Local connections enhancement as a neuroprotective strategy against depression recurrence: Insights from structural...

Depression recurrence significantly impacts patients' well-being and presents a major clinical challenge. Identifying the risk of recurrence during remission could enable early intervention and prevent disease progression.

This study included 115 patients in remission from their first depressive episode and 47 healthy controls (HCs). Participants underwent diffusion tensor imaging (DTI), neuropsychological assessments, and follow-up evaluations every three months over a two-year period. Structural brain networks were constructed using deterministic fiber tracking and graph theory analysis.

Non-recurrence patients exhibited significantly higher baseline local connections compared to the recurrence group (t = 8.148; P < 0.001), which emerged as a robust negative predictor of recurrence (AUC = 0.853 [95 % CI: 0.774-0.912]; OR = 0.594 [95 % CI: 0.489-0.722]; P < 0.001). Rich-club connections were inversely correlated with depression severity (r = -0.510; P < 0.001) and duration (r = -0.221; P = 0.018). Additionally, increases in local connections during remission correlated positively with subsequent rich-club connections (r = 0.540; P < 0.05).

Elevated local connections during remission after the first depressive episode significantly reduce the risk of recurrence. This suggests a compensatory neuroprotective mechanism, where enhanced local connections stabilize rich-club connections, thereby maintaining the integrity of the whole-brain network. These findings highlight local connections as a critical factor in preventing depression recurrence and as a potential target for early clinical intervention.