Network-level disconnectivity tracks poststroke depressive symptom improvement.

IF 5.9 3区 医学 Q1 CLINICAL NEUROLOGY
Psychiatry and Clinical Neurosciences Pub Date : 2026-08-01 Epub Date: 2026-05-14 DOI:10.1111/pcn.70075
Aleksi J Sihvonen, Sonia L E Brownsett, David A Copland, Alistair Walsh, Stephen M Davis, Geoffrey A Donnan, Leeanne M Carey
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引用次数: 0

Abstract

Aims: Poststroke depression is the most common psychological condition following a stroke and can severely impact outcome. However, the neurobiological biomarkers associated with recovery of poststroke depression remain unclear. In this longitudinal observational study, we set out to investigate the effect of lesion-induced focal damage and network-level disconnectivity, and longitudinal structural connectivity on poststroke depression and its recovery.

Methods: Sixty-two participants underwent a psychological assessment utilizing the Montgomery-Asberg Depression Rating Scale (MADRS-SIGMA) at 3 and 12 months post first-ever stroke. First, we evaluated the relationship between lesions and MADRS scores at the 3 months using voxel-based lesion-symptom mapping and lesion network mapping. Next, we assessed the longitudinal relationship between structural connectivity and MADRS scores (change from 3 to 12 months) using multi-shell diffusion-weighted MRI data (n = 29) collected at both timepoints.

Results: Patient lesions mapped to a connected brain network centered on the left dorsolateral prefrontal cortex (PFDR <0.05). Longitudinal diffusion MRI analysis revealed that increased quantitative anisotropy in the identified structural network was associated with improved depressive symptoms longitudinally (P = 0.014), independent of demographic and clinical covariates. Significant associations between the lesions and focal brain structures were not identified.

Conclusions: Depressive symptoms and their improvement mapped to a specific structural brain network. Knowledge of the integrity of this network could prove useful for predicting poststroke depression.

Clinical trial registration: START-PrePARE Australian New Zealand Clinical Trials, www.anzctr.org.au, Registry number: ACTRN12610000987066. EXTEND ClinicalTrial.gov identifier: NCT00887328.

网络水平的断连追踪中风后抑郁症状的改善。
目的:卒中后抑郁是卒中后最常见的心理状况,并可严重影响预后。然而,与中风后抑郁恢复相关的神经生物学生物标志物仍不清楚。在这项纵向观察研究中,我们着手研究损伤引起的局灶性损伤和网络水平的失联,以及纵向结构连通性对脑卒中后抑郁及其恢复的影响。方法:62名参与者在首次中风后3个月和12个月采用蒙哥马利-阿斯伯格抑郁评定量表(MADRS-SIGMA)进行心理评估。首先,我们使用基于体素的病变症状映射和病变网络映射来评估病变与3个月时MADRS评分之间的关系。接下来,我们使用在两个时间点收集的多壳扩散加权MRI数据(n = 29)评估结构连通性与MADRS评分之间的纵向关系(从3个月到12个月的变化)。结果:患者病变映射到以左背外侧前额叶皮层为中心的连接脑网络(PFDR)。结论:抑郁症状及其改善映射到一个特定的结构脑网络。了解这个网络的完整性对预测中风后抑郁是有用的。临床试验注册:START-PrePARE Australian New Zealand Clinical Trials, www.anzctr.org.au,注册号:ACTRN12610000987066。EXTEND ClinicalTrial.gov标识符:NCT00887328。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.40
自引率
4.20%
发文量
181
审稿时长
6-12 weeks
期刊介绍: PCN (Psychiatry and Clinical Neurosciences) Publication Frequency: Published 12 online issues a year by JSPN Content Categories: Review Articles Regular Articles Letters to the Editor Peer Review Process: All manuscripts undergo peer review by anonymous reviewers, an Editorial Board Member, and the Editor Publication Criteria: Manuscripts are accepted based on quality, originality, and significance to the readership Authors must confirm that the manuscript has not been published or submitted elsewhere and has been approved by each author
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