ABSTRACT
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.
Subject(s)
Antipsychotic Agents , beta-Defensins , Humans , Genome-Wide Association Study , Antipsychotic Agents/adverse effects , Longitudinal Studies , Switzerland , Psychotropic Drugs/adverse effects , Weight Gain/genetics , beta-Defensins/geneticsABSTRACT
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.
ABSTRACT
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.
ABSTRACT
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.
Subject(s)
Caffeine , Self Report , Theophylline , Caffeine/blood , Caffeine/administration & dosage , Humans , Female , Male , Theophylline/blood , Middle Aged , Adult , Switzerland , Coffee , Surveys and Questionnaires , Aged , Chromatography, High Pressure Liquid/methodsABSTRACT
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.
Subject(s)
Antipsychotic Agents , Drug-Related Side Effects and Adverse Reactions , General Practitioners , Humans , Adult , Antipsychotic Agents/adverse effects , Medication AdherenceABSTRACT
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.
Subject(s)
Cardiovascular Diseases , Metabolic Syndrome , Sleep Initiation and Maintenance Disorders , Cardiovascular Diseases/chemically induced , Cardiovascular Diseases/epidemiology , Female , Humans , Male , Metabolic Syndrome/chemically induced , Metabolic Syndrome/complications , Metabolic Syndrome/epidemiology , Prospective Studies , Psychotropic Drugs/adverse effects , Switzerland/epidemiology , Weight GainABSTRACT
Confronted with a complaint of insomnia, several points must be considered before prescribing a specific treatment. In particular, it is necessary to optimize the management of somatic and psychiatric comorbidities that can affect sleep and to review the intake of sleep-disrupting substances and drugs. The current guidelines for insomnia rank treatment options based on the quality of the evidence. They all agree to recommend cognitive behavioural therapy for insomnia as first-line treatment. Pharmacological treatment should only be considered if this therapy fails. We then propose to start with the drugs presenting the best safety profile before prescribing, if necessary, those having better effectiveness evidence but carrying a greater risk of side effects.
Face à une plainte d'insomnie, plusieurs points sont à prendre en compte avant d'envisager un traitement spécifique, notamment l'optimisation de la prise en charge des comorbidités somatiques et psychiatriques pouvant péjorer le sommeil et la revue de la prise de substances et médicaments le perturbant. Les recommandations sur l'insomnie classent les options thérapeutiques selon la qualité des études à disposition. Elles s'accordent toutes à recommander la thérapie cognitivo-comportementale spécifique pour l'insomnie en première intention. Un traitement pharmacologique ne devrait être envisagé qu'en cas d'échec de cette thérapie. Nous proposons alors de débuter avec les molécules présentant le meilleur profil de sécurité avant de passer, si nécessaire, à celles ayant mieux démontré leur efficacité mais comportant un plus grand risque d'effets secondaires.
Subject(s)
Cognitive Behavioral Therapy , Sleep Initiation and Maintenance Disorders , Comorbidity , Humans , Sleep , Sleep Initiation and Maintenance Disorders/drug therapyABSTRACT
Cases of addictions and misuses on gabapentinoids are increasingly reported. But the underlying pharmacological mechanism is not completely understood. Here is an uptodate of the current knowledges on this dependence and its management.
Des cas de mésusages et d'addictions aux gabapentinoïdes sont de plus en plus fréquemment rapportés, sans que le mécanisme pharmacologique sous-jacent ne soit complètement compris. Nous faisons un état des lieux des connaissances sur cette dépendance et sa prise en charge.
Subject(s)
Behavior, Addictive , Gabapentin , HumansABSTRACT
The management of patients who have become dependent on benzodiazepines and analogues is a problem frequently encountered in both somatic and psychiatric medicine. No pharmacological treatment is currently recognized as effective in the management of these addictions, apart from a gradual reduction of doses. We propose practical strategies for the implementation of gradual dose reduction and choice of molecules while promoting individual adaptation to the withdrawal symptoms presented by the patient.
La prise en charge de patients ayant développé une dépendance aux benzodiazépines et analogues est une problématique rencontrée fréquemment tant en médecine somatique que psychiatrique. Aucun traitement pharmacologique n'est actuellement reconnu comme efficace dans la prise en charge de ces dépendances, en dehors d'une réduction progressive des doses. Nous proposons des stratégies pratiques de mise en Åuvre de réduction progressive des doses et de choix de molécules tout en favorisant une adaptation individuelle aux symptômes de sevrage présentés par le patient.
Subject(s)
Behavior, Addictive , Substance Withdrawal Syndrome , Substance-Related Disorders , Benzodiazepines/therapeutic use , Humans , Substance Withdrawal Syndrome/drug therapy , Substance-Related Disorders/therapyABSTRACT
Acute treatment of agitation in psychiatry is one of the urgent situations for which management recommendations are needed. Various existing international recommendations have been evaluated and adapted to our clinical practice and to the drugs available in Switzerland in order to propose a uniform management strategy in our hospital. This strategy includes a treatment choice algorithm with different options depending on the clinical situation and the possible route of administration. Dose recommendations for the oral and intramuscular routes, certain pharmacokinetic parameters, as well as risks of interactions and important warnings are also included in this clinical recommendation.
Le traitement aigu de l'agitation en psychiatrie fait partie des situations urgentes pour lesquelles des recommandations de prise en charge sont nécessaires. Diverses recommandations internationales existantes ont été évaluées et adaptées à notre pratique clinique ainsi qu'aux médicaments disponibles en Suisse afin de proposer une stratégie de prise en charge uniformisée au sein de notre hôpital. Cette stratégie inclut un algorithme de choix de traitement avec différentes options selon la situation clinique et la voie d'administration possible. Des recommandations de doses pour les voies orale et intramusculaire, certains paramètres pharmacocinétiques, ainsi que les risques d'interactions et des mises en garde importantes figurent également dans cette recommandation clinique.
Subject(s)
Algorithms , Clinical Decision-Making , Psychiatry/methods , Tranquilizing Agents/administration & dosage , Tranquilizing Agents/therapeutic use , Decision Theory , Drug Administration Routes , Humans , Switzerland , Tranquilizing Agents/pharmacokineticsABSTRACT
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.
Subject(s)
Body Weight/drug effects , Psychotropic Drugs/adverse effects , Weight Gain , Adult , Area Under Curve , Female , Genetic Markers , Humans , Longitudinal Studies , Male , Middle Aged , Models, StatisticalABSTRACT
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.
ABSTRACT
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.
ABSTRACT
Objectives: The decision to prescribe a medication and the choice of which one are often complex, particularly in the field of child and adolescent psychiatry where evidence is scarce. The aim of this review is to provide a synthesis of psychotropic drugs approved in children and adolescents for psychiatric indications in several countries. Methods: All psychopharmacological treatments used in child and adolescent psychiatry, approved by at least one regulatory agency from Switzerland, the United Kingdom, France, the European Union, or the United States, were considered. A comprehensive review of the summaries of product characteristics was performed. Results: A total of 143 psychotropic drugs were included: 47 anxiolytics/hypnotics, 45 antidepressants, 37 antipsychotics, 10 medications for attention-deficit/hyperactivity disorder (ADHD), and 4 mood stabilizers. Only a few of these drugs were approved for use in children or adolescents (38%) at least for a single psychiatric diagnosis in at least one country. The therapeutic class with the lowest rate of approved status was antidepressants (20%), followed by mood stabilizers (25%), anxiolytics/hypnotics (28%), antipsychotics (57%), and medications for ADHD (100%). Important differences in approved diagnoses, ages, and doses were observed between regulatory agencies. Tables presenting drugs for approved diagnoses based on age and regulatory agencies are presented in this article. Drugs classified by regulatory agencies, with complete data on diagnoses, ages, doses, pharmaceutical forms, and particular restrictions, are presented as Supplementary Material. Conclusion: This article provides an overview to prescribers with respect to the approved medications in children and adolescents in selected European countries and the United States.
Subject(s)
Anti-Anxiety Agents , Antipsychotic Agents , Adolescent , Anti-Anxiety Agents/therapeutic use , Anticonvulsants/therapeutic use , Antidepressive Agents/therapeutic use , Antimanic Agents/therapeutic use , Antipsychotic Agents/therapeutic use , Child , Drug Prescriptions , Humans , Hypnotics and Sedatives/therapeutic use , Pharmaceutical Preparations , Psychotropic Drugs/therapeutic use , United StatesABSTRACT
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.
Subject(s)
Antipsychotic Agents , Adult , Antipsychotic Agents/adverse effects , Benzodiazepines/adverse effects , Humans , Olanzapine/adverse effects , Prospective Studies , Weight GainABSTRACT
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.
ABSTRACT
BACKGROUND: A simple liquid chromatography mass spectrometry method was developed and validated for the simultaneous determination of antidementia drugs, including donepezil, galantamine, rivastigmine and its major metabolite, NAP 226-90, and memantine. METHODS: A solid phase extraction procedure with a mixed-mode sorbent was used to isolate the drugs from 0.5 mL human plasma. Reverse phase chromatographic separation of the compounds was obtained with a gradient elution of an ammonium acetate buffer at pH 9.3 and acetonitrile and the analytes were detected by mass spectrometry in the single ion monitoring mode. RESULTS: The method was validated according to the recommendations of the Food and Drug Administration, including assessment of trueness (-8.0% to +10.7%), imprecision (repeatability: 1.1-4.9%, intermediate imprecision: 2.1-8.5%), selectivity and matrix effects variability (less than 6%) as well as short- and long-term stability in plasma. The calibration ranges were from 1 ng/mL to 300 ng/mL (rivastigmine and memantine) and 2 ng/mL to 300 ng/mL (donepezil, galantamine, and NAP 226-90). CONCLUSIONS: The method was successfully applied to patients' samples and might contribute to evaluate whether a therapeutic drug monitoring-guided dose adjustment of antidementia drugs could contribute to minimize the risk of adverse reactions and to increase the probability of efficient therapeutic response.
Subject(s)
Cholinesterase Inhibitors/blood , Dementia/drug therapy , Drug Monitoring/methods , Receptors, N-Methyl-D-Aspartate/antagonists & inhibitors , Cholinesterase Inhibitors/chemistry , Cholinesterase Inhibitors/metabolism , Cholinesterase Inhibitors/therapeutic use , Chromatography, Liquid , Drug Stability , Drug Therapy, Combination , Humans , Mass Spectrometry , N-Methylaspartate/metabolism , Psychotropic Drugs/metabolism , Reproducibility of Results , Sensitivity and Specificity , Solid Phase ExtractionABSTRACT
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.
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OBJECTIVE: To investigate the relations between caffeine-derived metabolites (methylxanthines) and plasma lipids by use of population-based data from 2 European countries. METHODS: Families were randomly selected from the general population of northern Belgium (FLEMENGHO), from August 12, 1985, until November 22, 1990, and 3 Swiss cities (SKIPOGH), from November 25, 2009, through April 4, 2013. We measured plasma concentrations (FLEMENGHO, SKIPOGH) and 24-hour urinary excretions (SKIPOGH) of 4 methylxanthines-caffeine, paraxanthine, theobromine, and theophylline-using ultra-high-performance liquid chromatography-tandem mass spectrometry. We used enzymatic methods to estimate total cholesterol, high-density lipoprotein cholesterol, and triglyceride levels and the Friedewald equation for low-density lipoprotein cholesterol levels in plasma. We applied sex-specific mixed models to investigate associations between methylxanthines and plasma lipids, adjusting for major confounders. RESULTS: In both FLEMENGHO (N=1987; 1055 [53%] female participants) and SKIPOGH (N=990; 523 [53%] female participants), total cholesterol, low-density lipoprotein cholesterol, and triglyceride levels increased across quartiles of plasma caffeine, paraxanthine, and theophylline (total cholesterol levels by caffeine quartiles in FLEMENGHO, male participants: 5.01±0.06 mmol/L, 5.05±0.06 mmol/L, 5.27±0.06 mmol/L, 5.62±0.06 mmol/L; female participants: 5.24±0.06 mmol/L, 5.15±0.05 mmol/L, 5.25±0.05 mmol/L, 5.42±0.05 mmol/L). Similar results were observed using urinary methylxanthines in SKIPOGH (total cholesterol levels by caffeine quartiles, male participants: 4.54±0.08 mmol/L, 4.94±0.08 mmol/L, 4.87±0.08 mmol/L, 5.27±0.09 mmol/L; female participants: 5.12±0.07 mmol/L, 5.21±0.07 mmol/L, 5.28±0.05 mmol/L, 5.28±0.07 mmol/L). Furthermore, urinary caffeine and theophylline were positively associated with high-density lipoprotein cholesterol in SKIPOGH male participants. CONCLUSION: Plasma and urinary caffeine, paraxanthine, and theophylline were positively associated with plasma lipids, whereas the associations involving theobromine were less clear. We postulate that the positive association between caffeine intake and plasma lipids may be related to the sympathomimetic function of methylxanthines, mitigating the overall health-beneficial effect of caffeine intake.