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Disrupted brain structural networks associated with depression and cognitive dysfunction in cerebral small vessel disease with microbleeds

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机构: [1]Department of Radiology, Shandong Provincial Hospital, Shandong University, Jing-wu Road No. 324, Jinan, Shandong 250021, China [2]Department of Radiology and Nuclear medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-chun St, Xicheng District, Beijing, China [3] Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China [4]Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, 16766 Jing-shi Road,Jinan 250014,China [5]Research Center for Brain-inspired Intelligence Institute of Automation, Chinese Academy of Sciences, ZhongGuanCun East Rd. 95#, Beijing 100190, China [6]Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing 400715, China
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关键词: Cerebral small vessel disease Cerebral microbleeds Diffusion tensor imaging Probabilistic tractography Network efficiency

摘要:
Emerging evidence highlights cerebral microbleeds (CMBs) as hallmarks of cerebral small vessel disease (CSVD) underlying depression and cognitive dysfunction. This study aimed to reveal how depression and cognition-related white matter (WM) abnormalities are topologically presented, and the network-level structural disruptions associated with CMBs in CSVD. We used probabilistic diffusion tractography and graph theory to investigate brain WM network topology in CSVD patients with (n = 64, CSVD-c) and without (n = 138, CSVD-n) CMBs and 90 healthy controls. Then we evaluated the Pearson's correlations between disrupted network metrics and neuropsychological parameters. For global topology, the CSVD-c group exhibited significantly decreased global (Eglob) and local (Eloc) efficiency and increased shortest path length compared with the controls, while no significant difference was found between the CSVD-c and CSVD-n groups. For regional topology, although all groups showed highly similar hub distributions, compare with control group, the CSVD-c group exhibited significantly decreased nodal efficiency mainly in the bilateral supplementary motor area (SMA), median cingulate gyrus (DCG) and right orbital middle frontal gyrus, while the CSVD-n group showed significantly decreased nodal efficiency only in the right SMA. Notably, Eglob, Eloc and nodal efficiency of the right anterior cingulate gyrus, DCG, middle temporal gyrus and left insula showed significantly negative correlations with depression score, significantly positive correlations with Rey auditory verbal learning test and symbol digit modalities test scores in CSVD-n group, as well as significantly negative correlations with Stroop color-word test scores in CSVD-c group. The WM networks of CSVD patients are characterized by decreased global integration and local specialization, and decreased nodal efficiency highly related to depression and cognitive dysfunction in the attention, default mode network and sensorimotor regions. These findings provide new insight into the neurobiological mechanisms of CSVD and concomitant affective and cognitive disorders.Copyright © 2024. Published by Elsevier Inc.

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出版当年[2023]版:
大类 | 2 区 医学
小类 | 2 区 临床神经病学 2 区 神经科学 2 区 药学 2 区 精神病学
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 临床神经病学 2 区 神经科学 2 区 药学 2 区 精神病学
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出版当年[2022]版:
Q1 CLINICAL NEUROLOGY Q1 NEUROSCIENCES Q1 PHARMACOLOGY & PHARMACY Q2 PSYCHIATRY
最新[2023]版:
Q1 CLINICAL NEUROLOGY Q1 NEUROSCIENCES Q1 PHARMACOLOGY & PHARMACY Q1 PSYCHIATRY

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第一作者机构: [1]Department of Radiology, Shandong Provincial Hospital, Shandong University, Jing-wu Road No. 324, Jinan, Shandong 250021, China [2]Department of Radiology and Nuclear medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-chun St, Xicheng District, Beijing, China
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