Can Valproic Acid be an Inducer of Clozapine Metabolism?

Introduction: Prior clozapine studies indicated no effects, mild inhibition or induction of valproic acid (VPA) on clozapine metabolism. The hypotheses that (i) VPA is a net inducer of clozapine metabolism, and (ii) smoking modifies this inductive effect were tested in a therapeutic drug monitoring study. Methods: After excluding strong inhibitors and inducers, 353 steady-state total clozapine (clozapine plus norclozapine) concentrations provided by 151 patients were analyzed using a random intercept linear model. Results: VPA appeared to be an inducer of clozapine metabolism since total plasma clozapine concentrations in subjects taking VPA were significantly lower (27% lower; 95% confidence interval, 14-39%) after controlling for confounding variables including smoking (35% lower, 28-56%). Discussion: Prospective studies are needed to definitively establish that VPA may (i) be an inducer of clozapine metabolism when induction prevails over competitive inhibition, and (ii) be an inducer even in smokers who are under the influence of smoking inductive effects on clozapine metabolism

Psychotropic Drug Prescription in Adolescents: A Retrospective Study in a Swiss Psychiatric University Hospital.

This retrospective study aims to evaluate off-label prescriptions and administrations of psychotropic medications in adolescents in a university psychiatric hospital in Switzerland. Data were collected during the entire stays from the electronic database for 76 inpatients in 2008 and 76 inpatients in 2014. Data collected included gender, age, psychiatric diagnosis, duration of hospitalization, and psychotropic drug prescriptions and administrations. A total of 224 psychotropic drugs (mean 2.9 drugs/patient) were prescribed in 2008 and 268 (mean 3.5 drugs/patient) in 2014. Due to the prescriptions of some drugs as required, only 76% of the prescriptions were actually administered in 2008 (mean 2.3 drugs/patient) and 55% in 2014 (mean 1.9 drugs/patient). Antipsychotics were the most frequently prescribed drugs in 2008 (74% of patients) and 2014 (86% of patients). Anxiolytics were also highly prescribed in 2008 (54% of patients) and 2014 (66% of patients), as well as antidepressants in 2008 (30% of patients), but less in 2014 (13% of patients). Overall, 69% of prescriptions were found to be off label in 2008 and 68% in 2014, according to age, diagnosis, dose, or formulation as approved by Swissmedic. The medication classes with the highest rate of off-label prescriptions were antidepressants (100% for both years), antipsychotics (94% in 2008 and 92% in 2014), and hypnotics (67% in 2008 and 100% in 2014). For both study periods, at least one off-label psychotropic drug prescription and administration was recorded in 96% and 79% of the patients, respectively. The high rate of off-label psychotropic drug use strengthens the need for clinical trials to better evaluate the efficacy and safety of these treatments in adolescents

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

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. 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. 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. 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). These results may help to implement genetic testing before starting psychotropic drug treatment to identify patients at risk of important WG

Prevalence of ECG abnormalities and risk factors for QTc interval prolongation in hospitalized psychiatric patients.

Psychiatric patients are at risk of cardiovascular diseases, and many psychotropic drugs can prolong QTc interval. Requirements for electrocardiogram (ECG) monitoring have been set up in our psychiatric university hospital. The objective of this study was to determine the proportion of adult patients who had an ECG during their hospitalization, the prevalence of ECG abnormalities, the evolution of the QTc after admission, and the risk factors for QTc prolongation. Retrospective analysis of ECGs and clinical data of all patients with a complete hospitalization in 2015. Assessment of the influence of covariates on QTc using linear mixed-effects models. At least one ECG (n = 600) was performed during 37.6% of the stays (n = 1198) and in 45.5% of the patients (n = 871). Among the patients with an ECG, 17.9% had significant ECG abnormalities, including 7.6% with a prolonged QTc. QTc measured at admission and during hospitalization did not change significantly (n = 46, 419.4 ± 29.7 ms, 417.2 ± 27.6 ms, p = 0.71). In the multivariate model (292 patients, 357 ECGs), the covariates significantly associated with the QTc were gender (+15.9 ms if female, p < 0.0001), age (+0.4 ms/year, p = 0.0001), triglyceride levels (+5.7 ms/mmol/l, p = 0.005), and drugs with known risk of torsades de pointes (+6.2 ms if ⩾1 drug, p = 0.028). The prevalence of hospitalized psychiatric patients with an abnormal ECG indicates that ECGs should be performed systematically in this population. Prescription of psychotropic drugs should be done cautiously, particularly in patients with QTc prolongation risk factors

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 <sup>-8</sup> ): 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

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 (β = 0.1; 0.11; 0.09; and 0.1, p <sub>corrected</sub> = 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 (β = 0.13, p <sub>corrected</sub> = 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

Relation of 24-hour urinary caffeine and caffeine metabolite excretions with self-reported consumption of coffee and other caffeinated beverages in the general population.

Caffeine intake is generally estimated by self-reported consumption, but it remains unclear how well self-report associates with metabolite urinary excretion. We investigated the associations of self-reported consumption of caffeinated drinks with urinary excretion of caffeine and its major metabolites in an adult population. We used data from the population-based Swiss Kidney Project on Genes in Hypertension (SKIPOGH) study. Consumption of caffeinated coffee, decaffeinated coffee and other caffeinated beverages was assessed by self-administered questionnaire. Quantification of caffeine, paraxanthine, theobromine and theophylline was performed by ultra-high performance liquid chromatography tandem mass spectrometry in 24-h urine. Association of reported consumption of caffeinated drinks with urinary caffeine derived metabolites was determined by quantile regression. We then explored the association between urinary metabolite excretion and dichotomized weekly consumption frequency of caffeinated coffee, with Receiver Operator Characteristic (ROC) analysis. In the present analysis, we included 598 individuals (52% women, mean age =46 ± 17 years). Self-reported caffeinated coffee intake was positively associated with 24-h urinary excretions of paraxanthine, theophylline and caffeine (p < 0.001), whereas reported intakes of decaffeinated coffee and other caffeinated beverages showed no association. In ROC analysis, optimal discrimination between individuals consuming less than one caffeinated coffee/week, vs. at least one coffee, was obtained for 24-h urinary paraxanthine (Area Under Curve (AUC) = 0.868, 95% Confidence Interval (CI) [0.830;0.906]), with slightly lower performance for theophylline and caffeine, whereas theobromine did not allow any discrimination. Our results suggest that reported consumption of caffeinated coffee is positively associated with 24-h urinary excretion of caffeine, paraxanthine, and theophylline, and may be used as a marker of caffeine intake for epidemiological studies

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.

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. 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. 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/m <sup>2</sup> 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. Insomnia disorders are significantly associated with metabolic worsening and risk of death from cardiovascular diseases in psychiatric patients

Buprenorphine and norbuprenorphine quantification in human plasma by simple protein precipitation and ultra-high performance liquid chromatography tandem mass spectrometry.

A highly sensitive ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method was developed for the quantification of buprenorphine and its major metabolite norbuprenorphine in human plasma. In order to speed up the process and decrease costs, sample preparation was performed by simple protein precipitation with acetonitrile. To the best of our knowledge, this is the first application of this extraction technique for the quantification of buprenorphine in plasma. Matrix effects were strongly reduced and selectivity increased by using an efficient chromatographic separation on a sub-2μm column (Acquity UPLC BEH C18 1.7μm, 2.1×50mm) in 5min with a gradient of ammonium formate 20mM pH 3.05 and acetonitrile as mobile phase at a flow rate of 0.4ml/min. Detection was made using a tandem quadrupole mass spectrometer operating in positive electrospray ionization mode, using multiple reaction monitoring. The procedure was fully validated according to the latest Food and Drug Administration guidelines and the Société Française des Sciences et Techniques Pharmaceutiques. Very good results were obtained by using a stable isotope-labeled internal standard for each analyte, to compensate for the variability due to the extraction and ionization steps. The method was very sensitive with lower limits of quantification of 0.1ng/ml for buprenorphine and 0.25ng/ml for norbuprenorphine. The upper limit of quantification was 250ng/ml for both drugs. Trueness (98.4-113.7%), repeatability (1.9-7.7%), intermediate precision (2.6-7.9%) and internal standard-normalized matrix effects (94-101%) were in accordance with international recommendations. The procedure was successfully used to quantify plasma samples from patients included in a clinical pharmacogenetic study and can be transferred for routine therapeutic drug monitoring in clinical laboratories without further development