Long-term changes in adiposity markers during and after antidepressant therapy in a community cohort.

Research on antidepressant-related weight changes over more than 12 months is scarce and adjustment for the effects of depressive episodes has rarely been applied. Accordingly, our aim was to assess the associations of the use of any antidepressants, subclasses of antidepressant and specific compounds prior to baseline and during a 5.5-year follow-up with changes in adiposity markers, and the effect of sex on these associations, with adjustment for multiple confounders including the effects of depressive episodes and their severity. Data stemmed from a prospective cohort study including 2479 randomly selected 35-66 year-old residents of an urban area (mean age 49.9 years, 53.3% women) who underwent physical and psychiatric evaluations at baseline and follow-up. Weight, height, waist circumference, and body fat were measured by trained nurses and information on diagnosis and antidepressant use prior to baseline and during follow-up was collected through standardized interviews. In the fully adjusted models, the number of antidepressants, mainly SSRIs and TCAs, used prior to baseline, was associated with a lower increase of body-mass index (BMI, ß (95%CI) = -0.12 (-0.19, -0.05)) and waist circumference (ß = -0.28 (-0.56, -0.01)), whereas participants treated with antidepressants during the follow-up had a steeper increase in BMI (ß = 0.32 (0.13, 0.50)) and waist circumference (ß = 1.23 (0.44, 2.01)). Within the class of SSRIs, the use of fluoxetine, sertraline or escitalopram during follow-up was associated with a steeper increase in adiposity markers. The associations of SSRIs with BMI and waist circumference were only observed when the SSRIs were used during the second period of the follow-up. Sex did not moderate these associations. Our findings suggest an increase of adiposity markers during sustained treatment with TCAs and SSRIs, which however return to normal levels after cessation of treatment. Hence, the benefit of long-term administration of these antidepressants should be carefully weighed against the potential risk of weight gain.

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.

Aripiprazole dose associations with metabolic adverse effect: Results from a longitudinal study.

OBJECTIVE: Weight gain, blood lipids and/or glucose dysregulation can follow aripiprazole treatment onset. Whether aripiprazole dosage is associated with an increase in these metabolic parameters remains uncertain. The present study investigates aripiprazole dose associations with weight change, blood glucose, lipids, and blood pressure. METHODS: 422 patients taking aripiprazole for a minimum of three weeks to one year were selected from PsyMetab and PsyClin cohorts. Associations between aripiprazole dose and metabolic outcomes were examined using linear mixed-effect models. RESULTS: Aripiprazole dose was associated with weight change when considering its interaction with treatment duration (interaction term: -0.10, p < 0.001). This interaction resulted in greater weight gain for high versus low doses at the beginning of the treatment, this result being overturned at approximately five months, with greater weight increase for low versus high doses thereafter. LDL and HDL cholesterol levels were associated with aripiprazole dose over five months independently of treatment duration, with an average of 0.06 and 0.02 mmol/l increase for each 5 mg increment, respectively (p = 0.033 and p = 0.016, respectively). Furthermore, mean dose increases were associated with greater odds (+30 % per 5 mg increase) of clinically relevant weight gain (i.e., ≥7 %) over one year (p = 0.025). CONCLUSION: Aripiprazole dose was associated with one-year weight changes when considering its interaction with treatment duration. Increasing its dose could lead to metabolic worsening over the first five months of treatment, during which minimum effective doses should be particularly preferred.

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.

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.

Neurocognition and NMDAR co-agonists pathways in individuals with treatment resistant first-episode psychosis: a 3-year follow-up longitudinal study.

This study aims to determine whether 1) individuals with treatment-resistant schizophrenia display early cognitive impairment compared to treatment-responders and healthy controls and 2) N-methyl-D-aspartate-receptor hypofunction is an underlying mechanism of cognitive deficits in treatment-resistance. In this case‒control 3-year-follow-up longitudinal study, n = 697 patients with first-episode psychosis, aged 18 to 35, were screened for Treatment Response and Resistance in Psychosis criteria through an algorithm that assigns patients to responder, limited-response or treatment-resistant category (respectively resistant to 0, 1 or 2 antipsychotics). Assessments at baseline: MATRICS Consensus Cognitive Battery; N-methyl-D-aspartate-receptor co-agonists biomarkers in brain by MRS (prefrontal glutamate levels) and plasma (D-serine and glutamate pathways key markers). Patients were compared to age- and sex-matched healthy controls (n = 114). Results: patient mean age 23, 27% female. Treatment-resistant (n = 51) showed lower scores than responders (n = 183) in processing speed, attention/vigilance, working memory, verbal learning and visual learning. Limited responders (n = 59) displayed an intermediary phenotype. Treatment-resistant and limited responders were merged in one group for the subsequent D-serine and glutamate pathway analyses. This group showed D-serine pathway dysregulation, with lower levels of the enzymes serine racemase and serine-hydroxymethyltransferase 1, and higher levels of the glutamate-cysteine transporter 3 than in responders. Better cognition was associated with higher D-serine and lower glutamate-cysteine transporter 3 levels only in responders; this association was disrupted in the treatment resistant group. Treatment resistant patients and limited responders displayed early cognitive and persistent functioning impairment. The dysregulation of NMDAR co-agonist pathways provides underlying molecular mechanisms for cognitive deficits in treatment-resistant first-episode psychosis. If replicated, our findings would open ways to mechanistic biomarkers guiding response-based patient stratification and targeting cognitive improvement in clinical trials.

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.

Pharmacokinetics and Pharmacodynamics of Inhaled Nicotine Salt and Free-Base Using an E-cigarette: A Randomized Crossover Study.

INTRODUCTION: Popular "pod-style" e-cigarettes commonly use nicotine salt-based e-liquids that cause less irritation when inhaled and can deliver higher nicotine concentrations than free-base nicotine. This study investigated the pharmacokinetic and pharmacodynamic effects of different nicotine formulations (salt vs. free-base) and concentrations that might influence systemic nicotine absorption and appeal of e-cigarettes. AIMS AND METHODS: In this randomized, double-blind, within-subject crossover study, 20 non-nicotine-naïve participants were switched among three e-liquids (free-base nicotine 20 mg/mL, nicotine salt 20 mg/mL, nicotine salt 40 mg/mL) using a refillable pod system and a standardized vaping protocol (one puff every 30 seconds, 10 puffs total). Serum nicotine concentrations and vital signs were assessed over 180 minutes; direct effects, craving, satisfaction, withdrawal, and respiratory symptoms were measured using questionnaires. CYP2A6 genotypes and the nicotine metabolite ratio were also assessed. RESULTS: Eleven (55%) participants were male and the median age was 23.5 years (range 18-67). All three formulations differed significantly in peak serum nicotine concentration (baseline adjusted Cmax, median (range): 12.0 ng/mL (1.6-27.3), 5.4 ng/mL (1.9-18.7), and 3.0 ng/mL (1.3-8.8) for nicotine salt 40 mg/mL, nicotine salt 20 mg/mL and free-base 20 mg/mL, respectively). All groups reached Cmax 2.0-2.5 minutes (median) after their last puff. Differences in subjective effects were not statistically significant. No serious adverse events were observed. CONCLUSIONS: Free-base 20 mg/mL formulations achieved lower blood nicotine concentrations than nicotine salt 20 mg/mL, while 40 mg/mL nicotine salt yielded concentrations similar to cigarette smoking. The findings can inform regulatory policy regarding e-liquids and their potential use in smoking cessation. IMPLICATIONS: Nicotine salt formulations inhaled by an e-cigarette led to higher nicotine delivery compared to nicotine-free-base formulations with the same nicotine concentration. These findings should be considered in future regulatory discussions. The 40 mg/mL nicotine salt formulation showed similar nicotine delivery as combustible cigarettes, albeit at concentrations over the maximum limit for e-liquids allowed in the European Union. Nicotine delivery resembling combustible cigarettes might be beneficial for smokers willing to quit to adequately alleviate withdrawal symptoms. However, increased nicotine delivery can also pose a public health risk, raising concerns about abuse liability, especially among youth and nonsmokers.

Associations between antipsychotics-induced weight gain and brain networks of impulsivity.

Given the unpredictable rapid onset and ubiquitous consequences of weight gain induced by antipsychotics, there is a pressing need to get insights into the underlying processes at the brain system level that will allow stratification of "at risk" patients. The pathophysiological hypothesis at hand is focused on brain networks governing impulsivity that are modulated by neuro-inflammatory processes. To this aim, we investigated brain anatomy and functional connectivity in patients with early psychosis (median age: 23 years, IQR = 21-27) using anthropometric data and magnetic resonance imaging acquired one month to one year after initiation of AP medication. Our analyses included 19 patients with high and rapid weight gain (i.e., ≥5% from baseline weight after one month) and 23 patients with low weight gain (i.e., <5% from baseline weight after one month). We replicated our analyses in young (26 years, IQR = 22-33, N = 102) and middle-aged (56 years, IQR = 51-62, N = 875) healthy individuals from the general population. In early psychosis patients, higher weight gain was associated with poor impulse control score (ß = 1.35; P = 0.03). Here, the observed brain differences comprised nodes of impulsivity networks - reduced frontal lobe grey matter volume (Pcorrected = 0.007) and higher striatal volume (Pcorrected = 0.048) paralleled by disruption of fronto-striatal functional connectivity (R = -0.32; P = 0.04). Weight gain was associated with the inflammatory biomarker plasminogen activator inhibitor-1 (ß = 4.9, P = 0.002). There was no significant association between increased BMI or weight gain and brain anatomy characteristics in both cohorts of young and middle-aged healthy individuals. Our findings support the notion of weight gain in treated psychotic patients associated with poor impulse control, impulsivity-related brain networks and chronic inflammation.

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.

Associations of Valproate Doses With Weight Gain in Adult Psychiatric Patients: A 1-Year Prospective Cohort Study.

Objective: The aim of this study was to evaluate valproate dose association with weight change, blood glucose, lipid levels, and blood pressure in a psychiatric population.Methods: Data from 215 patients taking valproate for up to 1 year were collected from 2 longitudinal studies that monitored metabolic variables between 2007 and 2022. Linear mixed-effect models and logistic regressions were used to analyze the associations between valproate doses and metabolic outcomes.Results: An increase in valproate dose of 500 mg was associated with a weight change of +0.52% per month over a year (P < .001). The association between valproate dose and weight change was evident both before and after 3 months of treatment. Weight increase was greater for treatment durations of < 3 months compared to ≥ 3 months (+0.56%, P < .001 and +0.12%, P = .02 per month, respectively). Using piecewise regression, a significant association between dose and weight gain was observed in patients receiving doses equal to or above the median dose (1,300 mg/d), with a +0.50% increase in weight for each dose increment of 500 mg (P = .004). Among men, each 500 mg dose increment was associated with weight increases of +0.59% per month (P = .004), whereas a trend was observed for women (+0.40%, P = .09). No associations were found between valproate doses and blood glucose, lipid levels, or blood pressure over a 6-month treatment period.Conclusions: This study provides evidence that valproate dose, mainly for doses at or above 1,300 mg/d, is associated with weight gain in psychiatric patients, suggesting that the lowest effective doses should be prescribed to minimize weight gain.

DNA methylation may partly explain psychotropic drug-induced metabolic side effects: results from a prospective 1-month observational study.

BACKGROUND: Metabolic side effects of psychotropic medications are a major drawback to patients' successful treatment. Using an epigenome-wide approach, we aimed to investigate DNA methylation changes occurring secondary to psychotropic treatment and evaluate associations between 1-month metabolic changes and both baseline and 1-month changes in DNA methylation levels. Seventy-nine patients starting a weight gain inducing psychotropic treatment were selected from the PsyMetab study cohort. Epigenome-wide DNA methylation was measured at baseline and after 1 month of treatment, using the Illumina Methylation EPIC BeadChip. RESULTS: A global methylation increase was noted after the first month of treatment, which was more pronounced (p < 2.2 × 10-16) in patients whose weight remained stable (< 2.5% weight increase). Epigenome-wide significant methylation changes (p < 9 × 10-8) were observed at 52 loci in the whole cohort. When restricting the analysis to patients who underwent important early weight gain (≥ 5% weight increase), one locus (cg12209987) showed a significant increase in methylation levels (p = 3.8 × 10-8), which was also associated with increased weight gain in the whole cohort (p = 0.004). Epigenome-wide association analyses failed to identify a significant link between metabolic changes and methylation data. Nevertheless, among the strongest associations, a potential causal effect of the baseline methylation level of cg11622362 on glycemia was revealed by a two-sample Mendelian randomization analysis (n = 3841 for instrument-exposure association; n = 314,916 for instrument-outcome association). CONCLUSION: These findings provide new insights into the mechanisms of psychotropic drug-induced weight gain, revealing important epigenetic alterations upon treatment, some of which may play a mediatory role.

Metabolic disturbances are risk factors for readmission to psychiatric hospitals in non-smokers but not in smokers: results from a Swiss psychiatric cohort and in first-episode psychosis patients.

Background: Psychiatric patients are at high risk of readmission, and a high body mass index has previously been shown as a risk factor. We sought to replicate this finding and 1) to prospectively assess the association of metabolic syndrome and its five components with readmission in psychiatric hospitals and 2) to identify other clinical and sociodemographic predictors of readmission. Methods: Between 2007 and 2019, data on 16727 admissions of 7786 adult and elderly patients admitted to the Department of Psychiatry of the Lausanne University Hospital, were collected. Metabolic syndrome was defined according to the International Diabetes Federation definition. Cox frailty models were used to investigate the associations between readmission and metabolic disturbances. Results: A total of 2697 (35%) patients were readmitted to our psychiatric hospital. Novel risk factors for readmission in non-smokers were identified, including being overweight (HR=1.26; 95%CI=[1.05; 1.51]) or obese (HR=1.33; 95%CI=[1.08; 1.62]), displaying hypertriglyceridemia (HR=1.21; 95%CI=[1.04; 1.40]) and metabolic syndrome (HR=1.26; 95%CI=[1.02; 1.55]). Central obesity and hyperglycemia increased the risk of readmission when considering the Health of the Nation Outcome Scales variable. In first-episode psychosis patients, obesity (HR=2.23; 95%CI=[1.14; 4.30]) and high-density lipoprotein hypocholesterolemia (HR=1.90; 95%CI=[1.14; 3.20]) doubled the risk of readmission. Conclusion: The observed interaction between smoking and metabolic variables are compatible with a ceiling effect; metabolic variables increase the risk of readmission in non-smokers but not in smokers who are already at higher risk. Future studies should determine whether better metabolic monitoring and treatment can reduce readmission risk.

[Antipsychotic prescribing in adults : what to watch out for ?] / Prescription d'antipsychotiques chez les adultes : à quoi faut-il être attentif ?

Antipsychotics are known to produce frequent and/or potentially serious adverse effects, including neurological, cardiovascular, metabolic and endocrine effects. The side-effects of antipsychotics vary according to their affinity for different central and peripheral receptors, and individual vulnerabilities. Some of these side-effects are dose-dependent, while others are little or not ; thus, management strategies need to be adapted. Good management of adverse events is important to encourage patients' medication adherence and to reduce the cardiovascular morbidity and mortality of side effects. Good collaboration between psychiatrists and general practitioners or specialists is essential.

Les antipsychotiques sont connus pour engendrer des effets indésirables fréquents et/ou potentiellement graves, notamment neurologiques, cardiovasculaires, métaboliques et endocriniens. Les effets secondaires des antipsychotiques varient selon leur profil d'affinités pour les différents récepteurs cérébraux et périphériques et selon les vulnérabilités individuelles. Certains d'entre eux sont dose-dépendants, d'autres peu ou pas ; les stratégies de prise en charge sont donc à adapter. Une bonne gestion des effets indésirables est importante pour favoriser l'adhésion médicamenteuse des patients et atténuer leur impact en termes de morbimortalité. Une bonne collaboration entre médecins psychiatres et généralistes ou spécialistes est nécessaire.

Exploring low clozapine C/D ratios, inverted clozapine-norclozapine ratios and undetectable concentrations as measures of non-adherence in clozapine patients: A literature review and a case series of 17 patients from 3 studies.

BACKGROUND: Up to 1/2 of outpatients prescribed clozapine may be partially/fully non-adherent, based on therapeutic drug monitoring (TDM). Three indices for measuring partial/full non-adherence are proposed a: 1) clozapine concentration/dose (C/D) ratio which drops to half or more of what is expected in the patient; 2) clozapine/norclozapine ratio that becomes inverted; and 3) clozapine concentration that becomes non-detectable. METHODS: These 3 proposed indices are based on a literature review and 17 cases of possible non-adherence from 3 samples: 1) an inpatient study in a Chinese hospital, 2) an inpatient randomized clinical trial in a United States hospital, and 3) and a Uruguayan outpatient study. RESULTS: The first index of non-adherence is a clozapine C/D ratio which is less than half the ratio corresponding to the patient's specific ancestry group and sex-smoking subgroup. Knowing the minimum therapeutic dose of the patient based on repeated TDM makes it much easier to establish non-adherence. The second index is inverted clozapine/norclozapine ratios in the absence of alternative explanations. The third index is undetectable concentrations. By using half-lives, the chronology of the 3 indices of non-adherence was modeled in two patients: 1) the clozapine C/D ratio dropped to ≥1/2 of what is expected from the patient (around day 2); 2) the clozapine/norclozapine ratio became inverted (around day 3); and 3) the clozapine concentration became undetectable by the laboratory (around days 9-11). CONCLUSION: Prospective studies should further explore these proposed clozapine indices in average patients, poor metabolizers (3 presented) and ultrarapid metabolizers (2 presented).

Infant exposure to Fluvoxamine through placenta and human milk: a case series - A contribution from the ConcePTION project.

Introduction: Fluvoxamine is widely used to treat depression during pregnancy and lactation. However, limited data are available on its transfer to the fetus or in human milk. This case series provides additional information on the infant exposure to fluvoxamine during pregnancy and lactation. Case presentation: Two women, aged 38 and 34 years, diagnosed with depression were treated with 50 mg fluvoxamine during pregnancy and lactation. At delivery a paired maternal and cord blood sample was collected for each woman. The first mother exclusively breastfed her child for 4 months and gave one foremilk and one hindmilk sample at 2 days and 4 weeks post-partum, whereas the second mother did not breastfeed. Results: The cord to plasma concentration ratios were 0.62 and 0.48, respectively. At 2 weeks post-partum, relative infant doses (RID) were 0.47 and 0.57% based on fluvoxamine concentrations in foremilk and hindmilk, respectively. At 4 weeks post-partum, the RIDs were 0.35 and 0.90%, respectively. The child from the first mother was born healthy and showed a normal development at the 6th, 18th and 36th month follow-ups. One of the twins from the second woman was hospitalized for hypoglycemia that was attributed to gestational diabetes and low birth weight. The second one was born healthy. Conclusion: These results suggest a minimal exposure to fluvoxamine during lactation which is in accordance with previously published data. Larger clinical and pharmacokinetic studies assessing the long-term safety of this drug during lactation and the variability of its exposure through breastmilk are warranted.

Clozapine ultrarapid metabolism during weak induction probably exists but requires careful diagnosis. A literature review, five new cases and a proposed definition.

During weak induction (from smoking and/or valproate co-prescription), clozapine ultrarapid metabolizers (UMs) need very high daily doses to reach the minimum therapeutic concentration of 350 ng/ml in plasma; clozapine UMs need clozapine doses higher than: 1) 900 mg/day in patients of European/African ancestry, or 2) 600 mg/day in those of Asian ancestry. Published clozapine UMs include 10 males of European/African ancestry, mainly assessed with single concentrations. Five new clozapine UMs (two of European and three of Asian ancestry) with repeated assessments are described. A US double-blind randomized trial included a 32-year-old male smoking two packages/day with a minimum therapeutic dose of 1,591 mg/day from a single TDM during open treatment of 900 mg/day. In a Turkish inpatient study, a 30-year-old male smoker was a possible clozapine UM needing a minimum therapeutic dose of 1,029 mg/day estimated from two trough steady-state concentrations on 600 mg/day. In a Chinese study, three possible clozapine UMs (all male smokers) were identified. The clozapine minimum therapeutic dose estimated with trough steady-state concentrations >150 ng/ml was: 1) 625 mg/day, based on a mean of 20 concentrations in Case 3; 2) 673 mg/day, based on a mean of 4 concentrations in Case 4; and 3) 648 mg/day, based on a mean of 11 concentrations in Case 5. Based on these limited studies, clozapine UMs during weak induction may account for 1-2% of clozapine-treated patients of European ancestry and <1% of those of Asian ancestry. A clozapine-to-norclozapine ratio <0.5 should not be used to identify clozapine UMs.

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.

The Influence of a Roux-en-Y Gastric Bypass on Plasma Concentrations of Antidepressants.

PURPOSE: Roux-en-Y gastric bypass (RYGB) involves alterations of the gastrointestinal tract resulting in altered absorption. Patients with obesity have a higher prevalence of depression, and antidepressants are often prescribed. Alterations caused by RYGB could modify drug bioavailability and cause potential subtherapeutic plasma concentrations, increasing the risk of depressive relapse. The aim of this study was to describe the evolution of trough drug dose-normalized antidepressant plasma concentrations before and after RYGB. MATERIALS AND METHODS: This naturalistic prospective case series considers patients with trough plasma concentrations in a 1-year timeframe before and after RYGB. Only antidepressants prescribed to at least three patients were included in the present study. RESULTS: Thirteen patients (n = 12 females, median age 44 years, median BMI before intervention = 41.3 kg/m2) were included. Two patients were treated concurrently with fluoxetine and trazodone; the remaining patients were all treated with antidepressant monotherapy. Therapeutic drug monitoring (TDM) values for duloxetine (n = 3), escitalopram (n = 4), fluoxetine (n = 4), and trazodone (n = 4) before (median 4.7 weeks) and after (median 21.3 weeks) RYGB intervention were analyzed. Compared to preintervention, median [interquartile range] decreases in dose-normalized trough plasma concentrations for duloxetine (33% [- 47; - 23]), escitalopram (43% [- 51; - 31]), fluoxetine (9% [- 20; 0.2]), and trazodone (16% [- 29; 0.3]) were observed. CONCLUSION: This study shows a decrease in plasma antidepressant concentrations following RYGB. TDM before and after RYGB, in addition to close monitoring of psychiatric symptomatology, may help optimize antidepressant treatment after bariatric surgery. These results also highlight the need for prospective studies assessing the clinical evidence available through TDM in these patients.

Is Clozapine-induced Weight Gain Dose-dependent? Results From a Prospective Cohort Study.

BACKGROUND: Antipsychotic-induced metabolic adverse effects are risk factors for cardiometabolic comorbidities. Whether dose lowering could mitigate such effects remains unclear. The present study aims to investigate the associations between clozapine doses and modifications of weight, blood pressure, blood glucose, and lipid levels. STUDY DESIGN: Linear mixed-effects models of weight changes over 1 year and of variations of other metabolic parameters over 4 months were applied to a prospective cohort of 115 patients. Age- and sex-stratified analyses of weight changes were also performed. STUDY RESULTS: Each 100 mg dose increment of clozapine was associated on average with a +0.48% weight increase (P = .004) over 1 year of treatment. Weight increase was greater for treatment duration ≤3 vs >3 months (+0.84% and +0.47% per month, respectively, P < .001), with a significant association with the dose for durations >3 months (+0.54%, P = .004) and a trend for durations ≤3 months (+0.33%, P = .075). Dose increments of 100 mg were also associated with weight increases of +0.71% among adults (P = .001), +1.91% among the elderly (P < .001) and +1.32% among men (P < .001) with no associations among women (P = .62). Among young adults, weight change was positively associated with doses ≤300 mg/day (+2.19% per 100 mg, P = .001), whereas no association was found with doses >300 mg/day (P = .60). No significant effect of clozapine dose on other metabolic parameters was found. CONCLUSIONS: This study reports a modest effect of clozapine dose increases on weight gain over 1 year with differences among age categories and sexes and no dose effect on other metabolic parameters over 4 months.