Cherise R Chin Fatt1, Manish K Jha1, Crystal M Cooper1, Gregory Fonzo1, Charles South1, Bruce Grannemann1, Thomas Carmody1, Tracy L Greer1, Benji Kurian1, Maurizio Fava1, Patrick J McGrath1, Phillip Adams1, Melvin McInnis1, Ramin V Parsey1, Myrna Weissman1, Mary L Phillips1, Amit Etkin1, Madhukar H Trivedi1. 1. Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips).
Abstract
OBJECTIVE: Major depressive disorder is associated with aberrant resting-state functional connectivity across multiple brain networks supporting emotion processing, executive function, and reward processing. The purpose of this study was to determine whether patterns of resting-state connectivity between brain regions predict differential outcome to antidepressant medication (sertraline) compared with placebo. METHODS: Participants in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study underwent structural and resting-state functional MRI at baseline. Participants were then randomly assigned to receive either sertraline or placebo treatment for 8 weeks (N=279). A region of interest-based approach was utilized to compute functional connectivity between brain regions. Linear mixed-model intent-to-treat analyses were used to identify brain regions that moderated (i.e., differentially predicted) outcomes between the sertraline and placebo arms. RESULTS: Prediction of response to sertraline involved several within- and between-network connectivity patterns. In general, higher connectivity within the default mode network predicted better outcomes specifically for sertraline, as did greater between-network connectivity of the default mode and executive control networks. In contrast, both placebo and sertraline outcomes were predicted (in opposite directions) by between-network hippocampal connectivity. CONCLUSIONS: This study identified specific functional network-based moderators of treatment outcome involving brain networks known to be affected by major depression. Specifically, functional connectivity patterns of brain regions between and within networks appear to play an important role in identifying a favorable response for a drug treatment for major depressive disorder.
RCT Entities:
OBJECTIVE: Major depressive disorder is associated with aberrant resting-state functional connectivity across multiple brain networks supporting emotion processing, executive function, and reward processing. The purpose of this study was to determine whether patterns of resting-state connectivity between brain regions predict differential outcome to antidepressant medication (sertraline) compared with placebo. METHODS:Participants in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study underwent structural and resting-state functional MRI at baseline. Participants were then randomly assigned to receive either sertraline or placebo treatment for 8 weeks (N=279). A region of interest-based approach was utilized to compute functional connectivity between brain regions. Linear mixed-model intent-to-treat analyses were used to identify brain regions that moderated (i.e., differentially predicted) outcomes between the sertraline and placebo arms. RESULTS: Prediction of response to sertraline involved several within- and between-network connectivity patterns. In general, higher connectivity within the default mode network predicted better outcomes specifically for sertraline, as did greater between-network connectivity of the default mode and executive control networks. In contrast, both placebo and sertraline outcomes were predicted (in opposite directions) by between-network hippocampal connectivity. CONCLUSIONS: This study identified specific functional network-based moderators of treatment outcome involving brain networks known to be affected by major depression. Specifically, functional connectivity patterns of brain regions between and within networks appear to play an important role in identifying a favorable response for a drug treatment for major depressive disorder.
Entities:
Keywords:
EMBARC; Functional Connectivity; Major Depressive Disorder; Moderators of Treatment Outcome
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