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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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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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), |
format | Online Article Text |
id | pubmed-6908746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
record_format | MEDLINE/PubMed |
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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