The impact of weight gain on antipsychotic nonadherence or discontinuation: A systematic review and meta-analysis.

BACKGROUND: Nonadherence/discontinuation of antipsychotic (AP) medications represents an important clinical issue in patients across psychiatric disorders, including schizophrenia spectrum disorders (SSDs). While antipsychotic-induced weight gain (AIWG) is a reported contributor to nonadherence, a systematic review of the association between AIWG and medication nonadherence/discontinuation has not been explored previously. METHOD: A systematic search was conducted in MEDLINE, EMBASE, PsychINFO, CINAHL, and CENTRAL databases, among others, to help identify all studies which explored adherence, study dropouts, AP switching and/or discontinuations attributable to AIWG among individuals with severe mental illness. A meta-analysis was also completed where applicable. RESULTS: We identified two categories of studies for the meta-analysis. Category 1 included three studies, which compared measures of AP adherence or discontinuation across BMI classes/degrees of self-reported weight gain. When compared to normal weight individuals receiving APs or those who did not report AIWG, individuals who were either overweight or obese or reported weight gain in relation to AP use had an increased odds of AP nonadherence (OR 2.37; 95% CI 1.51-3.73; p = 0.0002). Category 2 had 14 studies which compared measures of discontinuation related to weight gain reported as an adverse effect across different APs. Olanzapine was associated with a 3.32 times (95% CI 2.32-4.74; p < 0.00001) increased likelihood of nonadherence or discontinuation when compared to other APs with lower weight gain liabilities. Similarly, APs with moderate weight gain liability (paliperidone, risperidone, and quetiapine) increased the odds of nonadherence or discontinuation by 2.25 (95% CI 1.31-3.87; p = 0.003) when compared to APs considered to have lower weight gain liability (i.e. haloperidol and aripiprazole). The qualitative summary also confirmed these findings. CONCLUSION: This review and meta-analysis suggests that AIWG influences medication nonadherence/discontinuation, whereby APs with higher weight gain liability are associated with nonadherence/discontinuation. Additional studies are needed to confirm these findings.

Antipsychotic-Induced Weight Gain in Severe Mental Illness: Risk Factors and Special Considerations.

PURPOSE OF REVIEW: Weight gain is a disconcerting issue experienced by patients treated with antipsychotics (APs). This review summarizes current knowledge on the prevalence, etiology, and risk factors for antipsychotic-induced weight gain (AIWG), and evidence for interventions, including special considerations. RECENT FINDINGS: Predisposing risk factors for AIWG include lack of prior AP exposure, sex, and age. AP dose and duration of exposure are additional treatment-related factors that may contribute to this issue. Among current approaches to target AIWG, metformin has the most evidence to support its use, and this is increasingly reflected in clinical guidelines. While lifestyle approaches are recommended, cost-effectiveness and scalability represent limitations. More research is needed to identify newer treatment options and inform clinical recommendations for AIWG. Concerns around scope of practice in psychiatry to address AIWG and related comorbidities will require enhanced training opportunities and interdisciplinary collaborations, as well as updated position statements/practice guidelines emphasizing prevention.

Protocol for the hyperinsulinemic euglycemic clamp to measure glucose kinetics in rats.

In rats, cannulation of the jugular vein and the carotid artery precedes the use of the hyperinsulinemic euglycemic clamp to determine insulin sensitivity in vivo. Here, we present a vascular surgery protocol to allow the infusion of substances via the vein and the collection of blood samples from the artery on the day of the hyperinsulinemic euglycemic clamp. We describe steps for preparing for and performing catheterization surgery. We then detail procedures for clamp preparation and its use. For complete details on the use and execution of this protocol, please refer to Pereira et al.1,2,3.

Peripheral Lipid Signatures, Metabolic Dysfunction, and Pathophysiology in Schizophrenia Spectrum Disorders.

Metabolic dysfunction is commonly observed in schizophrenia spectrum disorders (SSDs). The causes of metabolic comorbidity in SSDs are complex and include intrinsic or biological factors linked to the disorder, which are compounded by antipsychotic (AP) medications. The exact mechanisms underlying SSD pathophysiology and AP-induced metabolic dysfunction are unknown, but dysregulated lipid metabolism may play a role. Lipidomics, which detects lipid metabolites in a biological sample, represents an analytical tool to examine lipid metabolism. This systematic review aims to determine peripheral lipid signatures that are dysregulated among individuals with SSDs (1) with minimal exposure to APs and (2) during AP treatment. To accomplish this goal, we searched MEDLINE, Embase, and PsychINFO databases in February 2024 to identify all full-text articles written in English where the authors conducted lipidomics in SSDs. Lipid signatures reported to significantly differ in SSDs compared to controls or in relation to AP treatment and the direction of dysregulation were extracted as outcomes. We identified 46 studies that met our inclusion criteria. Most of the lipid metabolites that significantly differed in minimally AP-treated patients vs. controls comprised glycerophospholipids, which were mostly downregulated. In the AP-treated group vs. controls, the significantly different metabolites were primarily fatty acyls, which were dysregulated in conflicting directions between studies. In the pre-to-post AP-treated patients, the most impacted metabolites were glycerophospholipids and fatty acyls, which were found to be primarily upregulated and conflicting, respectively. These lipid metabolites may contribute to SSD pathophysiology and metabolic dysfunction through various mechanisms, including the modulation of inflammation, cellular membrane permeability, and metabolic signaling pathways.