Mechanisms underlying the spontaneous reorganization of depression network after stroke

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 R<sup>2</sup> = -0.070, p < 0.001). Reorganization information effectively predicted symptoms at follow-up in the discovery cohort (adjust R<sup>2</sup> = 0.217, 95 %CI: 0.010 to 0.431), as well as symptom exacerbation (r = 0.421, p = 0.033) and treatment responsiveness (r = 0.587, p = 0.012) in the validation cohorts. Regions undergoing significant reorganization overlapped with neuromodulatory targets known to be effective in treating depression. The reorganization of the depression network was associated with immune-inflammatory responses gene expressions and gamma-aminobutyric acid. Our findings may yield important insights into the repair mechanisms of PSD and provide a critical context for developing post-stroke treatment strategies.

Authors

Institutions

Publication Details

Journal
NeuroImage Clinical
Published
2024-12-10
DOI
https://doi.org/10.1016/j.nicl.2024.103723
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mechanisms underlying the spontaneous reorganization of depression network after stroke

Ya‐Nan Lu, Wen He Sun, Yirong Fang, Hongmei Huang et al.
NeuroImage Clinical
Functional Brain Connectivity Studies
article

Mechanisms underlying the spontaneous reorganization of depression network after stroke

Ya‐Nan Lu, Wen He Sun, Yirong Fang, Hongmei Huang, Hao Chen, Dawei Yin, Xinfeng Liu, Ran Shi, Peng Wang, Xian Chao, Jinjing Wang, Zeyu Lu
article en

Abstract

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 R<sup>2</sup> = -0.070, p < 0.001). Reorganization information effectively predicted symptoms at follow-up in the discovery cohort (adjust R<sup>2</sup> = 0.217, 95 %CI: 0.010 to 0.431), as well as symptom exacerbation (r = 0.421, p = 0.033) and treatment responsiveness (r = 0.587, p = 0.012) in the validation cohorts. Regions undergoing significant reorganization overlapped with neuromodulatory targets known to be effective in treating depression. The reorganization of the depression network was associated with immune-inflammatory responses gene expressions and gamma-aminobutyric acid. Our findings may yield important insights into the repair mechanisms of PSD and provide a critical context for developing post-stroke treatment strategies.

NeuroImage ClinicalVol. 45
University of Science and Technology of China (CN), Xuzhou Medical College (CN)
National Natural Science Foundation of China, University of Science and Technology of China, Natural Science Foundation of Anhui Province
Good health and well-being
Openalex Percentile: Top 77%
Functional Brain Connectivity Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.