Identification of Plasma Metabolites Responding to Oxycodone Exposure in Rats

Background: Oxycodone has an elevated abuse liability profile compared to other prescription opioid medications. However, many human and rodent metabolomics studies have not been specifically focused on oxycodone. Objectives: Investigating metabolomics changes associated with oxycodone exposure can...

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Bibliographic Details
Published in:Metabolites
Main Authors: Thao Vu, Suneeta Godbole, Lieselot L. G. Carrette, Lisa Maturin, Olivier George, Laura M. Saba, Katerina Kechris
Format: Article
Language:English
Published: MDPI AG 2025-02-01
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Online Access:https://www.mdpi.com/2218-1989/15/2/95
Description
Summary:Background: Oxycodone has an elevated abuse liability profile compared to other prescription opioid medications. However, many human and rodent metabolomics studies have not been specifically focused on oxycodone. Objectives: Investigating metabolomics changes associated with oxycodone exposure can provide insights into biochemical mechanisms of the addiction cycle and prognosis prediction. Methods: Plasma samples from 16 rats at pre-exposure and intoxication time points were profiled on the Metabolon platform. A total of 941 metabolites were characterized. We employed a k-Nearest Neighbor imputation to impute metabolites with low levels of missingness and binarized metabolites with moderate levels of missingness, respectively. Results: Of the 136 binarized metabolites, 6 showed differential abundance (FDR < 0.05), including 5 that were present at pre-exposure but absent at intoxication (e.g., <i>adenine</i>), while <i>linoleamide (18:2n6)</i> exhibited the opposite behavior. Among the 798 metabolites with low levels of missingness, 364 showed significant changes between pre-exposure and intoxication (FDR < 0.01), including <i>succinate</i>, <i>oleamide</i>, and <i>sarcosine</i>. We identified four pathways, including <i>tryptophan metabolism,</i> that were nominally enriched among the metabolites that change with oxycodone exposure (<i>p</i> < 0.05). Furthermore, we identified several metabolites that showed nominal correlations with the Addiction Index (composite of oxycodone behaviors): 17 at pre-exposure and 8 at intoxication. In addition, the changes in abundance between pre-exposure and intoxication time points of 9 metabolites were nominally correlated with the Addiction Index, including <i>sphingomyelins</i>, <i>methylhistidines</i>, and <i>glycerols</i>. Conclusions: In summary, not only were we able to capture oxy-induced changes in metabolic pathways using easily accessible blood samples, but we also demonstrated the potential of blood metabolomics to better understand addiction liability.
ISSN:2218-1989