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Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression

The efficacy of antidepressant treatment for depression is controversial due to only modest superiority demonstrated over placebo. However, neurobiological heterogeneity within depression may limit overall antidepressant efficacy. We sought to identify a neurobiological phenotype responsive to antid...

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Autores principales: Fonzo, Gregory A., Etkin, Amit, Zhang, Yu, Wu, Wei, Cooper, Crystal, Chin-Fatt, Cherise, Jha, Manish K., Trombello, Joseph, Deckersbach, Thilo, Adams, Phil, McInnis, Melvin, McGrath, Patrick J., Weissman, Myrna M., Fava, Maurizio, Trivedi, Madhukar H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6908746/
https://www.ncbi.nlm.nih.gov/pubmed/31548678
http://dx.doi.org/10.1038/s41562-019-0732-1
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author Fonzo, Gregory A.
Etkin, Amit
Zhang, Yu
Wu, Wei
Cooper, Crystal
Chin-Fatt, Cherise
Jha, Manish K.
Trombello, Joseph
Deckersbach, Thilo
Adams, Phil
McInnis, Melvin
McGrath, Patrick J.
Weissman, Myrna M.
Fava, Maurizio
Trivedi, Madhukar H.
author_facet Fonzo, Gregory A.
Etkin, Amit
Zhang, Yu
Wu, Wei
Cooper, Crystal
Chin-Fatt, Cherise
Jha, Manish K.
Trombello, Joseph
Deckersbach, Thilo
Adams, Phil
McInnis, Melvin
McGrath, Patrick J.
Weissman, Myrna M.
Fava, Maurizio
Trivedi, Madhukar H.
author_sort Fonzo, Gregory A.
collection PubMed
description The efficacy of antidepressant treatment for depression is controversial due to only modest superiority demonstrated over placebo. However, neurobiological heterogeneity within depression may limit overall antidepressant efficacy. We sought to identify a neurobiological phenotype responsive to antidepressant treatment by testing pretreatment brain activation during response to, and regulation of, emotional conflict as a moderator of the clinical benefit of the antidepressant sertraline versus placebo. Using neuroimaging data from a large randomized controlled trial, we found widespread moderation of clinical benefits by brain activity during regulation of emotional conflict, in which greater down-regulation of conflict-responsive regions predicted better sertraline outcomes. Treatment-predictive machine learning utilizing brain metrics outperformed a model trained on clinical and demographic variables. Our findings demonstrate antidepressant response is predicted by brain activity underlying a key self-regulatory emotional capacity. Leveraging brain-based measures in psychiatry will forge a path toward better treatment personalization, refined mechanistic insights, and improved outcomes. TRIAL REGISTRATION: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC),
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spelling pubmed-69087462020-03-23 Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression Fonzo, Gregory A. Etkin, Amit Zhang, Yu Wu, Wei Cooper, Crystal Chin-Fatt, Cherise Jha, Manish K. Trombello, Joseph Deckersbach, Thilo Adams, Phil McInnis, Melvin McGrath, Patrick J. Weissman, Myrna M. Fava, Maurizio Trivedi, Madhukar H. Nat Hum Behav Article The efficacy of antidepressant treatment for depression is controversial due to only modest superiority demonstrated over placebo. However, neurobiological heterogeneity within depression may limit overall antidepressant efficacy. We sought to identify a neurobiological phenotype responsive to antidepressant treatment by testing pretreatment brain activation during response to, and regulation of, emotional conflict as a moderator of the clinical benefit of the antidepressant sertraline versus placebo. Using neuroimaging data from a large randomized controlled trial, we found widespread moderation of clinical benefits by brain activity during regulation of emotional conflict, in which greater down-regulation of conflict-responsive regions predicted better sertraline outcomes. Treatment-predictive machine learning utilizing brain metrics outperformed a model trained on clinical and demographic variables. Our findings demonstrate antidepressant response is predicted by brain activity underlying a key self-regulatory emotional capacity. Leveraging brain-based measures in psychiatry will forge a path toward better treatment personalization, refined mechanistic insights, and improved outcomes. TRIAL REGISTRATION: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), 2019-09-23 2019-12 /pmc/articles/PMC6908746/ /pubmed/31548678 http://dx.doi.org/10.1038/s41562-019-0732-1 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Fonzo, Gregory A.
Etkin, Amit
Zhang, Yu
Wu, Wei
Cooper, Crystal
Chin-Fatt, Cherise
Jha, Manish K.
Trombello, Joseph
Deckersbach, Thilo
Adams, Phil
McInnis, Melvin
McGrath, Patrick J.
Weissman, Myrna M.
Fava, Maurizio
Trivedi, Madhukar H.
Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression
title Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression
title_full Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression
title_fullStr Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression
title_full_unstemmed Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression
title_short Brain Regulation of Emotional Conflict Predicts Antidepressant Treatment Response for Depression
title_sort brain regulation of emotional conflict predicts antidepressant treatment response for depression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6908746/
https://www.ncbi.nlm.nih.gov/pubmed/31548678
http://dx.doi.org/10.1038/s41562-019-0732-1
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