Altered Dynamic Network Stability in Remitted Late-Life Depression Associated With Depression Recurrence

Area of Science:

• Neuroscience
• Gerontology
• Psychiatry

Background:

• Late-life depression (LLD) is linked to poor outcomes like recurrence and cognitive decline.
• The underlying neurobiology of these outcomes in LLD remains unclear.
• Disruptions in large-scale brain networks may underlie LLD-related cognitive impairment.

Purpose of the Study:

• To investigate neurobiological changes in brain network dynamics associated with late-life depression (LLD).
• To compare brain network properties in never-depressed individuals, those in remission from LLD, and those who experience depression recurrence.

Main Methods:

• Recruited never-depressed older adults and individuals in early remission from LLD (REMBRANDT study).
• Collected resting-state fMRI and neuropsychological data at baseline, monitoring for 2 years.
• Utilized k-means consensus clustering to identify recurring whole-brain network states and compared network properties.

Main Results:

• A 3-network model (default mode, cognitive control, anterior salience) best described network states.
• Remitted LLD participants showed reduced network resilience and altered network transitions compared to controls.
• Network stability correlated with clinical/neuropsychological markers in controls and remitted individuals, but this association was weaker in those with recurrent LLD.

Conclusions:

• LLD significantly alters dynamic brain network stability, with lasting effects into remission.
• Altered network stability and its association with clinical markers may predict LLD recurrence risk.