A review of fMRI studies during visual emotive processing in major depressive disorder

Jaworska, Natalia; Yang, Xinmin; Knott, Verner; MacQueen, Glenda

doi:10.3109/15622975.2014.885659

Cited by 116 publications

(92 citation statements)

References 104 publications

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“…Elevated activity in the PFC and the ACC has been shown during non-affective cognitive tasks in MDD patients as compared to controls using fMRI (Kerestes et al, 2014). Emotional cognition, in contrast, seems to also involve area of the amygdala and the hippocampus which show increased activation with emotive negative visual challenges processing; effects which are typically reversed by antidepressants (Jaworska et al, 2014;Kerestes et al, 2014). In addition poor performance on hippocampal-related memory tasks in MDD has been reported to precede any changes in hippocampal volume (Malykhin and Coupland, 2015).…”

Section: Neurodegenerative Changesmentioning

confidence: 96%

Depressive disorders: Processes leading to neurogeneration and potential novel treatments

Brown

McIntyre

Rosenblat

et al. 2018

Progress in Neuro-Psychopharmacology and Biological Psychiatry

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Section: Neurodegenerative Changesmentioning

confidence: 96%

Depressive disorders: Processes leading to neurogeneration and potential novel treatments

Brown

McIntyre

Rosenblat

et al. 2018

Progress in Neuro-Psychopharmacology and Biological Psychiatry

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“…A number of fMRI studies have reported amygdala hyper-reactivity in response to negative emotional faces in MDD overall relative to controls under both supraliminal (Peluso et al, 2009;Surguladze et al, 2005;Fu et al, 2004;Zhong et al, 2011) and subliminal (Sheline et al, 2001;Victor et al, 2010;Stuhrmann et al, 2012;Suslow et al, 2010) (for meta-analysis see the study by Hamilton et al (2012); for review see the studies by Browning et al (2010);Jaworska et al (2014)). These studies have typically reported on medicated patients, who by virtue of still meeting criteria for the disorder while on medication are likely non-responders.…”

Section: Discussionmentioning

confidence: 99%

Amygdala Reactivity to Emotional Faces in the Prediction of General and Medication-Specific Responses to Antidepressant Treatment in the Randomized iSPOT-D Trial

Williams

Korgaonkar

Song

et al. 2015

Neuropsychopharmacol

169

125

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Although the cost of poor treatment outcomes of depression is staggering, we do not yet have clinically useful methods for selecting the most effective antidepressant for each depressed person. Emotional brain activation is altered in major depressive disorder (MDD) and implicated in treatment response. Identifying which aspects of emotional brain activation are predictive of general and specific responses to antidepressants may help clinicians and patients when making treatment decisions. We examined whether amygdala activation probed by emotion stimuli is a general or differential predictor of response to three commonly prescribed antidepressants, using functional magnetic resonance imaging (fMRI). A test-retest design was used to assess patients with MDD in an academic setting as part of the International Study to Predict Optimized Treatment in Depression. A total of 80 MDD outpatients were scanned prior to treatment and 8 weeks after randomization to the selective serotonin reuptake inhibitors escitalopram and sertraline and the serotonin-norepinephrine reuptake inhibitor, venlafaxine-extended release (XR). A total of 34 matched controls were scanned at the same timepoints. We quantified the blood oxygen level-dependent signal of the amygdala during subliminal and supraliminal viewing of facial expressions of emotion. Response to treatment was defined by ⩾ 50% symptom improvement on the 17-item Hamilton Depression Rating Scale. Pre-treatment amygdala hypo-reactivity to subliminal happy and threat was a general predictor of treatment response, regardless of medication type (Cohen's d effect size 0.63 to 0.77; classification accuracy, 75%). Responders showed hypo-reactivity compared to controls at baseline, and an increase toward 'normalization' post-treatment. Pre-treatment amygdala reactivity to subliminal sadness was a differential moderator of non-response to venlafaxine-XR (Cohen's d effect size 1.5; classification accuracy, 81%). Non-responders to venlafaxine-XR showed pre-treatment hyperreactivity, which progressed to hypo-reactivity rather than normalization post-treatment, and hypo-reactivity post-treatment was abnormal compared to controls. Impaired amygdala activation has not previously been highlighted in the general vs differential prediction of antidepressant outcomes. Amygdala hypo-reactivity to emotions signaling reward and threat predicts the general capacity to respond to antidepressants. Amygdala hyper-reactivity to sad emotion is involved in a specific non-response to a serotonin-norepinephrine reuptake inhibitor. The findings suggest amygdala probes may help inform the personal selection of antidepressant treatments.

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“…To identify potential biomarkers of a depressive-like state in mice, we conducted a genome-wide transcriptome analysis on all RNA samples extracted from blood and the DG and ACC regions of the brain, both of which play major roles in emotion processing and are known to be altered in affective disorders (Jaworska et al, 2015). Processing of the raw data resulted in 17,368 analyzable probes for blood and 33,264 probes for each brain region.…”

Section: Blood Transcriptional Profiles Reflect Behavioral Variationsmentioning

confidence: 99%

“…We utilized the unpredictable chronic mild stress (UCMS) model, which has contributed to the elucidation of the pathophysiological mechanisms of depression such as decreased neurogenesis, hypothalamic-pituitary-adrenal (HPA) axis alterations and maladaptive changes in amygdala (Surget et al, 2008;Sibille et al, 2009;Nollet et al, 2013). We aimed to correlate depressive-like behavior induced by UCMS protocol and fluoxetine-induced recovery with transcriptional signatures from whole blood as well as the hippocampus and the anterior cingulate cortex (ACC), two brain regions involved in mood regulation in which dysfunction has been reported in MDD (Rive et al, 2013;Jaworska et al, 2015;Wise et al, 2016). Since the hippocampus is known to have large variations in gene expression, we focused on the dentate gyrus (DG) where adult neurogenesis has been described and linked to psychiatric illness (Kohen et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Translational identification of transcriptional signatures of major depression and antidepressant response

Hervé¹,

Bergon²,

Guisquet³

et al. 2017

European Neuropsychopharmacology

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Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.

show abstract

A review of fMRI studies during visual emotive processing in major depressive disorder

Abstract: In general, depressed patients have increased activation to emotive, especially negative, visual stimuli in regions involved in affective processing, with the exception of certain PFC regions; this pattern tends to normalize with treatment.

Cited by 116 publications

References 104 publications

Depressive disorders: Processes leading to neurogeneration and potential novel treatments

Depressive disorders: Processes leading to neurogeneration and potential novel treatments

Amygdala Reactivity to Emotional Faces in the Prediction of General and Medication-Specific Responses to Antidepressant Treatment in the Randomized iSPOT-D Trial

Translational identification of transcriptional signatures of major depression and antidepressant response

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