ArticleMetabolomics : Official journal of the Metabolomic Society2023
Behavioral metabolomics: how behavioral data can guide metabolomics research on neuropsychiatric disorders.
Article in Metabolomics : Official journal of the Metabolomic Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Maternal-offspring brain and tissue cross-talk in preeclampsia: insights from a rat model.Metabolic brain disease · 2025Article
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6 authors.
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Abstract
introductionMetabolomics produces vast quantities of data but determining which metabolites are the most relevant to the disease or disorder of interest can be challenging.
objectivesThis study sought to demonstrate how behavioral models of psychiatric disorders can be combined with metabolomics research to overcome this limitation.
methodsWe designed a preclinical, untargeted metabolomics procedure, that focuses on the determination of central metabolites relevant to substance use disorders that are (a) associated with changes in behavior produced by acute drug exposure and (b) impacted by repeated drug exposure. Untargeted metabolomics analysis was carried out on liquid chromatography-mass spectrometry data obtained from 336 microdialysis samples. Samples were collected from the medial striatum of male Sprague-Dawley (N = 21) rats whilst behavioral data were simultaneously collected as part of a (±)-3,4-methylenedioxymethamphetamine (MDMA)-induced behavioral sensitization experiment. Analysis was conducted by orthogonal partial least squares, where the Y variable was the behavioral data, and the X variables were the relative concentrations of the 737 detected features.
resultsMDMA and its derivatives, serotonin, and several dopamine/norepinephrine metabolites were the greatest predictors of acute MDMA-produced behavior. Subsequent univariate analyses showed that repeated MDMA exposure produced significant changes in MDMA metabolism, which may contribute to the increased abuse liability of the drug as a function of repeated exposure.
conclusionThese findings highlight how the inclusion of behavioral data can guide metabolomics data analysis and increase the relevance of the results to the phenotype of interest.
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