Variability of glucose, insulin, and lipid disturbances in first-episode psychosis: a meta-analysis

Comparative physiological effects of antipsychotic drugs in children and young people: a network meta-analysis

BACKGROUND

The degree of physiological responses to individual antipsychotic drugs is unclear in children and adolescents. With network meta-analysis, we aimed to investigate the effects of various antipsychotic medications on physiological variables in children and adolescents with neuropsychiatric and neurodevelopmental conditions.

METHODS

For this network meta-analysis, we searched Medline, EMBASE, PsycINFO, Web of Science, and Scopus from database inception until Dec 22, 2023, and included randomised controlled trials comparing antipsychotics with placebo in children or adolescents younger than 18 years with any neuropsychiatric and neurodevelopmental condition. Primary outcomes were mean change from baseline to end of acute treatment in bodyweight, BMI, fasting glucose, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, prolactin, heart rate, systolic blood pressure (SBP), and QT interval corrected for heart rate (QTc) for patients receiving either active treatment or placebo. For multigroup trials reporting several doses, we calculated a summary value for each physiological variable for all doses. After transitivity assessment, we fitted frequentist random-effects network meta-analyses for all comparisons in the network. A Kilim plot was used to summarise the results for all treatments and outcomes, providing information regarding the strength of the statistical evidence of treatment effects, using p values. Network heterogeneity was assessed with τ, risk of bias of individual trials was assessed with the Cochrane Collaboration's Tool for Assessing Risk of Bias, and the credibility of findings from each network meta-analysis was assessed with the Confidence in Network Meta-Analysis (CINEMA) app. This study is registered on PROSPERO (CRD42021274393).

FINDINGS

Of 6676 studies screened, 47 randomised controlled trials were included, which included 6500 children (mean age 13·29 years, SD 2·14) who received treatment for a median of 7 weeks (IQR 6-8) with either placebo (n=2134) or one of aripiprazole, asenapine, blonanserin, clozapine, haloperidol, lurasidone, molindone, olanzapine, paliperidone, pimozide, quetiapine, risperidone, or ziprasidone (n=4366). Mean differences for bodyweight change gain compared with placebo ranged from -2·00 kg (95% CI -3·61 to -0·39) with molindone to 5·60 kg (0·27 to 10·94) with haloperidol; BMI -0·70 kg/m2 (-1·21 to -0·19) with molindone to 2·03 kg/m2 (0·51 to 3·55) with quetiapine; total cholesterol -0·04 mmol/L (-0·39 to 0·31) with blonanserin to 0·35 mmol/L (0·17 to 0·53) with quetiapine; LDL cholesterol -0·12 mmol/L (-0·31 to 0·07) with risperidone or paliperidone to 0·17 mmol/L (-0·06 to 0·40) with olanzapine; HDL cholesterol 0·05 mmol/L (-0·19 to 0·30) with quetiapine to 0·48 mmol/L (0·18 to 0·78) with risperidone or paliperidone; triglycerides -0·03 mmol/L (-0·12 to 0·06) with lurasidone to 0·29 mmol/L (0·14 to 0·44) with olanzapine; fasting glucose from -0·09 mmol/L (-1·45 to 1·28) with blonanserin to 0·74 mmol/L (0·04 to 1·43) with quetiapine; prolactin from -2·83 ng/mL (-8·42 to 2·75) with aripiprazole to 26·40 ng/mL (21·13 to 31·67) with risperidone or paliperidone; heart rate from -0·20 bpm (-8·11 to 7·71) with ziprasidone to 12·42 bpm (3·83 to 21·01) with quetiapine; SBP from -3·40 mm Hg (-6·25 to -0·55) with ziprasidone to 10·04 mm Hg (5·56 to 14·51) with quetiapine; QTc from -0·61 ms (-1·47 to 0·26) with pimozide to 0·30 ms (-0·05 to 0·65) with ziprasidone.

INTERPRETATION

Children and adolescents show varied but clinically significant physiological responses to individual antipsychotic drugs. Treatment guidelines for children and adolescents with a range of neuropsychiatric and neurodevelopmental conditions should be updated to reflect each antipsychotic drug's distinct profile for associated metabolic changes, alterations in prolactin, and haemodynamic alterations.

FUNDING

UK Academy of Medical Sciences, Brain and Behaviour Research Foundation, UK National Institute of Health Research, Maudsley Charity, the Wellcome Trust, Medical Research Council, National Institute of Health and Care Research Biomedical Centre at King's College London and South London and Maudsley NHS Foundation Trust, the Italian Ministry of University and Research, the Italian National Recovery and Resilience Plan, and Swiss National Science Foundation.

TAAR1 agonist ulotaront delays gastric emptying of solids in patients with schizophrenia and concurrent metabolic syndrome with prediabetes

BACKGROUND

Metabolic syndrome (MetS), which can be induced or exacerbated by the current class of antipsychotic drugs, is highly prevalent in patients with schizophrenia and presents significant challenges to lifetime disease management. Supported by initial clinical results, trace amine-associated receptor 1 (TAAR1) agonists have emerged as potential novel treatments for schizophrenia. Notably, non-clinical studies have also shown weight-lowering and glucoregulatory effects of TAAR1 agonists, including the investigational agent ulotaront. However, the translatability of these findings to humans has not been adequately assessed. Given that delayed gastric emptying (GE) was identified as a potential mechanism contributing to the metabolic benefits of TAAR1 agonists in rodents, the aim of this study was to evaluate the effect of ulotaront on GE in patients with schizophrenia and concurrent MetS with prediabetes.

METHODS

Patients with schizophrenia were randomized to receive a single oral dose of ulotaront (150 mg) and their previous antipsychotic (PA) in an open-label, crossover, two-sequence design (NCT05402111). Eligible participants fulfilled at least three of five MetS criteria and had prediabetes defined by elevated glycated haemoglobin (5.7-6.4%) and/or fasting homeostatic model assessment of insulin resistance (i.e. ≥2.22). Following an overnight fast and 4 h post-dose, participants ingested a 99mTc-sulphur colloid radiolabelled egg meal (320 kcal, 30% fat). GE was measured by scintigraphy over 4 h. Endpoints included GE of solids half-time (T1/2) and percentage gastric retention at 1, 2 and 4 h.

RESULTS

Thirty-one adults were randomized and 27 completed the study. Ulotaront significantly delayed GE of solids [median GE T1/2 ulotaront at 139 min (119, 182) vs. the participant's PA of 124 min (109, 132), p = .006]. A significant increase in gastric retention was seen in the ulotaront versus the PA group at 1 h (80% vs. 75%, p = .015), 2 h (61% vs. 50%, p = .023) and 4 h (17% vs. 7%, p = .002) post-meal.

CONCLUSION

Ulotaront delayed the GE of solids in patients with schizophrenia and concurrent MetS with prediabetes. Additional studies are needed to assess whether treatment with TAAR1 agonists is associated with weight loss and glucoregulatory improvement.

TAAR1 agonists improve glycemic control, reduce body weight and modulate neurocircuits governing energy balance and feeding

OBJECTIVE

Metabolic Syndrome, which can be induced or exacerbated by current antipsychotic drugs (APDs), is highly prevalent in schizophrenia patients. Recent preclinical and clinical evidence suggest that agonists at trace amine-associated receptor 1 (TAAR1) have potential as a new treatment option for schizophrenia. Intriguingly, preclinical tudies have also identified TAAR1 as a novel regulator of metabolic control. Here we evaluated the effects of three TAAR1 agonists, including the clinical development candidate ulotaront, on body weight, metabolic parameters and modulation of neurocircuits implicated in homeostatic and hedonic feeding.

METHODS

Effects of TAAR1 agonists (ulotaront, RO5166017 and/or RO5263397) on body weight, food intake and/or metabolic parameters were investigated in rats fed a high-fat diet (HFD) and in a mouse model of diet-induced obesity (DIO). Body weight effects were also determined in a rat and mouse model of olanzapine-, and corticosterone-induced body weight gain, respectively. Glucose tolerance was assessed in lean and diabetic db/db mice and fasting plasma glucose and insulin examined in DIO mice. Effects on gastric emptying were evaluated in lean mice and rats. Drug-induced neurocircuit modulation was evaluated in mice using whole-brain imaging of c-fos protein expression.

RESULTS

TAAR1 agonists improved oral glucose tolerance by inhibiting gastric emptying. Sub-chronic administration of ulotaront in rats fed a HFD produced a dose-dependent reduction in body weight, food intake and liver triglycerides compared to vehicle controls. In addition, a more rapid reversal of olanzapine-induced weight gain and food intake was observed in HFD rats switched to ulotaront or RO5263397 treatment compared to those switched to vehicle. Chronic ulotaront administration also reduced body weight and improved glycemic control in DIO mice, and normalized corticosterone-induced body weight gain in mice. TAAR1 activation increased neuronal activity in discrete homeostatic and hedonic feeding centers located in the dorsal vagal complex and hypothalamus with concurrent activation of several limbic structures.

CONCLUSION

The current data demonstrate that TAAR1 agonists, as a class, not only lack APD-induced metabolic liabilities but can reduce body weight and improve glycemic control in rodent models. The underlying mechanisms likely include TAAR1-mediated peripheral effects on glucose homeostasis and gastric emptying as well as central regulation of energy balance and food intake.

Risk factors for abnormal glucose metabolism during antipsychotic treatment: A prospective cohort study

Antipsychotic medications increase the risk of abnormal glucose metabolism. However, in clinical practice, it is difficult to predict this risk because it is affected by medication-related and background factors. This study aimed to identify the risk factors for abnormal glucose metabolism during antipsychotic treatment. We conducted a multicenter, prospective, cohort study in patients with schizophrenia, schizoaffective disorder, or bipolar disorder. Of these patients, those with prediabetes or possible diabetes were excluded. Finally, 706 patients were included in the analysis. The hazard ratio (HR) for each factor was calculated for events of progression to hyperglycemia using time-dependent Cox regression analysis stratified according to facility type and adjusted for available background and drug-related factors. Treatments with olanzapine (HR = 2.06, 95% confidence interval [CI] = 1.05-4.05), clozapine (HR = 4.25, 95% CI = 1.56-11.60), and chlorpromazine (HR = 4.48, 95% CI = 1.21-16.57), overweight and obesity (HR = 1.57, 95% CI = 1.02-2.41), and hypertriglyceridemia (HR = 1.72, 95% CI = 1.02-2.88) were associated with a significantly higher occurrence of hyperglycemic progression. The number and daily dose of antipsychotics were not associated with their occurrence. Our study demonstrated that more careful monitoring is necessary during olanzapine, clozapine, and chlorpromazine treatment because of the higher occurrence of abnormalities in glucose metabolism. Furthermore, patients with obesity or hypertriglyceridemia warrant monitoring for the occurrence of abnormal glucose metabolism, regardless of the type of antipsychotic medication.

Prolactin and morning cortisol concentrations in antipsychotic naïve first episode psychosis: A systematic review and meta-analysis

IMPORTANCE

Alterations in prolactin and cortisol levels have been reported in antipsychotic naïve patients with first episode psychosis (FEP). However, it has been studied in very small samples, and inter-group variability has never been studied before.

OBJECTIVE

To provide estimates of standardized mean differences (SMD) and inter-group variability for prolactin, cortisol awakening response (CAR) and morning cortisol concentrations in antipsychotic naïve FEP (AN-FEP) patients and healthy controls (HC).

DATA SOURCES

BIOSIS, KCI, MEDLINE, Russian Science Citation Index, SciELO, Cochrane, PsycINFO, Web of Science were searched from inception to February 28, 2022.

STUDY SELECTION

Peer-reviewed cohort studies that reported on prolactin or cortisol blood concentrations in AN- FEP patients and HC were included.

DATA EXTRACTION AND SYNTHESIS

Study characteristics, means and standard deviations (SD) were extracted from each article. Inter group differences in magnitude of effect were estimated using Hedges g. Inter-group variability was estimated with the coefficient of variation ratio (CVR). In both cases estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using meta-regression. PRISMA guideline was followed (No. CRD42022303555).

MAIN OUTCOMES AND MEASURES

Prolactin, CAR and morning cortisol blood concentrations in AN-FEP group in relation to HC group.

RESULTS

Fourteen studies for prolactin (N = 761 for AN-FEP group, N = 687 for HC group) and twelve studies for morning cortisol (N = 434 for AN-FEP group, N = 528 for HC group) were included. No studies were found in CAR in AN-FEP patients. Mean SMD for prolactin blood concentration was 0.88 (95% CI 0.57, 1.20) for male and 0.56 (95% CI 0.26, 0.87) for female. As a group, AN-FEP presented greater inter-group variability for prolactin levels than HC (CVR=1.28, 95% CI 1.02, 1.62). SMD for morning cortisol concentrations was non-significant: 0.34 (95% CI -0.01, 0.69) and no inter-group variability significant differences were detected: CVR= 1.05 (95% CI 0.91, 1.20). Meta-regression analyses for age and quality were non-significant. Funnel plots did not suggest a publication bias.

CONCLUSIONS AND RELEVANCE

Increased prolactin levels were found in AN-FEP patients. A greater inter-group variability in the AN-FEP group suggests the existence of patient subgroups with different prolactin levels. No significant abnormalities were found in morning cortisol levels. Further research is needed to clarify whether prolactin concentrations could be used as an illness biomarker.

Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study

BACKGROUND

Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations.

METHODS

For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression.

FINDINGS

Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk scores for schizophrenia and principal component 1 were negatively associated (β=-0·01 [SE 0·003]; p=0·017). Similar to the principal component analysis results, for individual cardiac phenotypes, we observed negative associations between polygenic risk scores for schizophrenia and indexed right ventricular end-systolic volume (β=-0·14 [0·04]; p=0·0013, pFDR=0·015), indexed right ventricular end-diastolic volume (β=-0·17 [0·08]); p=0·025; pFDR=0·082), and absolute longitudinal peak diastolic strain rates (β=-0·01 [0·003]; p=0·0024, pFDR=0·015), and a positive association between polygenic risk scores for schizophrenia and right ventricular ejection fraction (β=0·09 [0·03]; p=0·0041, pFDR=0·015). Models examining the transforming growth factor-β (TGF-β)-specific and acute inflammation-specific polygenic risk scores for schizophrenia found significant associations with the first five principal components (F=2·62, p=0·022; F=2·54, p=0·026). Using linkage disequilibrium score regression, we observed genetic overlap with schizophrenia for right ventricular end-systolic volume and right ventricular ejection fraction (p=0·0090, p=0·0077).

INTERPRETATION

High polygenic risk scores for schizophrenia are associated with decreased cardiac volumes, increased ejection fractions, and decreased absolute peak diastolic strain rates. TGF-β and inflammatory pathways might be implicated, and there is evidence of genetic overlap for some cardiac phenotypes. Reduced absolute peak diastolic strain rates indicate increased myocardial stiffness and diastolic dysfunction, which increases risk of cardiac disease. Thus, genetic risk for schizophrenia is associated with cardiac structural changes that can worsen cardiac outcomes. Further work is required to determine whether these associations are specific to schizophrenia or are also seen in other psychiatric conditions.

FUNDING

National Institute for Health Research, Maudsley Charity, Wellcome Trust, Medical Research Council, Academy of Medical Sciences, Edmond J Safra Foundation, British Heart Foundation.

Brain Lipids and Lipid Droplet Dysregulation in Alzheimer's Disease and Neuropsychiatric Disorders

Background

Lipids are essential components of the structure and for the function of brain cells. The intricate balance of lipids, including phospholipids, glycolipids, cholesterol, cholesterol ester, and triglycerides, is crucial for maintaining normal brain function. The roles of lipids and lipid droplets and their relevance to neurodegenerative and neuropsychiatric disorders (NPDs) remain largely unknown.

Summary

Here, we reviewed the basic role of lipid components as well as a specific lipid organelle, lipid droplets, in brain function, highlighting the potential impact of altered lipid metabolism in the pathogenesis of Alzheimer's disease (AD) and NDPs.

Key Messages

Brain lipid dysregulation plays a pivotal role in the pathogenesis and progression of neurodegenerative and NPDs including AD and schizophrenia. Understanding the cell type-specific mechanisms of lipid dysregulation in these diseases is crucial for identifying better diagnostic biomarkers and for developing therapeutic strategies aiming at restoring lipid homeostasis.