Literature DB >> 26826874

Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression.

Xiaoqian J Chai1, Dina Hirshfeld-Becker2, Joseph Biederman3, Mai Uchida3, Oliver Doehrmann4, Julia A Leonard4, John Salvatore4, Tara Kenworthy3, Ariel Brown3, Elana Kagan3, Carlo de Los Angeles4, John D E Gabrieli5, Susan Whitfield-Gabrieli4.   

Abstract

BACKGROUND: Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression.
METHODS: We compared resting-state functional connectivity, measured with functional magnetic resonance imaging, between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8-14 years of age) and age-matched children of parents with no lifetime history of depression (control subjects, n = 16).
RESULTS: At-risk children exhibited hyperconnectivity between the default mode network and subgenual anterior cingulate cortex/orbital frontal cortex, and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited 1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the default mode network; 2) hypoconnectivity between left dorsolateral prefrontal cortex and subgenual anterior cingulate cortex; and 3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and control subjects based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales.
CONCLUSIONS: Children at familial risk for depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression.
Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Chidren; Default mode network; Depression; Familial risk; Resting-state fMRI; Subgenual ACC

Mesh:

Year:  2015        PMID: 26826874      PMCID: PMC4956583          DOI: 10.1016/j.biopsych.2015.12.003

Source DB:  PubMed          Journal:  Biol Psychiatry        ISSN: 0006-3223            Impact factor:   13.382


  65 in total

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2.  A component based noise correction method (CompCor) for BOLD and perfusion based fMRI.

Authors:  Yashar Behzadi; Khaled Restom; Joy Liau; Thomas T Liu
Journal:  Neuroimage       Date:  2007-05-03       Impact factor: 6.556

3.  Subgenual cingulate connectivity in children with a history of preschool-depression.

Authors:  Michael S Gaffrey; Joan L Luby; Grega Repovš; Andy C Belden; Kelly N Botteron; Katherine R Luking; Deanna M Barch
Journal:  Neuroreport       Date:  2010-12-29       Impact factor: 1.837

4.  Anticorrelations in resting state networks without global signal regression.

Authors:  Xiaoqian J Chai; Alfonso Nieto Castañón; Dost Ongür; Susan Whitfield-Gabrieli
Journal:  Neuroimage       Date:  2011-08-26       Impact factor: 6.556

5.  Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus.

Authors:  Michael D Greicius; Benjamin H Flores; Vinod Menon; Gary H Glover; Hugh B Solvason; Heather Kenna; Allan L Reiss; Alan F Schatzberg
Journal:  Biol Psychiatry       Date:  2007-01-08       Impact factor: 13.382

6.  Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity.

Authors:  Michael D Fox; Hesheng Liu; Alvaro Pascual-Leone
Journal:  Neuroimage       Date:  2012-11-07       Impact factor: 6.556

7.  Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study.

Authors:  Amit Anand; Yu Li; Yang Wang; Jingwei Wu; Sujuan Gao; Lubna Bukhari; Vincent P Mathews; Andrew Kalnin; Mark J Lowe
Journal:  Biol Psychiatry       Date:  2005-05-15       Impact factor: 13.382

8.  The default mode network and self-referential processes in depression.

Authors:  Yvette I Sheline; Deanna M Barch; Joseph L Price; Melissa M Rundle; S Neil Vaishnavi; Abraham Z Snyder; Mark A Mintun; Suzhi Wang; Rebecca S Coalson; Marcus E Raichle
Journal:  Proc Natl Acad Sci U S A       Date:  2009-01-26       Impact factor: 11.205

9.  First episode of depression in children at low and high familial risk for depression.

Authors:  Douglas E Williamson; Boris Birmaher; David A Axelson; Neal D Ryan; Ronald E Dahl
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2004-03       Impact factor: 8.829

10.  Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder.

Authors:  Elizabeth Redcay; Joseph M Moran; Penelope L Mavros; Helen Tager-Flusberg; John D E Gabrieli; Susan Whitfield-Gabrieli
Journal:  Front Hum Neurosci       Date:  2013-09-19       Impact factor: 3.169

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  19 in total

1.  Neural markers of depression risk predict the onset of depression.

Authors:  Benjamin G Shapero; Xiaoqian J Chai; Mark Vangel; Joseph Biederman; Christian S Hoover; Susan Whitfield-Gabrieli; John D E Gabrieli; Dina R Hirshfeld-Becker
Journal:  Psychiatry Res Neuroimaging       Date:  2019-01-25       Impact factor: 2.376

2.  Attenuation of Frontostriatal Connectivity During Reward Processing Predicts Response to Psychotherapy in Major Depressive Disorder.

Authors:  Erin Walsh; Hannah Carl; Tory Eisenlohr-Moul; Jared Minkel; Andrew Crowther; Tyler Moore; Devin Gibbs; Chris Petty; Josh Bizzell; Moria J Smoski; Gabriel S Dichter
Journal:  Neuropsychopharmacology       Date:  2016-09-02       Impact factor: 7.853

3.  Emotion dysregulation and functional connectivity in children with and without a history of major depressive disorder.

Authors:  Katherine C Lopez; Joan L Luby; Andy C Belden; Deanna M Barch
Journal:  Cogn Affect Behav Neurosci       Date:  2018-04       Impact factor: 3.282

4.  Intrinsic Functional Brain Connectivity Predicts Onset of Major Depression Disorder in Adolescence: A Pilot Study.

Authors:  Dina R Hirshfeld-Becker; John D E Gabrieli; Benjamin G Shapero; Joseph Biederman; Susan Whitfield-Gabrieli; Xiaoqian J Chai
Journal:  Brain Connect       Date:  2019-04-11

5.  Impaired Frontal-Limbic White Matter Maturation in Children at Risk for Major Depression.

Authors:  Yuwen Hung; Zeynep M Saygin; Joseph Biederman; Dina Hirshfeld-Becker; Mai Uchida; Oliver Doehrmann; Michelle Han; Xiaoqian J Chai; Tara Kenworthy; Pavel Yarmak; Schuyler L Gaillard; Susan Whitfield-Gabrieli; John D E Gabrieli
Journal:  Cereb Cortex       Date:  2017-09-01       Impact factor: 5.357

Review 6.  Adolescent brain development and depression: A case for the importance of connectivity of the anterior cingulate cortex.

Authors:  Sarah D Lichenstein; Timothy Verstynen; Erika E Forbes
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7.  Depression in chronic ketamine users: Sex differences and neural bases.

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Journal:  Psychiatry Res Neuroimaging       Date:  2017-09-05       Impact factor: 2.376

8.  Subsyndromal Manifestations of Depression in Children Predict the Development of Major Depression.

Authors:  Mai Uchida; Maura Fitzgerald; Hilary Woodworth; Nicholas Carrellas; Caroline Kelberman; Joseph Biederman
Journal:  J Pediatr       Date:  2018-07-13       Impact factor: 4.406

9.  Orbitofrontal cortex activity and connectivity predict future depression symptoms in adolescence.

Authors:  Jingwen Jin; Ananth Narayanan; Greg Perlman; Katherine Luking; Christine DeLorenzo; Greg Hajcak; Daniel N Klein; Roman Kotov; Aprajita Mohanty
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2017-02-27

10.  Neural Markers of Resilience in Adolescent Females at Familial Risk for Major Depressive Disorder.

Authors:  Adina S Fischer; M Catalina Camacho; Tiffany C Ho; Susan Whitfield-Gabrieli; Ian H Gotlib
Journal:  JAMA Psychiatry       Date:  2018-05-01       Impact factor: 21.596

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