Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites

Dragana Milutin Filipovic
* ORCID logo ,
Julica Inderhees
,
Alexandra Korda
,
Predrag Tadić
,
Markus Schwaninger
ORCID logo ,
Dragoš Inta
,
Stefan Borgwardt
ORCID logo
Version 1 : Received: 31 May 2023 / Approved: 1 June 2023 / Online: 1 June 2023 (13:35:47 CEST)

A peer-reviewed article of this Preprint also exists.

Filipović, D.; Inderhees, J.; Korda, A.; Tadić, P.; Schwaninger, M.; Inta, D.; Borgwardt, S. Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites. Int. J. Mol. Sci. 2023, 24, 10957. Filipović, D.; Inderhees, J.; Korda, A.; Tadić, P.; Schwaninger, M.; Inta, D.; Borgwardt, S. Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites. Int. J. Mol. Sci. 2023, 24, 10957.

Abstract

The increasing prevalence of depression worldwide requires more effectiveness in therapy approaches and a molecular understanding of antidepressants mode of action. We carried out untargeted metabolomics of the prefrontal cortex of rats exposed to chronic social isolation (CSIS), a rat model of depression, and/or fluoxetine treatment using liquid chromatography-high resolution mass spectrometry. The behavioral phenotype was assessed by the forced swim test. To analyze metabolomics data, univariate and multivariate analysis and biomarker capacity assessment using the classical receiver operating characteristic (ROC) curve were used. Support vector machine-linear kernel (SVM-LK), as a machine-learning algorithm was performed for binary classification. Upregulated myo-inositol following CSIS may represent a potential marker of depressive phenotype. Effective fluoxetine treatment reversed depressive-like behavior and increased sedoheptulose 7-phosphate, hypotaurine, and acetyl-L-carnitine contents, which were identified as potential markers. We identified 4 or 10 marker candidates with ROC curve greater than 0.9 for CSIS or fluoxetine effectiveness designation. SVM-LK has given accuracy of 61.50%, or 93.30%, and 7 or 25 predictive metabolites for CSIS vs. control and fluoxetine-treated CSIS vs. CSIS classification. Overall, metabolic fingerprints combined with ROC curve and SVM-LK may represent a new approach to identifying potential markers or predicting metabolites for group designation or classification.

Keywords

depressive-like behavior; prefrontal cortex; fluoxetine; metabolomics; ROC curve; support vector machine-linear kernel

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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