Disrupted default mode network and executive control network are associated with depression severity on structural...

Area of Science:

• Neuroscience
• Psychiatry
• Medical Imaging

Background:

• Major depressive disorder (MDD) presents challenges in treatment response.
• Understanding the neuroanatomical underpinnings of structural networks in MDD is crucial.
• Investigating the relationship between disease severity and brain structural alterations is essential.

Purpose of the Study:

• To investigate the neuroanatomical mechanisms of structural networks in relation to MDD severity.
• To analyze gray matter volume (GMV) and structural covariance network (SCN) connectivity in first-onset, untreated adult MDD patients.
• To identify specific brain regions and networks associated with different MDD severity levels.

Main Methods:

• Recruited 181 first-onset, untreated adult MDD patients (slight, moderate, heavy) and 81 healthy controls (HC).
• Utilized FreeSurfer for T1 image preprocessing to assess GMV.
• Analyzed the default mode network (DMN) and execution control network (ECN) using SCN.

Main Results:

• Brain region GMV decreased with increasing MDD severity.
• GMV of the left anterior cingulate gyrus (ACC.L) showed a negative correlation with MDD severity.
• SCN connectivity in the whole-brain network increased with MDD severity, with ACC.L being a key region connecting orbitofrontal areas in DMN and ECN.

Conclusions:

• Smaller GMV of ACC.L is associated with a higher likelihood of developing severe MDD.
• ACC.L plays a critical role in both DMN and ECN, exhibiting distinct structural network models.
• MDD patients display varying neuroimaging changes in DMN and ECN depending on disease severity.