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Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are the most common form of medication treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems respond to...

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Autores principales: Samuels, Benjamin A., Leonardo, E. David, Dranovsky, Alex, Williams, Amanda, Wong, Erik, Nesbitt, Addie May I., McCurdy, Richard D., Hen, Rene, Alter, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894967/
https://www.ncbi.nlm.nih.gov/pubmed/24465494
http://dx.doi.org/10.1371/journal.pone.0085136
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author Samuels, Benjamin A.
Leonardo, E. David
Dranovsky, Alex
Williams, Amanda
Wong, Erik
Nesbitt, Addie May I.
McCurdy, Richard D.
Hen, Rene
Alter, Mark
author_facet Samuels, Benjamin A.
Leonardo, E. David
Dranovsky, Alex
Williams, Amanda
Wong, Erik
Nesbitt, Addie May I.
McCurdy, Richard D.
Hen, Rene
Alter, Mark
author_sort Samuels, Benjamin A.
collection PubMed
description BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are the most common form of medication treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems respond to treatments may be critical for understanding antidepressant resistance. METHODS: We take a novel approach to this problem by demonstrating that the gene expression system of the dentate gyrus responds to fluoxetine (FLX), a commonly used antidepressant medication, in a stereotyped-manner involving changes in the expression levels of thousands of genes. The aggregate behavior of this large-scale systemic response was quantified with principal components analysis (PCA) yielding a single quantitative measure of the global gene expression system state. RESULTS: Quantitative measures of system state were highly correlated with variability in levels of antidepressant-sensitive behaviors in a mouse model of depression treated with fluoxetine. Analysis of dorsal and ventral dentate samples in the same mice indicated that system state co-varied across these regions despite their reported functional differences. Aggregate measures of gene expression system state were very robust and remained unchanged when different microarray data processing algorithms were used and even when completely different sets of gene expression levels were used for their calculation. CONCLUSIONS: System state measures provide a robust method to quantify and relate global gene expression system state variability to behavior and treatment. State variability also suggests that the diversity of reported changes in gene expression levels in response to treatments such as fluoxetine may represent different perspectives on unified but noisy global gene expression system state level responses. Studying regulation of gene expression systems at the state level may be useful in guiding new approaches to augmentation of traditional antidepressant treatments.
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spelling pubmed-38949672014-01-24 Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors Samuels, Benjamin A. Leonardo, E. David Dranovsky, Alex Williams, Amanda Wong, Erik Nesbitt, Addie May I. McCurdy, Richard D. Hen, Rene Alter, Mark PLoS One Research Article BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are the most common form of medication treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems respond to treatments may be critical for understanding antidepressant resistance. METHODS: We take a novel approach to this problem by demonstrating that the gene expression system of the dentate gyrus responds to fluoxetine (FLX), a commonly used antidepressant medication, in a stereotyped-manner involving changes in the expression levels of thousands of genes. The aggregate behavior of this large-scale systemic response was quantified with principal components analysis (PCA) yielding a single quantitative measure of the global gene expression system state. RESULTS: Quantitative measures of system state were highly correlated with variability in levels of antidepressant-sensitive behaviors in a mouse model of depression treated with fluoxetine. Analysis of dorsal and ventral dentate samples in the same mice indicated that system state co-varied across these regions despite their reported functional differences. Aggregate measures of gene expression system state were very robust and remained unchanged when different microarray data processing algorithms were used and even when completely different sets of gene expression levels were used for their calculation. CONCLUSIONS: System state measures provide a robust method to quantify and relate global gene expression system state variability to behavior and treatment. State variability also suggests that the diversity of reported changes in gene expression levels in response to treatments such as fluoxetine may represent different perspectives on unified but noisy global gene expression system state level responses. Studying regulation of gene expression systems at the state level may be useful in guiding new approaches to augmentation of traditional antidepressant treatments. Public Library of Science 2014-01-17 /pmc/articles/PMC3894967/ /pubmed/24465494 http://dx.doi.org/10.1371/journal.pone.0085136 Text en © 2014 Samuels et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Samuels, Benjamin A.
Leonardo, E. David
Dranovsky, Alex
Williams, Amanda
Wong, Erik
Nesbitt, Addie May I.
McCurdy, Richard D.
Hen, Rene
Alter, Mark
Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors
title Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors
title_full Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors
title_fullStr Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors
title_full_unstemmed Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors
title_short Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors
title_sort global state measures of the dentate gyrus gene expression system predict antidepressant-sensitive behaviors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894967/
https://www.ncbi.nlm.nih.gov/pubmed/24465494
http://dx.doi.org/10.1371/journal.pone.0085136
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