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

Author:

Chen Vincent Chin-Hung12,Shen Chao-Yu34,Liang Sophie Hsin-Yi15,Li Zhen-Hui3,Hsieh Ming-Hong6,Tyan Yeu-Sheng34,Lu Mong-Liang7,Lee Yena89,McIntyre Roger S.8910,Weng Jun-Cheng23411

Affiliation:

1. School of Medicine, Chang Gung University, Taoyuan, Taiwan

2. Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan

3. Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan

4. Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan

5. Section of Child Psychiatry, Department of Psychiatry, Chang Gung Memorial Hospital at Taoyuan, Taoyuan, Taiwan

6. Department of Psychiatry, Chung Shan Medical University and Hospital, Taichung, Taiwan

7. Department of Psychiatry, Wan Fang Hospital & School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan

8. Mood Disorder Psychopharmacology Unit, University Health Network, Department of Psychiatry, University of Toronto, Toronto, ON, Canada

9. Institute of Medical Science, University of Toronto, Toronto, ON, Canada

10. Departments of Psychiatry and Pharmacology, University of Toronto, Toronto, ON, Canada

11. Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan

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.

Funder

Ministry of Science and Technology, Taipei, Taiwan

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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