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Resting-state connectivity predictors of response to psychotherapy in major depressive disorder.

ABSTRACT: Despite the heterogeneous symptom presentation and complex etiology of major depressive disorder (MDD), functional neuroimaging studies have shown with remarkable consistency that dysfunction in mesocorticolimbic brain systems are central to the disorder. Relatively less research has focused on the identification of biological markers of response to antidepressant treatment that would serve to improve the personalized delivery of empirically supported antidepressant interventions. In the present study, we investigated whether resting-state functional brain connectivity (rs-fcMRI) predicted response to Behavioral Activation Treatment for Depression, an empirically validated psychotherapy modality designed to increase engagement with rewarding stimuli and reduce avoidance behaviors. Twenty-three unmedicated outpatients with MDD and 20 matched nondepressed controls completed rs-fcMRI scans after which the MDD group received an average of 12 sessions of psychotherapy. The mean change in Beck Depression Inventory-II scores after psychotherapy was 12.04 points, a clinically meaningful response. Resting-state neuroimaging data were analyzed with a seed-based approach to investigate functional connectivity with four canonical resting-state networks: the default mode network, the dorsal attention network, the executive control network, and the salience network. At baseline, the MDD group was characterized by relative hyperconnectivity of multiple regions with precuneus, anterior insula, dorsal anterior cingulate cortex (dACC), and left dorsolateral prefrontal cortex seeds and by relative hypoconnectivity with intraparietal sulcus, anterior insula, and dACC seeds. Additionally, connectivity of the precuneus with the left middle temporal gyrus and connectivity of the dACC with the parahippocampal gyrus predicted the magnitude of pretreatment MDD symptoms. Hierarchical linear modeling revealed that response to psychotherapy in the MDD group was predicted by pretreatment connectivity of the right insula with the right middle temporal gyrus and the left intraparietal sulcus with the orbital frontal cortex. These results add to the nascent body of literature investigating pretreatment rs-fcMRI predictors of antidepressant treatment response and is the first study to examine rs-fcMRI predictors of response to psychotherapy.

SUBMITTER: Crowther A

PROVIDER: S-EPMC4915248 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Resting-state connectivity predictors of response to psychotherapy in major depressive disorder.

Crowther Andrew A Smoski Moria J MJ Minkel Jared J Moore Tyler T Gibbs Devin D Petty Chris C Bizzell Josh J Schiller Crystal Edler CE Sideris John J Carl Hannah H Dichter Gabriel S GS

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 20150112 7

Despite the heterogeneous symptom presentation and complex etiology of major depressive disorder (MDD), functional neuroimaging studies have shown with remarkable consistency that dysfunction in mesocorticolimbic brain systems are central to the disorder. Relatively less research has focused on the identification of biological markers of response to antidepressant treatment that would serve to improve the personalized delivery of empirically supported antidepressant interventions. In the present ...[more]

PMID: 25578796

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Project description:ImportanceMajor depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive.ObjectiveTo investigate network dysfunction in MDD through a meta-analysis of rsFC studies.Data sourcesSeed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data.Study selectionTwenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis.Data extraction and synthesisCoordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network.ResultsMajor depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions.Conclusions and relevanceReduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.

Project description:BACKGROUND:Although dysfunction of amygdala-related circuits is centrally implicated in major depressive disorder (MDD), little is known about how this dysfunction differs between adult and adolescent MDD patients. METHODS:Voxel-wise meta-analyses of abnormal amygdala resting-state functional connectivity (rsFC) were conducted in adult and adolescent groups separately, followed by a quantitative meta-analytic comparison of the two groups. FINDINGS:Nineteen studies that included 665 MDD patients (392 adults and 273 adolescents) and 546 controls (341 adults and 205 adolescents) were identified in the current study. Adult-specific abnormal amygdala rsFC in MDD patients compared to that in controls was located mainly within the affective network, including increased connectivity with the right hippocampus/parahippocampus and bilateral ventromedial orbitofrontal cortex and decreased connectivity with the bilateral insula and the left caudate. Adolescent MDD patients specifically demonstrated decreased amygdala rsFC within the cognitive control network encompassing the left dorsolateral prefrontal cortex and imbalanced amygdala rsFC within the default mode network, which was manifested as hyperconnectivity in the right precuneus and hypoconnectivity in the right inferior temporal gyrus. Additionally, direct comparison between the two groups showed that adult patients had strengthened amygdala rsFC with the right hippocampus/parahippocampus as well as the right inferior temporal gyrus and weakened amygdala rsFC with the bilateral insula compared to that in adolescent patients. INTERPRETATION:Distinct impairments of amygdala-centered rsFC in adult and adolescent patients were related to different network dysfunctions in MDD. Adult-specific amygdala rsFC dysfunction within the affective network presumably reflects emotional dysregulation in MDD, whereas adolescent-specific amygdala rsFC abnormalities in networks involved in cognitive control might reflect the neural basis of affective cognition deficiency that is characteristic of adolescent MDD. FUND: This study was supported by a grant from the National Natural Science Foundation of China (81671669) and by a Sichuan Provincial Youth Grant (2017JQ0001).

Dataset Information

Resting-state connectivity predictors of response to psychotherapy in major depressive disorder.

Publications

Resting-state connectivity predictors of response to psychotherapy in major depressive disorder.

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