Dataset Information

Brain mechanisms of anxiety's effects on cognitive control in major depressive disorder.

ABSTRACT: Adults with major depressive disorder (MDD) demonstrate increased susceptibility to interfering effects of anxiety on cognitive control; although under certain conditions adults with MDD are able to compensate for these effects. The brain mechanisms that may facilitate the ability to compensate for anxiety either via the recruitment of additional cognitive resources or via the regulation of interference from anxiety remain largely unknown. To clarify these mechanisms, we examined the effects of anxiety on brain activity and amygdala-prefrontal functional connectivity in adults diagnosed with MDD.A total of 22 unmedicated adults with MDD and 18 healthy controls (HCs) performed the Tower of London task under conditions designed to induce anxiety, while undergoing a functional magnetic resonance imaging assessment.During the easy condition, the MDD group demonstrated equivalent planning accuracy, longer planning times, elevated amygdala activity and left rostrolateral prefrontal cortex (RLPFC) hyperactivity relative to HCs. Anxiety mediated observed group differences in planning times, as well as differences in amygdala activation, which subsequently mediated observed differences in RLPFC activation. During the easy condition, the MDD group also demonstrated increased negative amygdala-dorsolateral prefrontal cortex (DLPFC) connectivity which correlated with improved planning accuracy. During the hard condition, HCs demonstrated greater DLPFC activation and stronger negative amygdala-DLPFC connectivity, which was unrelated to planning accuracy.Our results suggest that persons with MDD compensate for anxiety-related limbic activation during low-load cognitive tasks by recruiting additional RLPFC activation and through increased inhibitory amygdala-DLPFC communication. Targeting these neural mechanisms directly may improve cognitive functioning in MDD.

SUBMITTER: Jones NP

PROVIDER: S-EPMC4946974 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Brain mechanisms of anxiety's effects on cognitive control in major depressive disorder.

Jones N P NP Chase H W HW Fournier J C JC

Psychological medicine 20160613 11

<h4>Background</h4>Adults with major depressive disorder (MDD) demonstrate increased susceptibility to interfering effects of anxiety on cognitive control; although under certain conditions adults with MDD are able to compensate for these effects. The brain mechanisms that may facilitate the ability to compensate for anxiety either via the recruitment of additional cognitive resources or via the regulation of interference from anxiety remain largely unknown. To clarify these mechanisms, we exami ...[more]

PMID: 27291341

Similar Datasets

Project description:BackgroundCognitive dysfunction and brain structural connectivity alterations have been observed in major depressive disorder (MDD). However, little is known about their interrelation. The present study follows a network approach to evaluate alterations in cognition-related brain structural networks.MethodsCognitive performance of n = 805 healthy and n = 679 acutely depressed or remitted individuals was assessed using 14 cognitive tests aggregated into cognitive factors. The structural connectome was reconstructed from structural and diffusion-weighted magnetic resonance imaging. Associations between global connectivity strength and cognitive factors were established using linear regressions. Network-based statistics were applied to identify subnetworks of connections underlying these global-level associations. In exploratory analyses, effects of depression were assessed by evaluating remission status-related group differences in subnetwork-specific connectivity. Partial correlations were employed to directly test the complete triad of cognitive factors, depressive symptom severity, and subnetwork-specific connectivity strength.ResultsAll cognitive factors were associated with global connectivity strength. For each cognitive factor, network-based statistics identified a subnetwork of connections, revealing, for example, a subnetwork positively associated with processing speed. Within that subnetwork, acutely depressed patients showed significantly reduced connectivity strength compared to healthy controls. Moreover, connectivity strength in that subnetwork was associated to current depressive symptom severity independent of the previous disease course.ConclusionsOur study is the first to identify cognition-related structural brain networks in MDD patients, thereby revealing associations between cognitive deficits, depressive symptoms, and reduced structural connectivity. This supports the hypothesis that structural connectome alterations may mediate the association of cognitive deficits and depression severity.

Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Project description:BackgroundMajor depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Cognitive therapy may be an effective treatment option for major depressive disorder, but the effects have only had limited assessment in systematic reviews.Methods/principal findingsWe used The Cochrane systematic review methodology with meta-analyses and trial sequential analyses of randomized trials comparing the effects of cognitive therapy versus 'no intervention' for major depressive disorder. Participants had to be older than 17 years with a primary diagnosis of major depressive disorder to be eligible. Altogether, we included 12 trials randomizing a total of 669 participants. All 12 trials had high risk of bias. Meta-analysis on the Hamilton Rating Scale for Depression showed that cognitive therapy significantly reduced depressive symptoms (four trials; mean difference -3.05 (95% confidence interval (Cl), -5.23 to -0.87; P<0.006)) compared with 'no intervention'. Trial sequential analysis could not confirm this result. Meta-analysis on the Beck Depression Inventory showed that cognitive therapy significantly reduced depressive symptoms (eight trials; mean difference on -4.86 (95% CI -6.44 to -3.28; P = 0.00001)). Trial sequential analysis on these data confirmed the result. Only a few trials reported on 'no remission', suicide inclination, suicide attempts, suicides, and adverse events without significant differences between the compared intervention groups.DiscussionCognitive therapy might be an effective treatment for depression measured on Hamilton Rating Scale for Depression and Beck Depression Inventory, but these outcomes may be overestimated due to risks of systematic errors (bias) and random errors (play of chance). Furthermore, the effects of cognitive therapy on no remission, suicidality, adverse events, and quality of life are unclear. There is a need for randomized trials with low risk of bias, low risk of random errors, and longer follow-up assessing both benefits and harms with clinically relevant outcome measures.

Dataset Information

Brain mechanisms of anxiety's effects on cognitive control in major depressive disorder.

Publications

Brain mechanisms of anxiety's effects on cognitive control in major depressive disorder.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets