Literature DB >> 25640931

Identifying predictors, moderators, and mediators of antidepressant response in major depressive disorder: neuroimaging approaches.

Mary L Phillips1, Henry W Chase, Yvette I Sheline, Amit Etkin, Jorge R C Almeida, Thilo Deckersbach, Madhukar H Trivedi.   

Abstract

OBJECTIVE: Despite significant advances in neuroscience and treatment development, no widely accepted biomarkers are available to inform diagnostics or identify preferred treatments for individuals with major depressive disorder.
METHOD: In this critical review, the authors examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in depression and whether such biomarkers may act as predictors, moderators, and mediators of treatment response that might facilitate development of personalized treatments based on a better understanding of these processes.
RESULTS: The authors first highlight the most consistent findings from neuroimaging studies using different techniques in depression, including structural and functional abnormalities in two parallel neural circuits: serotonergically modulated implicit emotion regulation circuitry, centered on the amygdala and different regions in the medial prefrontal cortex; and dopaminergically modulated reward neural circuitry, centered on the ventral striatum and medial prefrontal cortex. They then describe key findings from the relatively small number of studies indicating that specific measures of regional function and, to a lesser extent, structure in these neural circuits predict treatment response in depression.
CONCLUSIONS: Limitations of existing studies include small sample sizes, use of only one neuroimaging modality, and a focus on identifying predictors rather than moderators and mediators of differential treatment response. By addressing these limitations and, most importantly, capitalizing on the benefits of multimodal neuroimaging, future studies can yield moderators and mediators of treatment response in depression to facilitate significant improvements in shorter- and longer-term clinical and functional outcomes.

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Year:  2015        PMID: 25640931      PMCID: PMC4464814          DOI: 10.1176/appi.ajp.2014.14010076

Source DB:  PubMed          Journal:  Am J Psychiatry        ISSN: 0002-953X            Impact factor:   18.112


  183 in total

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2.  Predicting human resting-state functional connectivity from structural connectivity.

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3.  Altered white matter integrity in first-episode, treatment-naive young adults with major depressive disorder: a tract-based spatial statistics study.

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Journal:  Brain Res       Date:  2010-11-01       Impact factor: 3.252

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5.  White matter changes in healthy adolescents at familial risk for unipolar depression: a diffusion tensor imaging study.

Authors:  Hao Huang; Xin Fan; Douglas E Williamson; Uma Rao
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6.  Increased anterior cingulate cortical activity in response to fearful faces: a neurophysiological biomarker that predicts rapid antidepressant response to ketamine.

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7.  Genetic variation in components of dopamine neurotransmission impacts ventral striatal reactivity associated with impulsivity.

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Authors:  Björn H Schott; Luciano Minuzzi; Ruth M Krebs; David Elmenhorst; Markus Lang; Oliver H Winz; Constanze I Seidenbecher; Heinz H Coenen; Hans-Jochen Heinze; Karl Zilles; Emrah Düzel; Andreas Bauer
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10.  Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization.

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  70 in total

1.  Diagnostic classification of unipolar depression based on resting-state functional connectivity MRI: effects of generalization to a diverse sample.

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2.  DATA-DRIVEN CLUSTER SELECTION FOR SUBCORTICAL SHAPE AND CORTICAL THICKNESS PREDICTS RECOVERY FROM DEPRESSIVE SYMPTOMS.

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Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2017-06-19

3.  Co-Variation of Peripheral Levels of miR-1202 and Brain Activity and Connectivity During Antidepressant Treatment.

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4.  Rethinking strategies for when to acquire neural markers associated with treatment response.

Authors:  A S Heller
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5.  Predicting Response to the Antidepressant Bupropion using Pretreatment fMRI.

Authors:  Kevin P Nguyen; Cherise Chin Fatt; Alex Treacher; Cooper Mellema; Madhukar H Trivedi; Albert Montillo
Journal:  Predict Intell Med (2019)       Date:  2019-10-10

6.  Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study.

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Journal:  Am J Psychiatry       Date:  2015-07-17       Impact factor: 18.112

7.  Neurochemical differences between target-specific populations of rat dorsal raphe projection neurons.

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8.  Acupuncture treatment modulates the corticostriatal reward circuitry in major depressive disorder.

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Review 10.  Glutamate and Gamma-Aminobutyric Acid Systems in the Pathophysiology of Major Depression and Antidepressant Response to Ketamine.

Authors:  Marc S Lener; Mark J Niciu; Elizabeth D Ballard; Minkyung Park; Lawrence T Park; Allison C Nugent; Carlos A Zarate
Journal:  Biol Psychiatry       Date:  2016-05-12       Impact factor: 13.382

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