Antipsychotic-Induced Alterations in Lipid Turnover

Pereira, Sandra; Au, Emily; Agarwal, Sri Mahavir; Wright, David C.; Hahn, Margaret

doi:10.1210/endocr/bqad025

Cited by 7 publications

(2 citation statements)

References 158 publications

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“…Immunoglobulin-like proteins and apolipoproteins were identified among the drug-induced DEPs from both EV models. Since many antipsychotics, including clozapine and olanzapine, are associated with dysregulated lipid metabolism, weight gain, and metabolic syndrome (Procyshyn et al, 2007;Chiang et al, 2008;Nimura et al, 2015;Pereira et al, 2023;Scheen, 2023), these are likely true observations, but whether these apolipoproteins are specifically enriched in EVs or coprecipitated lipid particles remains to be determined (von Zychlinski and Kleffmann, 2015;Simonsen, 2017;Brennan et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Involvement of Extracellular Vesicles in the Proinflammatory Response to Clozapine: Implications for Clozapine-Induced Agranulocytosis

Sernoskie,

Bonneil,

Thibault

et al. 2024

J Pharmacol Exp Ther

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Most idiosyncratic drug reactions (IDRs) appear to be immune-mediated, but mechanistic events preceding severe reaction onset remain poorly defined. Damage-associated molecular patterns (DAMPs) may contribute to both innate and adaptive immune phases of IDRs, and changes in extracellular vesicle (EV) cargo have been detected post-exposure to several IDRassociated drugs. To explore the hypothesis that EVs are also a source of DAMPs in the induction of the immune response preceding drug-induced agranulocytosis, the proteome and immunogenicity of clozapine-(agranulocytosis-associated drug) and olanzapine-(nonagranulocytosis-associated drug) exposed EVs were compared in two preclinical models: THP-1 macrophages and Sprague Dawley rats. Compared to olanzapine, clozapine induced a greater increase in the concentration of EVs enriched from both cell culture media and rat serum.Moreover, treatment of drug-naïve THP-1 cells with clozapine-exposed EVs induced an inflammasome-dependent response, supporting a potential role for EVs in immune activation.Proteomic and bioinformatic analyses demonstrated an increased number of differentially expressed proteins with clozapine that were enriched in pathways related to inflammation, myeloid cell chemotaxis, wounding, transforming growth factor (TGF)-β signaling, and negative regulation of stimuli response. These data indicate that, although clozapine and olanzapine exposure both alter the protein cargo of EVs, clozapine-exposed EVs carry mediators that exhibit significantly greater immunogenicity. Ultimately, this supports the working hypothesis that drugs associated with a risk of IDRs induce cell stress, release of proinflammatory mediators, and early immune activation that precedes severe reaction onset. Further studies characterizing EVs may elucidate biomarkers that predict IDR risk during development of drug candidates.

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Section: Discussionmentioning

confidence: 99%

Involvement of Extracellular Vesicles in the Proinflammatory Response to Clozapine: Implications for Clozapine-Induced Agranulocytosis

Sernoskie,

Bonneil,

Thibault

et al. 2024

J Pharmacol Exp Ther

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“…Changes in lipid profiles have not only been cited as a side effect but also an indicator of antipsychotic efficacy, and it has been hypothesized that changes in lipid metabolism are among possible pathogenic mechanisms of schizophrenia [66,67]. Yet, the mechanism by which antipsychotics induce lipid alterations is still debated and includes influencing lipid biosynthesis, metabolism, trafficking, and signaling, in addition to altered gene activity [68][69][70][71]. The findings in the untargeted studies included here suggest that antipsychotics have widespread effects on various lipid classes within the body.…”

Section: Findings In Untargeted Lipidomic Studiesmentioning

confidence: 99%

Metabolomics, Lipidomics, and Antipsychotics: A Systematic Review

Burghardt,

Kajy,

Ward

et al. 2023

Biomedicines

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Antipsychotics are an important pharmacotherapy option for the treatment of many mental illnesses. Unfortunately, selecting antipsychotics is often a trial-and-error process due to a lack of understanding as to which medications an individual patient will find most effective and best tolerated. Metabolomics, or the study of small molecules in a biosample, is an increasingly used omics platform that has the potential to identify biomarkers for medication efficacy and toxicity. This systematic review was conducted to identify metabolites and metabolomic pathways associated with antipsychotic use in humans. Ultimately, 42 studies were identified for inclusion in this review, with all but three studies being performed in blood sources such as plasma or serum. A total of 14 metabolite classes and 12 lipid classes were assessed across studies. Although the studies were highly heterogeneous in approach and mixed in their findings, increases in phosphatidylcholines, decreases in carboxylic acids, and decreases in acylcarnitines were most consistently noted as perturbed in patients exposed to antipsychotics. Furthermore, for the targeted metabolomic and lipidomic studies, seven metabolites and three lipid species had findings that were replicated. The most consistent finding for targeted studies was an identification of a decrease in aspartate with antipsychotic treatment. Studies varied in depth of detail provided for their study participants and in study design. For example, in some cases, there was a lack of detail on specific antipsychotics used or concomitant medications, and the depth of detail on sample handling and analysis varied widely. The conclusions here demonstrate that there is a large foundation of metabolomic work with antipsychotics that requires more complete reporting so that an objective synthesis such as a meta-analysis can take place. This will then allow for validation and clinical application of the most robust findings to move the field forward. Future studies should be carefully controlled to take advantage of the sensitivity of metabolomics while limiting potential confounders that may result from participant heterogeneity and varied analysis approaches.

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