Elucidating of the metabolic impact of risperidone on brain microvascular endothelial cells using untargeted metabolomics-based LC-MS.

Risperidone is useful for the treatment of schizophrenia symptoms; however, it also has side effects, and an overdose can be harmful. The metabolic effects of risperidone at high therapeutic doses and its metabolites have not been elucidated. Endogenous cellular metabolites may be comprehensively analyzed using untargeted metabolomics-based liquid chromatography-mass spectrometry (LC-MS), which can reveal changes in cell regulation and metabolic pathways. By identifying the metabolites and pathway changes using a nontargeted metabolomics-based LC-MS approach, we aimed to shed light on the potential toxicological effects of high-dose risperidone on brain microvascular endothelial cells (MVECs) associated with the human blood brain barrier. A total of 42 metabolites were selected as significant putative metabolites of the toxicological response of high-dose risperidone in MVECs. Six highly correlated pathways were identified, including those involving diacylglycerol, fatty acid, ceramide, glycerophospholipid, amino acid, and tricarboxylic acid metabolism. We demonstrated that methods focused on metabolomics are useful for identifying metabolites that may be used to clarify the mechanism of drug-induced toxicity.

Metabolomic identification of biochemical changes induced by fluoxetine in an insulinoma cell line (MIN6).

Background and purpose: The use of fluoxetine raises the risk of pancreatic beta-cell dysfunction. However, the specific mechanism behind its mechanism of action in beta cells is unknown. This study investigated the cellular response of MIN6 cells to fluoxetine using untargeted cell-based metabolomics. Experimental approach: Metabolic profiling of MIN6 cells was performed using liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis on samples prepared under optimized conditions, followed by principal component analysis, partial least squares-discriminant analysis, and pair-wise orthogonal projections to latent structures discriminant analyses. Findings/Results: Sixty-six metabolites that had been differentially expressed between the control and fluoxetine-treated groups demonstrated that the citric acid cycle is mainly perturbed by fluoxetine treatment. Conclusion and implications: The current study provides insights into the molecular mechanisms of fluoxetine effects in MIN6 cells.

Exploring the mechanisms of clozapine-induced blood-brain barrier dysfunction using untargeted metabolomics and cellular metabolism analysis.

Brain microvascular endothelial cells (BMVECs) from the blood- brain barrier form a highly selective membrane that protects the brain from circulating blood and maintains a stable microenvironment for the central nervous system. BMVEC dysfunction has been implicated in a variety of neurological and psychiatric disorders. Clozapine, a widely used antipsychotics, has been demonstrated to alter the permeability of BMVECs, but the underlying mechanisms of this effect are not fully understood. In this study, we investigated the effects of clozapine in BMVECs using untargeted metabolomics analysis. Our results illustrated that treatment with clozapine led to significant changes in the metabolic profile of BMVECs, including alterations in amino acid and energy metabolism. These findings suggest that clozapine affects BMVEC permeability through its effects on cellular metabolism. Our study could inform the development of more targeted and effective treatments for understanding the relationships among clozapine, cellular metabolism, and BMVECs in more detail.