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Network Pharmacology and Validation of the Antidepressant Mechanisms of Qiangzhifang in a Chronic Restraint Stress-induced Depression Rat Model
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Altered Dynamic Network Stability in Remitted Late-Life Depression Associated With Depression Recurrence.

Damek Homiack1, Brian Boyd2, Aifeng Zhang1

  • 1Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois.

Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
|September 7, 2025
PubMed
Summary
This summary is machine-generated.

Late-life depression (LLD) disrupts brain network stability, impacting cognitive function and increasing recurrence risk. These network changes persist even after remission, offering potential biomarkers for predicting future depressive episodes.

Keywords:
CognitionDynamic functional connectivityEarly remissionLate-life depressionRecurrenceRumination

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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.