Causal structural covariance network identifies progressive gray matter atrophy in adolescents with major depressive disorder
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View abstract on PubMed
Summary
This summary is machine-generated.Adolescent depression involves gray matter atrophy, starting in specific brain areas like the vmPFC and spreading with illness duration. These initial changes impact major brain networks, highlighting progression in major depressive disorder (MDD).
Area Of Science
- Neuroscience
- Psychiatry
- Developmental Psychology
Background
- Adolescence is a critical period for the onset of major depressive disorder (MDD).
- Gray matter atrophy is observed in MDD patients, but the underlying causal structural networks are unclear.
- Understanding these networks is crucial for identifying early brain alterations in depressed adolescents.
Purpose Of The Study
- To examine initial gray matter alterations in adolescents with MDD.
- To investigate the causal relationships of these abnormalities within brain structural networks.
- To identify potential pathways between causal sources and targets of brain abnormalities.
Main Methods
- Voxel-based morphometry (VBM) was used to analyze T1-weighted structural MRI scans.
- Granger causality analysis (GCA) was employed to construct causal structural covariance networks.
- First-episode adolescent MDD patients (n=80) and healthy controls (n=82) were compared.
Main Results
- MDD patients showed gray matter atrophy in the ventral medial prefrontal cortex (vmPFC), anterior cingulate cortex, and insula, especially with shorter illness duration.
- Gray matter atrophy extended to widespread brain areas with prolonged MDD.
- Early abnormalities positively affected default mode, frontoparietal, and reward networks, with vmPFC identified as a potential initial source.
Conclusions
- Gray matter atrophy progresses in adolescent depression, starting locally and affecting widespread networks.
- Initial localized brain alterations have directional influences on subsequent network deterioration.
- Findings elucidate the progression and causal network dynamics of brain abnormalities in adolescent MDD.
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