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Author Notes:

Corresponding Author: Boadie W. Dunlop, MD, MS, Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 12 Executive Park Drive NE, 3rd Floor, Atlanta, GA, 30329, bdunlop@emory.edu, Phone: 404-727-8474, Fax: 404-727-3700.

Acknowledgments: From the Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta; the Department of Psychology, Emory University, Atlanta; the Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta; the Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, Mass.; and the Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami.

BWD has received research support from Assurex, Bristol-Myers Squibb, GlaxoSmithKline, Janssen, NIMH, Otsuka, Pfizer, and Takeda

He has served as a consultant to Pfizer and Medavante.

WEC is a board member of Hugarheill ehf, an Icelandic company dedicated to the prevention of depression, receives book royalties from John Wiley & Sons, is supported by the Mary and John Brock Foundation and the Fuqua Family Foundations, is a consultant to the George West Mental Health Foundation, and is a member of the Scientific Advisory Board of ADAA.

See publication for full list of disclosures.


Research Funding:

This study was supported by the following National Institutes of Health grants: P50 MH077083; RO1 MH080880; UL1 RR025008; M01 RR0039 and K23 MH086690.

Forest Labs and Elli Lilly Inc. donated the study medications, escitalopram and duloxetine, respectively, but were otherwise uninvolved in study design, data collection, data analysis, or interpretation of findings.


  • Science & Technology
  • Life Sciences & Biomedicine
  • Psychiatry
  • MOOD
  • MRI

Functional Connectivity of the Subcallosal Cingulate Cortex And Differential Outcomes to Treatment With Cognitive-Behavioral Therapy or Antidepressant Medication for Major Depressive Disorder


Journal Title:

American Journal of Psychiatry


Volume 174, Number 6


, Pages 533-545

Type of Work:

Article | Post-print: After Peer Review


Objective: The purpose of this article was to inform the firstline treatment choice between cognitive-behavioral therapy (CBT) or an antidepressant medication for treatment-naive adults with major depressive disorder by defining a neuroimaging biomarker that differentially identifies the outcomes of remission and treatment failure to these interventions. Method: Functional MRI resting-state functional connectivity analyses using a bilateral subcallosal cingulate cortex (SCC) seed was applied to 122 patients from the Prediction of Remission to Individual and Combined Treatments (PReDICT) study who completed 12 weeks of randomized treatment with CBT or antidepressant medication. Of the 122 participants, 58 achieved remission (Hamilton Depression Rating Scale [HAM-D] score #7 at weeks 10 and 12), and 24 had treatment failure (,30% decrease frombaseline in HAM-D score). A 232 analysis of variance using voxel-wise subsampling permutation tests compared the interaction of treatment and outcome. Receiver operating characteristic curves constructed using brain connectivitymeasures were used to determine possible classification rates for differential treatment outcomes. Results: The resting-state functional connectivity of the following three regions with the SCC was differentially associated with outcomes of remission and treatment failure to CBT and antidepressant medication and survived application of the subsample permutation tests: the left anterior ventrolateral prefrontal cortex/insula, the dorsal midbrain, and the left ventromedial prefrontal cortex. Using the summed SCC functional connectivity scores for these three regions, overall classification rates of 72%278% for remission and 75%289% for treatment failure was demonstrated. Positive summed functional connectivity was associated with remission with CBT and treatment failure with medication, whereas negative summed functional connectivity scores were associated with remission to medication and treatment failure with CBT. Conclusions: Imaging-based depression subtypes defined using resting-state functional connectivity differentially identified an individual's probability of remission or treatment failure with first-line treatment options for major depression. This biomarker should be explored in future research through prospective testing and as a component of multivariate treatment prediction models.

Copyright information:

© American Psychiatric Association ALL RIGHTS RESERVED

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