TY  - JOUR
AU  - Filipović, Dragana
AU  - Inderhees, Julica
AU  - Korda, Alexandra
AU  - Tadić, Predrag
AU  - Schwaninger, Markus
AU  - Inta, Dragoš
AU  - Borgwardt, Stefan
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11355
AB  - The increasing prevalence of depression requires more effective therapy and the 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 the metabolomics data, we employed univariate and multivariate analysis and biomarker capacity assessment using the receiver operating characteristic (ROC) curve. We also identified the most predictive biomarkers using a support vector machine with linear kernel (SVM-LK). 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 marker candidates for fluoxetine efficacy. ROC analysis revealed 4 significant marker candidates for CSIS group discrimination, and 10 for fluoxetine efficacy. SVM-LK with accuracies of 61.50% or 93.30% identified a panel of 7 or 25 predictive metabolites for depressive-like behavior or fluoxetine effectiveness, respectively. Overall, metabolic fingerprints combined with the ROC curve and SVM-LK may represent a new approach to identifying marker candidates or predictive metabolites for ongoing disease or disease risk and treatment outcome.
T2  - International Journal of Molecular Sciences
T1  - Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites
VL  - 24
IS  - 13
SP  - 10957
DO  - 10.3390/ijms241310957
ER  - 

@article{
author = "Filipović, Dragana and Inderhees, Julica and Korda, Alexandra and Tadić, Predrag and Schwaninger, Markus and Inta, Dragoš and Borgwardt, Stefan",
year = "2023",
abstract = "The increasing prevalence of depression requires more effective therapy and the 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 the metabolomics data, we employed univariate and multivariate analysis and biomarker capacity assessment using the receiver operating characteristic (ROC) curve. We also identified the most predictive biomarkers using a support vector machine with linear kernel (SVM-LK). 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 marker candidates for fluoxetine efficacy. ROC analysis revealed 4 significant marker candidates for CSIS group discrimination, and 10 for fluoxetine efficacy. SVM-LK with accuracies of 61.50% or 93.30% identified a panel of 7 or 25 predictive metabolites for depressive-like behavior or fluoxetine effectiveness, respectively. Overall, metabolic fingerprints combined with the ROC curve and SVM-LK may represent a new approach to identifying marker candidates or predictive metabolites for ongoing disease or disease risk and treatment outcome.",
journal = "International Journal of Molecular Sciences",
title = "Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites",
volume = "24",
number = "13",
pages = "10957",
doi = "10.3390/ijms241310957"
}

Filipović, D., Inderhees, J., Korda, A., Tadić, P., Schwaninger, M., Inta, D.,& Borgwardt, S.. (2023). Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites. in International Journal of Molecular Sciences, 24(13), 10957.
https://doi.org/10.3390/ijms241310957

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. in International Journal of Molecular Sciences. 2023;24(13):10957.
doi:10.3390/ijms241310957 .

Filipović, Dragana, Inderhees, Julica, Korda, Alexandra, Tadić, Predrag, Schwaninger, Markus, Inta, Dragoš, Borgwardt, Stefan, "Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites" in International Journal of Molecular Sciences, 24, no. 13 (2023):10957,
https://doi.org/10.3390/ijms241310957 . .