Influence of depression severity on interhemispheric functional integration: an analysis from the REST-meta-MDD
Jie Ding1, Junfeng Peng2, Qian Zhang3
1College Student Mental Health Education Center, Xinyang Vocational and Technical College, Xinyang, China.
Brain Imaging and Behavior
|November 29, 2024
Summary
Voxel-mirrored homotopic connectivity (VMHC) using fMRI can differentiate major depressive disorder (MDD) severity. Reduced VMHC in certain brain areas and increased connectivity in others correlate with depression levels, aiding diagnosis.
Area of Science:
- Neuroimaging
- Psychiatry
- Brain Connectivity
Background:
- Major Depressive Disorder (MDD) significantly impacts daily functioning, necessitating accurate severity stratification for effective treatment.
- Resting-state functional magnetic resonance imaging (fMRI) offers potential neuroimaging biomarkers for MDD assessment.
Purpose of the Study:
- To evaluate voxel-mirrored homotopic connectivity (VMHC) as a neuroimaging biomarker for differentiating MDD severity.
- To investigate VMHC differences between mild-to-moderate and severe MDD patients and their correlation with depression scores.
Main Methods:
- Analysis of resting-state fMRI data from 392 first-episode MDD patients and 440 healthy controls (HC) from the REST-meta-MDD project.
- Classification of MDD patients into mild-to-moderate and severe groups using Hamilton Depression Scale (HAMD) scores.
- Examination of VMHC differences and correlation with HAMD scores, including Receiver Operating Characteristic (ROC) curve analysis.
Main Results:
- Significant VMHC reductions observed in the fusiform gyrus (mild-to-moderate MDD vs. HC) and extended to the insula, postcentral, and angular gyri (severe MDD).
- Increased VMHC in the middle cingulate cortex was found in severe MDD patients compared to mild-to-moderate MDD patients, positively correlating with HAMD scores.
- VMHC effectively differentiated MDD patients from HCs and across different depression severity levels.
Conclusions:
- VMHC serves as a promising neuroimaging biomarker for clinical diagnosis and stratification of MDD severity.
- Findings provide insights into the neurobiological underpinnings of MDD severity.
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