• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

系统性红斑狼疮的脑网络重组和空间病变分布。

Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.

机构信息

Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.

UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.

出版信息

Lupus. 2021 Feb;30(2):285-298. doi: 10.1177/0961203320979045. Epub 2020 Dec 13.

DOI:10.1177/0961203320979045
PMID:33307988
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7854491/
Abstract

OBJECTIVE

This work investigates network organisation of brain structural connectivity in systemic lupus erythematosus (SLE) relative to healthy controls and its putative association with lesion distribution and disease indicators.

METHODS

White matter hyperintensity (WMH) segmentation and connectomics were performed in 47 patients with SLE and 47 healthy age-matched controls from structural and diffusion MRI data. Network nodes were divided into hierarchical tiers based on numbers of connections. Results were compared between patients and controls to assess for differences in brain network organisation. Voxel-based analyses of the spatial distribution of WMH in relation to network measures and SLE disease indicators were conducted.

RESULTS

Despite inter-individual differences in brain network organization observed across the study sample, the connectome networks of SLE patients had larger proportion of connections in the peripheral nodes. SLE patients had statistically larger numbers of links in their networks with generally larger fractional anisotropy weights (i.e. a measure of white matter integrity) and less tendency to aggregate than those of healthy controls. The voxels exhibiting connectomic differences were coincident with WMH clusters, particularly the left hemisphere's intersection between the anterior limb of the internal and external capsules. Moreover, these voxels also associated more strongly with disease indicators.

CONCLUSION

Our results indicate network differences reflective of compensatory reorganization of the neural circuits, reflecting adaptive or extended neuroplasticity in SLE.

摘要

目的

本研究旨在探讨系统性红斑狼疮(SLE)患者脑结构连接的网络组织与健康对照者的差异,及其与病变分布和疾病指标的潜在关联。

方法

对 47 例 SLE 患者和 47 例年龄匹配的健康对照者的结构和弥散 MRI 数据进行了脑白质高信号(WMH)分割和连接组学分析。根据连接数量将网络节点分为层次级别。比较患者和对照组之间的脑网络组织差异。对 WMH 在空间分布与网络测量和 SLE 疾病指标之间的关系进行了体素基分析。

结果

尽管在整个研究样本中观察到个体间脑网络组织存在差异,但 SLE 患者的连接组网络具有更大比例的外围节点连接。SLE 患者的网络中存在统计学上更多的连接,且它们的网络具有更大的分数各向异性权重(即衡量白质完整性的指标),且比健康对照组的连接更不容易聚集。表现出连接组差异的体素与 WMH 簇重合,特别是左半球内囊前肢与外囊之间的交点。此外,这些体素与疾病指标的关联也更强。

结论

我们的结果表明,网络差异反映了神经网络的代偿性重组,反映了 SLE 中适应性或扩展的神经可塑性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/5b7896d81c28/10.1177_0961203320979045-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/dac1d11733b6/10.1177_0961203320979045-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/3aedc3227673/10.1177_0961203320979045-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/67cc91af3088/10.1177_0961203320979045-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/5b7896d81c28/10.1177_0961203320979045-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/dac1d11733b6/10.1177_0961203320979045-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/3aedc3227673/10.1177_0961203320979045-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/67cc91af3088/10.1177_0961203320979045-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/704c/7859664/5b7896d81c28/10.1177_0961203320979045-fig4.jpg

相似文献

1
Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.系统性红斑狼疮的脑网络重组和空间病变分布。
Lupus. 2021 Feb;30(2):285-298. doi: 10.1177/0961203320979045. Epub 2020 Dec 13.
2
Structural and functional brain connectomes in patients with systemic lupus erythematosus.系统性红斑狼疮患者的结构和功能脑连接组。
Eur J Neurol. 2020 Jan;27(1):113-e2. doi: 10.1111/ene.14041. Epub 2019 Aug 8.
3
Impairment of white matter microstructure and structural network in patients with systemic lupus erythematosus.系统性红斑狼疮患者白质微结构和结构网络的损伤
Semin Arthritis Rheum. 2025 Apr;71:152620. doi: 10.1016/j.semarthrit.2024.152620. Epub 2024 Dec 22.
4
Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus.系统性红斑狼疮的认知功能、疾病负担与结构连接组
Lupus. 2018 Jul;27(8):1329-1337. doi: 10.1177/0961203318772666. Epub 2018 May 3.
5
White-matter integrity in patients with systemic lupus erythematosus and memory deficits.系统性红斑狼疮患者的白质完整性与记忆缺陷
Neuroradiol J. 2018 Dec;31(6):587-595. doi: 10.1177/1971400918793601. Epub 2018 Aug 9.
6
MR Diffusion Tractography to Identify and Characterize Microstructural White Matter Tract Changes in Systemic Lupus Erythematosus Patients.磁共振扩散张量成像用于识别和表征系统性红斑狼疮患者脑白质微结构的改变
Acad Radiol. 2016 Nov;23(11):1431-1440. doi: 10.1016/j.acra.2016.03.019. Epub 2016 Oct 13.
7
Diminished white matter integrity in patients with systemic lupus erythematosus.系统性红斑狼疮患者的脑白质完整性降低。
Neuroimage Clin. 2014 Jul 10;5:291-7. doi: 10.1016/j.nicl.2014.07.001. eCollection 2014.
8
Functional Brain Network Alterations in Patients With Systemic Lupus Erythematosus With Different Cognitive Function States: A Graph Theory Analysis Study.不同认知功能状态的系统性红斑狼疮患者的脑功能网络改变:一项图论分析研究
J Comput Assist Tomogr. 2024;48(2):283-291. doi: 10.1097/RCT.0000000000001546. Epub 2023 Aug 23.
9
White matter lesions and brain atrophy in systemic lupus erythematosus patients: correlation to cognitive dysfunction in a cohort of systemic lupus erythematosus patients using different definition models for neuropsychiatric systemic lupus erythematosus.系统性红斑狼疮患者的白质病变与脑萎缩:在一组使用不同神经精神性系统性红斑狼疮定义模型的系统性红斑狼疮患者中与认知功能障碍的相关性
Lupus. 2018 Jun;27(7):1140-1149. doi: 10.1177/0961203318763533. Epub 2018 Mar 9.
10
Tract-based white matter hyperintensity patterns in patients with systemic lupus erythematosus using an unsupervised machine learning approach.采用无监督机器学习方法分析系统性红斑狼疮患者的基于束状的脑白质高信号模式。
Sci Rep. 2022 Dec 9;12(1):21376. doi: 10.1038/s41598-022-25990-w.

引用本文的文献

1
Relative Strength Variability Measures for Brain Structural Connectomes and Their Relationship With Cognitive Functioning.脑结构连接组的相对强度变异性测量及其与认知功能的关系
Hum Brain Mapp. 2025 Aug 1;46(11):e70314. doi: 10.1002/hbm.70314.
2
Relative strength variability measures for brain structural connectomes and their relationship with cognitive functioning.脑结构连接组的相对强度变异性测量及其与认知功能的关系。
bioRxiv. 2025 Mar 16:2025.03.15.643458. doi: 10.1101/2025.03.15.643458.
3
MRI-based neuroimaging alterations in immune-related skin diseases: a comprehensive review.

本文引用的文献

1
Hierarchical Complexity of the Macro-Scale Neonatal Brain.宏观尺度新生儿大脑的层次复杂性。
Cereb Cortex. 2021 Mar 5;31(4):2071-2084. doi: 10.1093/cercor/bhaa345.
2
Spatial Gradient of Microstructural Changes in Normal-Appearing White Matter in Tracts Affected by White Matter Hyperintensities in Older Age.老年白质高信号影响区域中正常表现白质微结构变化的空间梯度
Front Neurol. 2019 Jul 25;10:784. doi: 10.3389/fneur.2019.00784. eCollection 2019.
3
Structural and functional brain connectomes in patients with systemic lupus erythematosus.
基于磁共振成像的免疫相关性皮肤病神经影像学改变:一项综述
Arch Dermatol Res. 2025 Mar 8;317(1):529. doi: 10.1007/s00403-025-04023-2.
4
Organ-based characterization of B cells in patients with systemic lupus erythematosus.系统性红斑狼疮患者B细胞的器官特异性特征分析
Front Immunol. 2025 Jan 23;16:1509033. doi: 10.3389/fimmu.2025.1509033. eCollection 2025.
5
Abnormal Functional Hierarchies of EEG Networks in Familial and Sporadic Prodromal Alzheimer's Disease During Visual Short-Term Memory Binding.家族性和散发性前驱阿尔茨海默病在视觉短期记忆绑定过程中脑电图网络的异常功能层次结构
Front Neuroimaging. 2022 Jun 17;1:883968. doi: 10.3389/fnimg.2022.883968. eCollection 2022.
6
Relationship between carotid intima-media thickness (cIMT) and dual-system imbalance in tobacco dependence: An rs-fMRI research.颈动脉内膜中层厚度(cIMT)与烟草依赖双系统失衡的关系:一项 rs-fMRI 研究。
Brain Behav. 2023 Jul;13(7):e3059. doi: 10.1002/brb3.3059. Epub 2023 Jun 12.
7
Paranasal sinus occupancy assessed from magnetic resonance images-associations with clinical indicators in patients with systemic lupus erythematosus.鼻窦磁共振成像评估-系统性红斑狼疮患者的临床指标相关性。
Rheumatology (Oxford). 2024 Jan 4;63(1):149-157. doi: 10.1093/rheumatology/kead185.
8
Cerebral Microstructure Analysis by Diffusion-Based MRI in Systemic Lupus Erythematosus: Lessons Learned and Research Directions.基于扩散加权磁共振成像的系统性红斑狼疮脑微观结构分析:经验教训与研究方向
Brain Sci. 2021 Dec 31;12(1):70. doi: 10.3390/brainsci12010070.
系统性红斑狼疮患者的结构和功能脑连接组。
Eur J Neurol. 2020 Jan;27(1):113-e2. doi: 10.1111/ene.14041. Epub 2019 Aug 8.
4
Hierarchical complexity of the adult human structural connectome.成人结构连接组的层次复杂性。
Neuroimage. 2019 May 1;191:205-215. doi: 10.1016/j.neuroimage.2019.02.028. Epub 2019 Feb 14.
5
Dynamics of brain connectivity after stroke.中风后的大脑连接动力学。
Rev Neurosci. 2019 Jul 26;30(6):605-623. doi: 10.1515/revneuro-2018-0082.
6
Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus.系统性红斑狼疮的认知功能、疾病负担与结构连接组
Lupus. 2018 Jul;27(8):1329-1337. doi: 10.1177/0961203318772666. Epub 2018 May 3.
7
Preserved Structural Network Organization Mediates Pathology Spread in Alzheimer's Disease Spectrum Despite Loss of White Matter Tract Integrity.保留的结构网络组织介导阿尔茨海默病谱中的病理学进展,尽管白质束完整性丧失。
J Alzheimers Dis. 2018;65(3):747-764. doi: 10.3233/JAD-170798.
8
Altered white matter microstructure in lupus patients: a diffusion tensor imaging study.狼疮患者的脑白质微结构改变:一项弥散张量成像研究。
Arthritis Res Ther. 2018 Feb 7;20(1):21. doi: 10.1186/s13075-018-1516-0.
9
Alteration of putaminal fractional anisotropy in Parkinson's disease: a longitudinal diffusion kurtosis imaging study.帕金森病中壳核分数各向异性的改变:一项纵向扩散峰度成像研究。
Neuroradiology. 2018 Mar;60(3):247-254. doi: 10.1007/s00234-017-1971-3. Epub 2018 Jan 24.
10
Accounting for the complex hierarchical topology of EEG phase-based functional connectivity in network binarisation.在网络二值化中考虑基于脑电图(EEG)相位的功能连接的复杂层次拓扑结构。
PLoS One. 2017 Oct 20;12(10):e0186164. doi: 10.1371/journal.pone.0186164. eCollection 2017.