Mechanisms underlying the spontaneous reorganization of depression network after stroke

• Published in: NeuroImage clinical 2024-12, Vol.45, p.103723, Article 103723
• Main Authors: Fang, Yirong, Chao, Xian, Lu, Zeyu, Huang, Hongmei, Shi, Ran, Yin, Dawei, Chen, Hao, Lu, Yanan, Wang, Jinjing, Wang, Peng, Liu, Xinfeng, Sun, Wen
• Format: Article
• Language: English
• Subjects: Stroke depression treat FMRI transcription neurotransmitter
• ISSN: 2213-1582; 2213-1582
• DOI: 10.1016/j.nicl.2024.103723

[Display omitted] •We utilized longitudinal data from poststroke patients to investigate the spontaneous reorganization mechanisms of depression network.•By employing stepwise functional connectivity analysis, we investigated topological changes in depression networks.•We used data from patients with worsening depressive symptoms to validate the reorganization mechanisms in reverse.•We validated the therapeutic implications of reorganization mechanisms using patients with antidepressants, along with neuroregulatory targets.•Utilizing the Allen and PET atlases, we explored the neurobiological underpinnings of the reorganization within the depression network. Exploring the causal relationship between focal brain lesions and post-stroke depression (PSD) can provide therapeutic insights. However, a gap exists between causal and therapeutic information. Exploring post-stroke brain repair processes post-stroke could bridge this gap. We defined a depression network using the normative connectome and investigated the predictive capacity of lesion-induced network damage on depressive symptoms in discovery cohort of 96 patients, at baseline and six months post-stroke. Stepwise functional connectivity (SFC) was used to examine topological changes in the depression network over time to identify patterns of network reorganization. The predictive value of reorganization information was evaluated for follow-up symptoms in discovery and validation cohort 1 (22 worsening PSD patients) as well as for treatment responsiveness in validation cohort 2 (23 antidepressant-treated patients). We evaluated the consistency of significant reorganization areas with neuromodulation targets. Spatial correlations of network reorganization patterns with gene expression and neurotransmitter maps were analyzed. The predictive power of network damage for symptoms diminished at follow-up compared to baseline (Δadjusted R2 = -0.070, p