Literature DB >> 26068725

Neural Correlates of Three Promising Endophenotypes of Depression: Evidence from the EMBARC Study.

Christian A Webb1, Daniel G Dillon1, Pia Pechtel1, Franziska K Goer1, Laura Murray1, Quentin J M Huys2,3, Maurizio Fava4, Patrick J McGrath5, Myrna Weissman5, Ramin Parsey6, Benji T Kurian7, Phillip Adams5, Sarah Weyandt7, Joseph M Trombello7, Bruce Grannemann7, Crystal M Cooper7, Patricia Deldin8, Craig Tenke5, Madhukar Trivedi7, Gerard Bruder5, Diego A Pizzagalli1.   

Abstract

Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5-44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5-8 Hz) and alpha2 (10.5-12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities.

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Year:  2015        PMID: 26068725      PMCID: PMC5130121          DOI: 10.1038/npp.2015.165

Source DB:  PubMed          Journal:  Neuropsychopharmacology        ISSN: 0893-133X            Impact factor:   7.853


  55 in total

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Authors:  Diego A Pizzagalli
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Journal:  Clin Neurophysiol       Date:  2007-06-15       Impact factor: 3.708

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Authors:  Paul T Costa; R Michael Bagby; Jeffrey H Herbst; Robert R McCrae
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6.  Reliability and plasticity of response inhibition and interference control.

Authors:  Nicola M Wöstmann; Désirée S Aichert; Anna Costa; Katya Rubia; Hans-Jürgen Möller; Ulrich Ettinger
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Review 7.  Emotional processing in anterior cingulate and medial prefrontal cortex.

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Journal:  Trends Cogn Sci       Date:  2010-12-16       Impact factor: 20.229

8.  Assessing and interpreting personality change and continuity in patients treated for major depression.

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9.  Individual differences in reinforcement learning: behavioral, electrophysiological, and neuroimaging correlates.

Authors:  Diane L Santesso; Daniel G Dillon; Jeffrey L Birk; Avram J Holmes; Elena Goetz; Ryan Bogdan; Diego A Pizzagalli
Journal:  Neuroimage       Date:  2008-07-02       Impact factor: 6.556

10.  Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis.

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Journal:  Biol Mood Anxiety Disord       Date:  2013-06-19
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  38 in total

Review 1.  Toward Circuit Mechanisms of Pathophysiology in Depression.

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2.  Morphometry of the Hippocampus Across the Adult Life-Span in Patients with Depressive Disorders: Association with Neuroticism.

Authors:  Yu Liu; Jie Meng; Kangcheng Wang; Kaixiang Zhuang; Qunlin Chen; Wenjing Yang; Jiang Qiu; Dongtao Wei
Journal:  Brain Topogr       Date:  2021-05-14       Impact factor: 3.020

3.  Anhedonia and individual differences in orbitofrontal cortex sulcogyral morphology.

Authors:  Hyden Zhang; Lauren Harris; Molly Split; Vanessa Troiani; Ingrid R Olson
Journal:  Hum Brain Mapp       Date:  2016-11       Impact factor: 5.038

Review 4.  Peripheral biomarkers of major depression and antidepressant treatment response: Current knowledge and future outlooks.

Authors:  Bharathi S Gadad; Manish K Jha; Andrew Czysz; Jennifer L Furman; Taryn L Mayes; Michael P Emslie; Madhukar H Trivedi
Journal:  J Affect Disord       Date:  2017-07-05       Impact factor: 4.839

5.  Latent variable analysis of positive and negative valence processing focused on symptom and behavioral units of analysis in mood and anxiety disorders.

Authors:  Martin P Paulus; Murray B Stein; Michelle G Craske; Susan Bookheimer; Charles T Taylor; Alan N Simmons; Natasha Sidhu; Katherine S Young; Boyang Fan
Journal:  J Affect Disord       Date:  2017-01-11       Impact factor: 4.839

6.  Brooding, Inattention, and Impulsivity as Predictors of Adolescent Suicidal Ideation.

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7.  Cortical thickness is not associated with current depression in a clinical treatment study.

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Journal:  Hum Brain Mapp       Date:  2017-06-08       Impact factor: 5.038

8.  Characterizing anxiety subtypes and the relationship to behavioral phenotyping in major depression: Results from the EMBARC study.

Authors:  Joseph M Trombello; Diego A Pizzagalli; Myrna M Weissman; Bruce D Grannemann; Crystal M Cooper; Tracy L Greer; Ashley L Malchow; Manish K Jha; Thomas J Carmody; Benji T Kurian; Christian A Webb; Daniel G Dillon; Patrick J McGrath; Gerard Bruder; Maurizio Fava; Ramin V Parsey; Melvin G McInnis; Phil Adams; Madhukar H Trivedi
Journal:  J Psychiatr Res       Date:  2018-04-06       Impact factor: 4.791

9.  A neurophysiological measure of reward sensitivity and its association with anhedonia in psychiatrically healthy adolescents and young adults.

Authors:  David W Frank; Elise M Stevens; Francesco Versace
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10.  Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis.

Authors:  Alik S Widge; M Taha Bilge; Rebecca Montana; Weilynn Chang; Carolyn I Rodriguez; Thilo Deckersbach; Linda L Carpenter; Ned H Kalin; Charles B Nemeroff
Journal:  Am J Psychiatry       Date:  2018-10-03       Impact factor: 18.112

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