolic disturbances (i.e., antipsychotics, mood stabilizers and some antidepressants) in 1135 patients from the PsyMetab cohort. Six highly correlated BMI phenotypes (i.e., BMI change and BMI slope after distinct durations of psychotropic treatment) were considered in the analyses. Our results showed that four novel loci were associated with altered BMI upon treatment at genome-wide significance (p < 5 × 10-8): rs7736552 (near MAN2A1), rs11074029 (in SLCO3A1), rs117496040 (near DEFB1) and rs7647863 (in IQSEC1). Associations between the four loci and alternative BMI-change phenotypes showed consistent effects. Replication analyses in 1622 UK Biobank participants under psychotropic treatment showed a consistent association between rs7736552 and BMI slope (p = 0.017). These findings provide new insights into metabolic side effects induced by psychotropic drugs and underline the need for future studies to replicate these associations in larger cohorts.

A population pharmacokinetic model for sertraline in women during the perinatal period-A contribution from the ConcePTION project.

AIMS: Sertraline is frequently prescribed for mental health conditions in both pregnant and breastfeeding women. According to the limited available data, only small amounts of sertraline are transferred into human milk, yet with a large amount of unexplained interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model to describe the pharmacokinetics of sertraline during the perinatal period and explain interindividual variability. METHODS: Pregnant women treated with sertraline were enrolled in the multicenter prospective cohort SSRI-Breast Milk study. A popPK model for sertraline maternal plasma and breast milk concentrations was developed and allowed estimating the milk-to-plasma ratio (MPR). An additional fetal compartment allowed cord blood concentrations to be described. Several covariates were tested for significance. Ultimately, model-based simulations allowed infant drug exposure through placenta and breast milk under various conditions to be predicted. RESULTS: Thirty-eight women treated with sertraline were included in the study and provided 89 maternal plasma, 29 cord blood and 107 breast milk samples. Sertraline clearance was reduced by 42% in CYP2C19 poor metabolizers compared to other phenotypes. Doubling milk fat content increased the MPR by 95%. Simulations suggested a median daily infant dosage of 6.9 µg kg-1 after a 50 mg maternal daily dose, representing 0.95% of the weight-adjusted maternal dose. Median cord blood concentrations could range from 3.29 to 33.23 ng mL-1 after maternal daily doses between 25 and 150 mg. CONCLUSIONS: Infant exposure to sertraline, influenced by CYP2C19 phenotype and breast milk fat content, remains low, providing reassurance regarding the use of sertraline during pregnancy and breastfeeding.

Therapeutic Drug Monitoring of Olanzapine: Effects of Clinical Factors on Plasma Concentrations in Psychiatric Patients.

BACKGROUND: Therapeutic drug monitoring (TDM) is strongly recommended for olanzapine due to its high pharmacokinetic variability. This study aimed to investigate the impact of various clinical factors on olanzapine plasma concentrations in patients with psychiatric disorders. METHODS: The study used TDM data from the PsyMetab cohort, including 547 daily dose-normalized, steady-state, olanzapine plasma concentrations (C:D ratios) from 248 patients. Both intrinsic factors (eg, sex, age, body weight) and extrinsic factors (eg, smoking status, comedications, hospitalization) were examined. Univariate and multivariable, linear, mixed-effects models were employed, with a stepwise selection procedure based on Akaike information criterion to identify the relevant covariates. RESULTS: In the multivariable model (based on 440 observations with a complete data set), several significant findings emerged. Olanzapine C:D ratios were significantly lower in smokers (ß = -0.65, P < 0.001), valproate users (ß = -0.53, P = 0.002), and inpatients (ß = -0.20, P = 0.025). Furthermore, the C:D ratios decreased significantly as the time since the last dose increased (ß = -0.040, P < 0.001). The male sex had a significant main effect on olanzapine C:D ratios (ß = -2.80, P < 0.001), with significant interactions with age (ß = 0.025, P < 0.001) and body weight (ß = 0.017, P = 0.011). The selected covariates explained 30.3% of the variation in C:D ratios, with smoking status accounting for 7.7% and sex contributing 6.9%. The overall variation explained by both the fixed and random parts of the model was 67.4%. The model facilitated the prediction of olanzapine C:D ratios based on sex, age, and body weight. CONCLUSIONS: The clinical factors examined in this study, including sex, age, body weight, smoking status, and valproate comedication, remarkably influence olanzapine C:D ratios. Considering these factors, in addition to TDM and the clinical situation, could be important for dose adjustment.

Self-reported caffeine consumption miss-matched consumption measured by plasma levels of caffeine and its metabolites: results from two population-based studies.

IMPORTANCE AND OBJECTIVE: Self-reported caffeine consumption has been widely used in research while it may be subject to bias. We sought to investigate the associations between self-reported caffeine consumption and plasma levels of caffeine and its two main metabolites (paraxanthine and theophylline) in the community. METHODS: Data from two population-based studies (SKIPOGH1 and 2 (N = 1246) and CoLaus|PsyCoLaus (N = 4461)) conducted in Switzerland were used. Self-reported caffeine consumption was assessed using questionnaires. Plasma levels of caffeine and its metabolites were quantified by ultra-high performance liquid chromatography coupled to a tandem quadrupole mass spectrometer. RESULTS: In both studies, mean log plasma levels of caffeine and its two metabolites were over 6.48 (plasma levels = 652 ng/ml) when no caffeine consumption was reported. Subsequently, nonlinear associations between log plasma levels and self-reported caffeine consumption were observed in SKIPOGH, with a change of the slope at 3-5 cups of espresso per day in SKIPOGH1 but not SKIPOGH2. In CoLaus|PsyCoLaus, increased daily consumption of caffeinated beverages was associated with increased log plasma levels with a change of the slope at 3 cups. In both studies, declared caffeine consumption higher than 3-5 cups per day was not associated with higher plasma levels of caffeine and its metabolites. CONCLUSION: Self-reports of no or low caffeine consumption and consumption of more than 3-5 cups of coffee should be interpreted with caution, with possible under- or over-estimation. Quantifying plasma levels of caffeine and its metabolites may contribute to a better estimation of caffeine intake.

Insomnia disorders are associated with increased cardiometabolic disturbances and death risks from cardiovascular diseases in psychiatric patients treated with weight-gain-inducing psychotropic drugs: results from a Swiss cohort.

STUDY OBJECTIVES: Insomnia disorders as well as cardiometabolic disorders are highly prevalent in the psychiatric population compared to the general population. We aimed to investigate their association and evolution over time in a Swiss psychiatric cohort. METHODS: Data for 2861 patients (8954 observations) were obtained from two prospective cohorts (PsyMetab and PsyClin) with metabolic parameters monitored routinely during psychotropic treatment. Insomnia disorders were based on the presence of ICD-10 "F51.0" diagnosis (non-organic insomnia), the prescription of sedatives before bedtime or the discharge letter. Metabolic syndrome was defined using the International Diabetes Federation definition, while the 10-year risk of cardiovascular event or death was assessed using the Framingham Risk Score and the Systematic Coronary Risk Estimation, respectively. RESULTS: Insomnia disorders were observed in 30% of the cohort, who were older, predominantly female, used more psychotropic drugs carrying risk of high weight gain (olanzapine, clozapine, valproate) and were more prone to suffer from schizoaffective or bipolar disorders. Multivariate analyses showed that patients with high body mass index (OR = 2.02, 95%CI [1.51-2.72] for each ten-kg/m2 increase), central obesity (OR = 2.20, [1.63-2.96]), hypertension (OR = 1.86, [1.23-2.81]), hyperglycemia (OR = 3.70, [2.16-6.33]), high density lipoprotein hypocholesterolemia in women (OR = 1.51, [1.17-1.95]), metabolic syndrome (OR = 1.84, [1.16-2.92]) and higher 10-year risk of death from cardiovascular diseases (OR = 1.34, [1.17-1.53]) were more likely to have insomnia disorders. Time and insomnia disorders were associated with a deterioration of cardiometabolic parameters. CONCLUSIONS: Insomnia disorders are significantly associated with metabolic worsening and risk of death from cardiovascular diseases in psychiatric patients.

Genetic immune and inflammatory markers associated with diabetes in solid organ transplant recipients.

New-onset diabetes mellitus after transplantation (NODAT) is a complication following solid organ transplantation (SOT) and may be related to immune or inflammatory responses. We investigated whether single nucleotide polymorphisms (SNPs) within 158 immune- or inflammation-related genes contribute to NODAT in SOT recipients. The association between 263 SNPs and NODAT was investigated in a discovery sample of SOT recipients from the Swiss Transplant Cohort Study (STCS, n1  = 696). Positive results were tested in a first STCS replication sample (n2  = 489) and SNPs remaining significant after multiple test corrections were tested in a second SOT replication sample (n3  = 156). Associations with diabetic traits were further tested in several large general population-based samples (n > 480 000). Only SP110 rs2114592C>T remained associated with NODAT in the STCS replication sample. Carriers of rs2114592-TT had 9.9 times (95% confidence interval [CI]: 3.22-30.5, P = .00006) higher risk for NODAT in the combined STCS samples (n = 1184). rs2114592C>T was further associated with NODAT in the second SOT sample (odds ratio: 4.8, 95% CI: 1.55-14.6, P = .006). On the other hand, SP110 rs2114592C>T was not associated with diabetic traits in population-based samples, suggesting a specific gene-environment interaction, possibly due to the use of specific medications (ie, immunosuppressants) in transplant patients and/or to the illness that may unmask the gene effect.

Genetic and clinic predictors of new onset diabetes mellitus after transplantation.

New Onset Diabetes after Transplantation (NODAT) is a frequent complication after solid organ transplantation, with higher incidence during the first year. Several clinical and genetic factors have been described as risk factors of Type 2 Diabetes (T2DM). Additionally, T2DM shares some genetic factors with NODAT. We investigated if three genetic risk scores (w-GRS) and clinical factors were associated with NODAT and how they predicted NODAT development 1 year after transplantation. In both main (n = 725) and replication (n = 156) samples the clinical risk score was significantly associated with NODAT (ORmain: 1.60 [1.36-1.90], p = 3.72*10-8 and ORreplication: 2.14 [1.39-3.41], p = 0.0008, respectively). Two w-GRS were significantly associated with NODAT in the main sample (ORw-GRS 2:1.09 [1.04-1.15], p = 0.001 and ORw-GRS 3:1.14 [1.01-1.29], p = 0.03) and a similar ORw-GRS 2 was found in the replication sample, although it did not reach significance probably due to a power issue. Despite the low OR of w-GRS on NODAT compared to clinical covariates, when integrating w-GRS 2 and w-GRS 3 in the clinical model, the Area under the Receiver Operating Characteristics curve (AUROC), specificity, sensitivity and accuracy were 0.69, 0.71, 0.58 and 0.68, respectively, with significant Likelihood Ratio test discrimination index (p-value 0.0004), performing better in NODAT discrimination than the clinical model alone. Twenty-five patients needed to be genotyped in order to detect one misclassified case that would have developed NODAT 1 year after transplantation if using only clinical covariates. To our knowledge, this is the first study extensively examining genetic risk scores contributing to NODAT development.

Prediction of early weight gain during psychotropic treatment using a combinatorial model with clinical and genetic markers.

BACKGROUND: Psychotropic drugs can induce significant (>5%) weight gain (WG) already after 1 month of treatment, which is a good predictor for major WG at 3 and 12 months. The large interindividual variability of drug-induced WG can be explained in part by genetic and clinical factors. AIM: The aim of this study was to determine whether extensive analysis of genes, in addition to clinical factors, can improve prediction of patients at risk for more than 5% WG at 1 month of treatment. METHODS: Data were obtained from a 1-year naturalistic longitudinal study, with weight monitoring during weight-inducing psychotropic treatment. A total of 248 Caucasian psychiatric patients, with at least baseline and 1-month weight measures, and with compliance ascertained were included. Results were tested for replication in a second cohort including 32 patients. RESULTS: Age and baseline BMI were associated significantly with strong WG. The area under the curve (AUC) of the final model including genetic (18 genes) and clinical variables was significantly greater than that of the model including clinical variables only (AUCfinal: 0.92, AUCclinical: 0.75, P<0.0001). Predicted accuracy increased by 17% with genetic markers (Accuracyfinal: 87%), indicating that six patients must be genotyped to avoid one misclassified patient. The validity of the final model was confirmed in a replication cohort. Patients predicted before treatment as having more than 5% WG after 1 month of treatment had 4.4% more WG over 1 year than patients predicted to have up to 5% WG (P≤0.0001). CONCLUSION: These results may help to implement genetic testing before starting psychotropic drug treatment to identify patients at risk of important WG.

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, specialised tools are used. Three tools have been proven useful to personalise 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 45 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 optimise treatment effects, minimise side effects and ultimately reduce the global burden of diseases, personalised drug treatment has not yet become the standard of care in psychiatry.

Contribution of CYP2B6 alleles in explaining extreme (S)-methadone plasma levels: a CYP2B6 gene resequencing study.

BACKGROUND: (S)-Methadone, metabolized mainly by CYP2B6, shows a wide interindividual variability in its pharmacokinetics and pharmacodynamics. METHODS: Resequencing of the CYP2B6 gene was performed in 12 and 35 selected individuals with high (S)-methadone plasma exposure and low (S)-methadone plasma exposure, respectively, from a previously described cohort of 276 patients undergoing methadone maintenance treatment. Selected genetic polymorphisms were then analyzed in the complete cohort. RESULTS: The rs35303484 (*11; c136A>G; M46V) polymorphism was overrepresented in the high (S)-methadone level group, whereas the rs3745274 (*9; c516G>T; Q172H), rs2279344 (c822+183G>A), and rs8192719 (c1294+53C>T) polymorphisms were underrepresented in the low (S)-methadone level group, suggesting an association with decreased CYP2B6 activity. Conversely, the rs3211371 (*5; c1459C>T; R487C) polymorphism was overrepresented in the low-level group, indicating an increased CYP2B6 activity. A higher allele frequency was found in the high-level group compared with the low-level group for rs3745274 (*9; c516G>T; Q172H), rs2279343 (*4; c785A>G; K262R) (together representing CYP2B6*6), rs8192719 (c1294+53C>T), and rs2279344 (c822+183G>A), suggesting their involvement in decreased CYP2B6 activity. These results should be replicated in larger independent cohorts. CONCLUSION: Known genetic polymorphisms in CYP2B6 contribute toward explaining extreme (S)-methadone plasma levels observed in a cohort of patients following methadone maintenance treatment.

Multicenter study on the clinical effectiveness, pharmacokinetics, and pharmacogenetics of mirtazapine in depression.

Pharmacogenetic tests and therapeutic drug monitoring may considerably improve the pharmacotherapy of depression. The aim of this study was to evaluate the relationship between the efficacy of mirtazapine (MIR) and the steady-state plasma concentrations of its enantiomers and metabolites in moderately to severely depressed patients, taking their pharmacogenetic status into account. Inpatients and outpatients (n = 45; mean age, 51 years; range, 19-79 years) with major depressive episode received MIR for 8 weeks (30 mg/d on days 1-14 and 30-45 mg/d on days 15-56). Mirtazapine treatment resulted in a significant improvement in mean Hamilton Depression Rating Scale total score at the end of the study (P < 0.0001). There was no evidence for a significant plasma concentration-clinical effectiveness relationship regarding any pharmacokinetic parameter. The enantiomers of MIR and its hydroxylated (OH-MIR) and demethylated (DMIR) metabolites in plasma samples on days 14 and 56 were influenced by sex and age. Nonsmokers (n = 28) had higher mean MIR plasma levels than smokers (n = 17): S(+)-enantiomer of MIR, 9.4 (SD, 3.9) versus 6.2 (SD, 5.5) ng/mL (P = 0.005); R(-)-enantiomer of MIR, 24.4 (SD, 6.5) versus 18.5 (SD, 4.1) ng/mL (P = 0.003). Only in nonsmokers, plasma levels of S(+)-enantiomer of MIR and metabolites depended on the CYP2D6 genotype. Therefore, high CYP1A2 activity seen in smokers seems to mask the influence of the CYP2D6 genotype. In patients presenting the CYP2B6 *6/*6 genotype (n = 8), S-OH-MIR concentrations were higher those in the other patients (n = 37). Although it is not known if S-OH-MIR is associated with the therapeutic effect of MIR, the reduction of the Hamilton scores was significantly (P = 0.016) more pronounced in the CYP2B6 *6/*6-genotyped patients at the end of the study. The role of CYP2B6 in the metabolism and effectiveness of MIR should be further investigated.

Case Report: Opioid Use Disorder Associated With Low/Moderate Dose of Loperamide in an Intellectual Disability Patient With CYP3A and P-Glycoprotein Reduced Activity.

Loperamide is an over-the-counter antidiarrheal for which increasing cases of abuse or misuse are described. We report the onset of opioid use disorder associated with low to moderate doses of loperamide in an intellectual disability patient without previous history of substance use disorder (SUD). Our patient presented strongly reduced activities of CYP3A and P-glycoprotein, which are mainly involved in loperamide metabolism and transport. We suggest that this led to an increase in bioavailability, systemic exposure, and brain penetration thus allowing loperamide to act on the central nervous system and contributing to the development of SUD. Slow release oral morphine (SROM) was chosen as opioid agonist treatment, which successfully contained loperamide use and globally improved her clinical condition. This situation highlights the need for caution and awareness when prescribing loperamide, particularly in vulnerable patients with few cognitive resources to understand the risks of self-medication and little insight into its effects.

Olanzapine-associated dose-dependent alterations for weight and metabolic parameters in a prospective cohort.

Metabolic abnormalities have been associated with olanzapine treatment. We assessed if olanzapine has dose-dependent effects on metabolic parameters with changes for weight, blood pressure, lipid and glucose profiles being modelled using linear mixed-effects models. The risk of metabolic abnormalities including early weight gain (EWG) (≥5% during first month) was assessed using mixed-effects logistic regression models. In 392 olanzapine-treated patients (median age 38.0 years, interquartile range [IQR] = 26.0-53.3, median dose 10.0 mg/day, IQR = 5.0-10.0 for a median follow-up duration of 40.0 days, IQR = 20.7-112.2), weight gain was not associated with olanzapine dose (p = 0.61) although it was larger for doses versus ≤10 mg/day (2.54 ± 5.55 vs. 1.61 ± 4.51% respectively, p = 0.01). Treatment duration and co-prescription of >2 antipsychotics, antidepressants, benzodiazepines and/or antihypertensive agents were associated with larger weight gain (p < 0.05). Lower doses were associated with increase in total and HDL cholesterol and systolic and diastolic blood pressure (p < 0.05), whereas higher doses were associated with glucose increases (p = 0.01). Patients receiving >10 mg/day were at higher EWG risk (odds risk: 2.15, 1.57-2.97). EWG might be prominent in high-dose olanzapine-treated patients with treatment duration and co-prescription of other medications being weight gain moderators. The lack of major dose-dependent patterns for weight gain emphasizes that olanzapine-treated patients are at weight gain risk regardless of the dose.

The psychosis metabolic risk calculator (PsyMetRiC) for young people with psychosis: International external validation and site-specific recalibration in two independent European samples.

Background: Cardiometabolic dysfunction is common in young people with psychosis. Recently, the Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed and externally validated in the UK, predicting up-to six-year risk of metabolic syndrome (MetS) from routinely collected data. The full-model includes age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations; the partial-model excludes biochemical predictors. Methods: To move toward a future internationally-useful tool, we externally validated PsyMetRiC in two independent European samples. We used data from the PsyMetab (Lausanne, Switzerland) and PAFIP (Cantabria, Spain) cohorts, including participants aged 16-35y without MetS at baseline who had 1-6y follow-up. Predictive performance was assessed primarily via discrimination (C-statistic), calibration (calibration plots), and decision curve analysis. Site-specific recalibration was considered. Findings: We included 1024 participants (PsyMetab n=558, male=62%, outcome prevalence=19%, mean follow-up=2.48y; PAFIP n=466, male=65%, outcome prevalence=14%, mean follow-up=2.59y). Discrimination was better in the full- compared with partial-model (PsyMetab=full-model C=0.73, 95% C.I., 0.68-0.79, partial-model C=0.68, 95% C.I., 0.62-0.74; PAFIP=full-model C=0.72, 95% C.I., 0.66-0.78; partial-model C=0.66, 95% C.I., 0.60-0.71). As expected, calibration plots revealed varying degrees of miscalibration, which recovered following site-specific recalibration. PsyMetRiC showed net benefit in both new cohorts, more so after recalibration. Interpretation: The study provides evidence of PsyMetRiC's generalizability in Western Europe, although further local and international validation studies are required. In future, PsyMetRiC could help clinicians internationally to identify young people with psychosis who are at higher cardiometabolic risk, so interventions can be directed effectively to reduce long-term morbidity and mortality. Funding: NIHR Cambridge Biomedical Research Centre (BRC-1215-20014); The Wellcome Trust (201486/Z/16/Z); Swiss National Research Foundation (320030-120686, 324730- 144064, and 320030-173211); The Carlos III Health Institute (CM20/00015, FIS00/3095, PI020499, PI050427, and PI060507); IDIVAL (INT/A21/10 and INT/A20/04); The Andalusian Regional Government (A1-0055-2020 and A1-0005-2021); SENY Fundacion Research (2005-0308007); Fundacion Marques de Valdecilla (A/02/07, API07/011); Ministry of Economy and Competitiveness and the European Fund for Regional Development (SAF2016-76046-R and SAF2013-46292-R).For the Spanish and French translation of the abstract see Supplementary Materials section.

Associations Between High Plasma Methylxanthine Levels, Sleep Disorders and Polygenic Risk Scores of Caffeine Consumption or Sleep Duration in a Swiss Psychiatric Cohort.

Objective: We first sought to examine the relationship between plasma levels of methylxanthines (caffeine and its metabolites) and sleep disorders, and secondarily between polygenic risk scores (PRS) of caffeine consumption or sleep duration with methylxanthine plasma levels and/or sleep disorders in a psychiatric cohort. Methods: Plasma levels of methylxanthines were quantified by ultra-high performance liquid chromatography/tandem mass spectrometry. In inpatients, sleep disorder diagnosis was defined using ICD-10 "F51.0," sedative drug intake before bedtime, or hospital discharge letters, while a subgroup of sedative drugs was used for outpatients. The PRS of coffee consumption and sleep duration were constructed using publicly available GWAS results from the UKBiobank. Results: 1,747 observations (1,060 patients) were included (50.3% of observations with sleep disorders). Multivariate analyses adjusted for age, sex, body mass index, setting of care and psychiatric diagnoses showed that patients in the highest decile of plasma levels of methylxanthines had more than double the risk for sleep disorders compared to the lowest decile (OR = 2.13, p = 0.004). PRS of caffeine consumption was associated with plasma levels of caffeine, paraxanthine, theophylline and with their sum (ß = 0.1; 0.11; 0.09; and 0.1, pcorrected = 0.01; 0.02; 0.02; and 0.01, respectively) but not with sleep disorders. A trend was found between the PRS of sleep duration and paraxanthine levels (ß = 0.13, pcorrected = 0.09). Discussion: Very high caffeine consumption is associated with sleep disorders in psychiatric in- and outpatients. Future prospective studies should aim to determine the benefit of reducing caffeine consumption in high caffeine-consuming patients suffering from sleep disorders.

The P450 oxidoreductase genotype is associated with CYP3A activity in vivo as measured by the midazolam phenotyping test.

BACKGROUND: CYP3A4, CYP3A5 and CYP3A7 are hepatic enzymes that metabolize about 50% of drugs on the market, with a large overlap in their specificities. We investigated the genetic bases that contribute to the variation of CYP3A activity. METHODS: We phenotyped 251 individuals from two independent studies (182 patients treated with methadone and 69 patients with clozapine) for CYP3A activity using the midazolam phenotyping test and genotyped them for CYP3A4, CYP3A5, and CYP3A7 genetic variants, including the single nucleotide polymorphism (SNP) rs4646437C>T in intron 7 of CYP3A4. Owing to the fact that CYP enzymes require electron transfer through the P450 oxidoreductase (POR), and functional impairment has been shown for the POR*28 SNP, this polymorphism was also analysed. RESULTS: We show that CYP3A4, CYP3A5 and CYP3A7 genotypes, including the SNP rs4646437C>T, do not reflect the inter-individual variability of CYP3A activity (P>0.1). In contrast, POR*28 TT genotype presents a 1.6-fold increase in CYP3A activity compared with POR*28C carriers (n = 182, P = 0.004). This finding was replicated in the second independent dataset (n = 69, P = 0.04). CONCLUSION: The SNP POR*28 seems to be a better genetic marker of the variability of total CYP3A activity in vivo than CYP3A4, CYP3A5 and CYP3A7 genetic variants.

ABCB1 and cytochrome P450 polymorphisms: clinical pharmacogenetics of clozapine.

To examine the genetic factors influencing clozapine kinetics in vivo, 75 patients treated with clozapine were genotyped for CYPs and ABCB1 polymorphisms and phenotyped for CYP1A2 and CYP3A activity. CYP1A2 activity and dose-corrected trough steady-state plasma concentrations of clozapine correlated significantly (r = -0.61; P = 1 x 10), with no influence of the CYP1A2*1F genotype (P = 0.38). CYP2C19 poor metabolizers (*2/*2 genotype) had 2.3-fold higher (P = 0.036) clozapine concentrations than the extensive metabolizers (non-*2/*2). In patients comedicated with fluvoxamine, a strong CYP1A2 inhibitor, clozapine and norclozapine concentrations correlate with CYP3A activity (r = 0.44, P = 0.075; r = 0.63, P = 0.007, respectively). Carriers of the ABCB1 3435TT genotype had a 1.6-fold higher clozapine plasma concentrations than noncarriers (P = 0.046). In conclusion, this study has shown for the first time a significant in vivo role of CYP2C19 and the P-gp transporter in the pharmacokinetics of clozapine. CYP1A2 is the main CYP isoform involved in clozapine metabolism, with CYP2C19 contributing moderately, and CYP3A4 contributing only in patients with reduced CYP1A2 activity. In addition, ABCB1, but not CYP2B6, CYP2C9, CYP2D6, CYP3A5, nor CYP3A7 polymorphisms, influence clozapine pharmacokinetics.

Cannabis and benzodiazepines as determinants of methadone trough plasma concentration variability in maintenance treatment: a transnational study.

PURPOSE: To assess tobacco, alcohol, cannabis and benzodiazepine use in methadone maintenance treatment (MMT) as potential sources of variability in methadone pharmacokinetics. METHODS: Trough plasma (R)- and (S)-methadone concentrations were measured on 77 Australian and 74 Swiss MMT patients with no additional medications other than benzodiazepines. Simple and multiple regression analyses were performed for the primary metric, plasma methadone concentration/dose. RESULTS: Cannabis and methadone dose were significantly associated with lower 24-h plasma (R)- and (S)-methadone concentrations/dose. The models containing these variables explained 14-16% and 17-25% of the variation in (R)- and (S)-methadone concentration/dose, respectively. Analysis of 61 patients using only CYP3A4 metabolised benzodiazepines showed this class to be associated with higher (R)-concentration/dose, which is consistent with a potential competitive inhibition of CYP3A4. CONCLUSION: Cannabis use and higher methadone doses in MMT could in part be a response to-or a cause of-more rapid methadone clearance. The effects of cannabis and benzodiazepines should be controlled for in future studies on methadone pharmacokinetics in MMT.

Sorafenib N-Oxide Is an Inhibitor of Human Hepatic CYP3A4.

The multi-kinase inhibitor sorafenib (SOR) is clinically important in the treatment of hepatocellular and renal cancers and undergoes CYP3A4-dependent oxidation in liver to the pharmacologically active N-oxide metabolite (SNO). There have been reports that kinase inhibitors such as SOR may precipitate pharmacokinetic interactions with coadministered drugs that compete for CYP3A4-mediated biotransformation, but these occur non-uniformly in patients. Clinical evidence also indicates that SNO accumulates in serum of some patients during prolonged SOR therapy. In this study undertaken in hepatic microsomes from individual donors, we assessed the possibility that SNO might contribute to pharmacokinetic interactions mediated by SOR. Enzyme kinetics of CYP3A4-mediated midazolam 1'-hydroxylation in individual human hepatic microsomes were analyzed by non-linear regression and appropriate replots. Thus, SNO and SOR were linear-mixed inhibitors of microsomal CYP3A4 activity (Kis 15 ± 4 and 33 ± 14 µM, respectively). To assess these findings, further molecular docking studies of SOR and SNO with the 1TQN crystal structure of CYP3A4 were undertaken. SNO elicited a larger number of interactions with key amino acid residues located in substrate recognition sequences of the enzyme. In the optimal docking pose, the N-oxide moiety of SNO was also found to interact directly with the heme moiety of CYP3A4. These findings suggest that SNO could contribute to pharmacokinetic interactions involving SOR, perhaps in individuals who produce high circulating concentrations of the metabolite.