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Assessment of brain functional connectome alternations and correlation with depression and anxiety in major depressive disorders.

ABSTRACT: Major depressive disorder (MDD) is highly prevalent, recurrent, and associated with functional impairment, morbidity, and mortality. Herein, we aimed to identify disruptions in functional connectomics among subjects with MDD by using resting-state functional magnetic resonance imaging (rs-fMRI). Sixteen subjects with MDD and thirty health controls completed resting-state fMRI scans and clinical assessments (e.g., Hamilton Depression Rating Scale (HAMD) and Hospital Anxiety and Depression Scale (HADS)). We found higher amplitude of low frequency fluctuations (ALFF) bilaterally in the hippocampus and amygdala among MDD subjects when compared to healthy controls. Using graph theoretical analysis, we found decreased clustering coefficient, local efficiency, and transitivity in the MDD patients. Our findings suggest a potential biomarker for differentiating individuals with MDD from individuals without MDD.

SUBMITTER: Chen VC

PROVIDER: S-EPMC5702252 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Assessment of brain functional connectome alternations and correlation with depression and anxiety in major depressive disorders.

Chen Vincent Chin-Hung VC Shen Chao-Yu CY Liang Sophie Hsin-Yi SH Li Zhen-Hui ZH Hsieh Ming-Hong MH Tyan Yeu-Sheng YS Lu Mong-Liang ML Lee Yena Y McIntyre Roger S RS Weng Jun-Cheng JC

PeerJ 20171122

Major depressive disorder (MDD) is highly prevalent, recurrent, and associated with functional impairment, morbidity, and mortality. Herein, we aimed to identify disruptions in functional connectomics among subjects with MDD by using resting-state functional magnetic resonance imaging (rs-fMRI). Sixteen subjects with MDD and thirty health controls completed resting-state fMRI scans and clinical assessments (e.g., Hamilton Depression Rating Scale (HAMD) and Hospital Anxiety and Depression Scale ( ...[more]

PMID: 29181274

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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:Accumulating data suggest that air pollution increases the risk of internalizing psychopathology, including anxiety and depressive disorders. Moreover, the link between air pollution and poor mental health may relate to neurostructural and neurofunctional changes. We systematically reviewed the MEDLINE database in September 2021 for original articles reporting effects of air pollution on 1) internalizing symptoms and behaviors (anxiety or depression) and 2) frontolimbic brain regions (i.e., hippocampus, amygdala, prefrontal cortex). One hundred and eleven articles on mental health (76% human, 24% animals) and 92 on brain structure and function (11% human, 86% animals) were identified. For literature search 1, the most common pollutants examined were PM2.5 (64.9%), NO2 (37.8%), and PM10 (33.3%). For literature search 2, the most common pollutants examined were PM2.5 (32.6%), O3 (26.1%) and Diesel Exhaust Particles (DEP) (26.1%). The majority of studies (73%) reported higher internalizing symptoms and behaviors with higher air pollution exposure. Air pollution was consistently associated (95% of articles reported significant findings) with neurostructural and neurofunctional effects (e.g., increased inflammation and oxidative stress, changes to neurotransmitters and neuromodulators and their metabolites) within multiple brain regions (24% of articles), or within the hippocampus (66%), PFC (7%), and amygdala (1%). For both literature searches, the most studied exposure time frames were adulthood (48% and 59% for literature searches 1 and 2, respectively) and the prenatal period (26% and 27% for literature searches 1 and 2, respectively). Forty-three percent and 29% of studies assessed more than one exposure window in literature search 1 and 2, respectively. The extant literature suggests that air pollution is associated with increased depressive and anxiety symptoms and behaviors, and alterations in brain regions implicated in risk of psychopathology. However, there are several gaps in the literature, including: limited studies examining the neural consequences of air pollution in humans. Further, a comprehensive developmental approach is needed to examine windows of susceptibility to exposure and track the emergence of psychopathology following air pollution exposure.

Dataset Information

Assessment of brain functional connectome alternations and correlation with depression and anxiety in major depressive disorders.

Publications

Assessment of brain functional connectome alternations and correlation with depression and anxiety in major depressive disorders.

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