Journal
PEERJ
Volume 5, Issue -, Pages -Publisher
PEERJ INC
DOI: 10.7717/peerj.3147
Keywords
Functional connectome; Graph theoretical analysis; Resting-state functional magnetic resonance imaging; Major depressive disorder
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Funding
- Ministry of Science and Technology, Taipei, Taiwan [MOST105-2314-B-182-028, NSC102-2314-B-040-004-MY3, MOST104-2314-B-040-001]
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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 DD 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.
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