Brain regulation of emotional conflict predicts antidepressant treatment response for depression

被引:0
作者
Gregory A. Fonzo
Amit Etkin
Yu Zhang
Wei Wu
Crystal Cooper
Cherise Chin-Fatt
Manish K. Jha
Joseph Trombello
Thilo Deckersbach
Phil Adams
Melvin McInnis
Patrick J. McGrath
Myrna M. Weissman
Maurizio Fava
Madhukar H. Trivedi
机构
[1] The University of Texas at Austin,Department of Psychiatry, Dell Medical School
[2] Stanford University,Department of Psychiatry and Behavioral Sciences
[3] Stanford University,Wu Tsai Neurosciences Institute
[4] Sierra Pacific Mental Illness Research,Department of Psychiatry
[5] Education and Clinical Center in the Veterans Affairs Palo Alto Healthcare System,Department of Psychiatry
[6] University of Texas Southwestern Medical Center,New York State Psychiatric Institute and Department of Psychiatry
[7] Massachusetts General Hospital,Department of Psychiatry
[8] College of Physicians and Surgeons of Columbia University,undefined
[9] University of Michigan,undefined
来源
Nature Human Behaviour | 2019年 / 3卷
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摘要
The efficacy of antidepressant treatment for depression is controversial due to the 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 downregulation of conflict-responsive regions predicted better sertraline outcomes. Treatment-predictive machine learning using brain metrics outperformed a model trained on clinical and demographic variables. Our findings demonstrate that 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.
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页码:1319 / 1331
页数:12
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