Pharmacopsychiatry最新文献

Attention deficit-/hyperactivity disorder (ADHD) medications are commonly prescribed to children and adolescents, but therapeutic reference ranges have not been systematically evaluated yet. This study aimed to establish preliminary therapeutic reference ranges for methylphenidate (MPH), d-amphetamine (d-AMP), atomoxetine (ATX), and guanfacine (GFC), based on a systematic review of the existing relevant literature.Therapeutic reference ranges were calculated based on blood concentrations measured in responder children and adolescents with ADHD. Therapeutic ranges were determined both as mean values plus one standard deviation (SD) and using the 25^th/75^th IQRs. For MPH, a therapeutic reference range was calculated according to the mean maximum concentration (C_max)±SD (8.8±7.7 ng/mL) as 1.1-16.6 ng/mL and according to the 25^th/75^th IQR as 7.2-11.3 ng/mL. The mean d-AMP C_max concentration±SD was 31.9±15.2 ng/mL, resulting in a range of 16.6-47.1 ng/mL, and the calculated range according to IQR 25^th/75^th was 18.4-32.5 ng/mL. For ATX, mean maximum concentration at steady state (C_max,ss)±SD was 589.7±656.3 ng/mL, resulting in a range of 0.0-1245.9 ng/mL, and according to 25^th/75^th IQR, the range was calculated as 537.0-635.5 ng/mL. For GFC, only one study was eligible, with a mean blood concentration of 7.5 ng/mL in responders.The results provide preliminary recommendations that can serve as reference values for therapeutic drug monitoring in children and adolescents treated with MPH, AMP, ATX, and GFC. Further research is needed to validate or refine the proposed therapeutic ranges.

Acute stress, potentially mediated by the stress-induced release of cortisol, affects decision-making processes. In the brain, cortisol activates two different types of receptors: the glucocorticoid receptor (GR) and the mineralocorticoid receptor (MR), each with different functional profiles. While previous studies suggest specific effects for MR and GR, the role of both receptor types in decision-making is insufficiently investigated.In this study, stress-induced effects of cortisol on decision-making processes were investigated after pharmacological receptor blockade of the MR (spironolactone, 300 mg) or the GR (mifepristone, 600 mg) in 318 healthy men (M=25.42, SD=5.01). After single-dose administration, participants were subjected to a social-evaluative stress task (Trier Social Stress Test, TSST), which reliably activates the HPA-axis, or a non-stressful control task (pTSST). Participants were randomly assigned to one study group: pTSST-placebo, TSST-placebo, TSST-spironolactone, or TSST-mifepristone. Subsequently, participants completed the Iowa Gambling Task (IGT) as an outcome measure. A mediation analysis was conducted to investigate direct effects of experimental manipulation in this study and indirect effects mediated by cortisol levels. The evidence for stress effects on decisions under ambiguity was positive.While stressed participants exhibited higher risk-taking, this was not the case in the TSST-spironolactone group, although this group had the most pronounced cortisol stress response. Thus, cortisol did not mediate this effect.The stress effect on decision-making was attenuated when MR was blocked. This corresponds to previous findings of increased risk-taking after MR activation and highlights a functional differentiation of both receptors for this domain.

Bipolar depression is often difficult to treat and needs a specific therapeutic approach. This systematic review and meta-analysis aimed to evaluate the efficacy of lumateperone to be inclusive of more recently published studies with this agent in depressive episodes of bipolar disorder. Three meta-analyses were conducted to determine whether the mean Montgomery-Asberg Depression Rating Scale (MADRS) values in the placebo groups differ significantly from the mean MADRS scale values in the group receiving lumateperone 42 mg and whether the mean of Clinical Global Impression Bipolar Version - Severity Scale (CGI-BP-S) - (depression subscore and overall bipolar illness) values in the placebo groups differ significantly from the mean CGI-BP-S scale values in the group receiving lumateperone 42 mg. The meta-analysis showed a statistically significant difference between patients treated with lumateperone 42 mg and those treated with placebo for the MADRS and CGI subscores. The clinical profile of lumateperone indicates that it is a established and highly efficacious treatment option for major depressive episodes associated with bipolar disorder.

Schizophrenia spectrum disorders (SSD) are debilitating psychiatric illnesses that require extensive pharmacologic, cognitive, and functional management. SSD patients are often prescribed different medications, most commonly antipsychotics, which bear numerous side effects. Recently, accumulating evidence has shown epigenetic aging changes in SSD. However, the effects of antipsychotic medications on this phenomenon remain unexplored.We investigated whether antipsychotic medications are associated with epigenetic age acceleration (EAA) in 153 SSD patients. EAA was estimated using six different epigenetic clocks, based on the methylation patterns of peripheral blood cells.The analysis revealed some evidence of aging deceleration based on the Hannum DNAm Age in individuals on antipsychotic polypharmacy, relative to their monopharmacy counterparts (mean difference=-0.59 years, p=0.0109), which was only nearing significance after adjusting for multiple comparisons (p_adjusted=0.0654). In sex-specific analysis, only females displayed significantly decelerated epigenetic aging in the polypharmacy group in three of the six clocks. Furthermore, we observed no dose-dependent effects of antipsychotics on EAA in all clocks using three dose standardization methods (daily defined dose, chlorpromazine equivalents, and percent of maximum allowed dose).The findings suggest that antipsychotic treatment may modulate biological aging in SSD; however, this effect is not dose-dependent. Moreover, there appears to be an interplay between sex, polypharmacy, and epigenetic aging. These findings contribute to our understanding of the biological effects of antipsychotic treatment, and future research in this area is key for weighing the benefits and the risks of pharmacological management of SSD.

Lithium remains a first-line mood stabilizer for bipolar disorder; yet, only a subset of patients achieves symptomatic remission. Early prediction of treatment response could guide personalized management. In this study, we leveraged machine learning algorithms to predict 3-month remission, defined as a Montgomery-Åsberg Depression Rating Scale score≤10, in 593 patients with bipolar disorder initiating lithium.In this retrospective cohort, baseline sociodemographic, clinical and laboratory data as well as concomitant medication usage were collected. Montgomery Åsberg Depression Rating Scale and Mania Rating Scale were administered at baseline and 3 months. Data were preprocessed (missing imputation and normalization) and then split into 80% training and 20% test sets. We evaluated various machine learning techniques such as random forest, XGBoost, neural network and support vector machines with five-fold cross validation. Performance metrics included area under the receiver operating characteristic curve and accuracy. The mean age was 44±16.9 years and 53% of participants were females. The remission rate at 3 months was 44%. The random forest model (augmented by polynomial transformations) performed best (area under the receiver operating characteristic curve=0.76 and accuracy=0.64) improving by 10% of the standard logistic model. Key predictors included the baseline Montgomery Åsberg Depression Rating Scale and Mania Rating Scale, creatinine, thyroid-stimulating hormone levels, body mass index and age. Machine learning, particularly gradient boosted trees, can help to predict the 3-month remission in bipolar disorder patients who start lithium therapy. Incorporating clinical and laboratory features enhances the early identification of likely responders, enabling personalized treatment strategies.

Bipolar disorder is a chronic psychiatric condition that requires long-term treatment. Lithium remains the gold standard for mood stabilization; yet, its therapeutic response is highly variable and unpredictable due to the lack of reliable biomarkers. As lithium may exert its effect through interactions with neuronal membranes, particularly their lipid composition, red blood cell membranes have been proposed as a peripheral model to investigate this relationship. We conducted a monocentric, cross-sectional study involving 30 patients with bipolar disorder receiving a stable dose of lithium. Clinical and sociodemographic characteristics were assessed alongside plasma lithium and red blood cell lithium levels. Fatty acid profiles of red blood cell membranes were analyzed. The cohort was divided into three groups based on the red blood cell lithium/plasma lithium ratio to explore potential associations with fatty acid profiles. Additionally, an unsupervised clustering approach was used to identify patient subgroups based on fatty acid profiles and clinical characteristics, and their lithium levels were compared. No significant differences in fatty acid composition were found across the red blood cell lithium/plasma lithium ratio groups. However, older age was associated with higher red blood cell lithium/plasma lithium ratios. No clear association was found between fatty acid concentrations and intracellular lithium. Cluster analysis based on clinical data revealed two clinical subgroups, with the less severe group exhibiting significantly higher plasma lithium and higher omega-6 fatty acid levels. While no direct relationship was observed between fatty acid composition and lithium distribution, this study suggests that the lithium's action may involve other membrane components. Future longitudinal studies with larger samples and advanced lipidomic profiling are needed to identify potential composite biomarkers of lithium response.

Polypharmacy has an important role in psychiatry, as the kidney function can be affected by medication. Risperidone is metabolized hepatically to 9-hydroxyrisperidone and excreted renally. Here, we study how serum concentrations of risperidone, 9-hydroxyrisperidone and active moiety (risperidone+9-hydroxyrisperidone) are related to impairment of kidney function and potentially interacting comedications that affect renal functions ((1) nonsteroidal anti-inflammatory drugs, (2) angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, and (3) diuretics). In this retrospective study, data from risperidone-treated inpatients (2015-2020, n=517) at the University Hospital of Würzburg were analyzed. Routine therapeutic drug monitoring was performed at trough levels at a steady-state. Groups were compared by means of the Kruskal-Wallis test. To correct for confounding parameters, additional multiple linear regression modeling was performed. After correction for age, sex, body mass index and the respective interaction between the estimated glomerular filtration rate and the number of interacting drugs, the dose-corrected serum concentration of 9-hydroxyrisperidone and the active moiety of risperidone were positively associated with the number of interacting drugs. The active moiety was negatively associated with the estimated glomerular filtration rate. Our data suggest that renal functions and the number of interacting drugs influence the pharmacokinetics of risperidone. Previous studies often explained the increasing serum concentration with age as a surrogate, whereas our results suggest that the kidney function and comedication affecting kidney function might be more relevant. When prescribing risperidone, especially in patients with renal impairment or co-medicated with interacting drugs, we suggest to start with lower starting doses and recommend monitoring serum concentrations to prevent overdosing.

Ketamine and esketamine (ESK) offer new treatment options for resistant depression. Unlike traditional antidepressants, they can be used in combination with non-selective monoamine oxidase inhibitors (NS-MAOI) without the risk of serotonergic syndrome. However, potential sympathomimetic synergy may lead to elevated blood pressure (BP). This series investigates whether cardiovascular parameters (heart rate, systolic [SP], and diastolic [DP] pressures) increase during ESK sessions and whether the ESK+NS-MAOI combination is associated with BP elevations.We collected cardiovascular parameters for ESK sessions conducted between 2018 and 2022. These parameters were measured at baseline and every 30 min for 2 h. Patients were categorized into two non-equivalent groups: those receiving ESK alone and those receiving ESK+NS-MAOI. A Bayesian random model was used to estimate the evolution of these parameters, while a Bayesian hierarchical model assessed factors contributing to BP elevation.ESK sessions (n=193), of which 116 involved NS-MAOI, were performed in 13 patients. SP, DP, and heart rate showed peak increases during sessions, but these changes were not clinically significant (SP+8.68 mmHg, DP+6.57 mmHg, and heart rate+3.5 bpm). No significant differences were found between the ESK-alone and ESK+NS-MAOI groups. The combination was not identified as a factor linked to BP elevations.These findings align with previous research on ketamine derivatives and suggest minimal peripheric sympathomimetic synergy with NS-MAOI. Bayesian models were used to account for biases intrinsically related to these ecological data and provide a foundation for future open adversarial collaborations. Registration NCT05530668.

Second-generation antipsychotic drugs, such as olanzapine, have been associated with metabolic side effects including significant weight gain. Recent evidence suggests that this adverse effect may be attenuated by metformin.Male Wistar rats were chronically treated with olanzapine, together with or without metformin, for 7 and 14 weeks. Feeding behavior, food intake, and weight gain were recorded, as well as plasma leptin and triglyceride levels were measured. The expression of hypothalamic candidate genes, Pomc and Npy, involved in appetite and energy balance expressions' was assessed by quantitative real-time polymerase chain reaction.Olanzapine alone caused significant body weight gain, and the co-administration of metformin for 14 weeks lowered body weight and food intake compared with both the 7-week and control groups. Plasma triglyceride levels did not differ among groups. Leptin levels were significantly higher in the olanzapine-only group and were lower in both metformin-olanzapine groups, more promising in the early co-treatment with metformin. Compared to the control group, the hypothalamus of the olanzapine treatment group exhibited downregulated Pomc expression and upregulated Npy expression.Early co-treatment with metformin significantly mitigated olanzapine-induced weight gain and food intake, demonstrating its potential in preventing metabolic side effects when initiated at the beginning of antipsychotic therapy.