功能动态网络连接区分阿尔茨海默病连续体中的生物模式

IF 5.6 2区 医学 Q1 NEUROSCIENCES Neurobiology of Disease Pub Date : 2025-05-01 Epub Date: 2025-03-11 DOI:10.1016/j.nbd.2025.106866
Lorenzo Pini , Lorenza Brusini , Alessandra Griffa , Federica Cruciani , Gilles Allali , Giovanni B. Frisoni , Maurizio Corbetta , Gloria Menegaz , Ilaria Boscolo Galazzo , for the Alzheimer's Disease Neuroimaging Initiative
{"title":"功能动态网络连接区分阿尔茨海默病连续体中的生物模式","authors":"Lorenzo Pini ,&nbsp;Lorenza Brusini ,&nbsp;Alessandra Griffa ,&nbsp;Federica Cruciani ,&nbsp;Gilles Allali ,&nbsp;Giovanni B. Frisoni ,&nbsp;Maurizio Corbetta ,&nbsp;Gloria Menegaz ,&nbsp;Ilaria Boscolo Galazzo ,&nbsp;for the Alzheimer's Disease Neuroimaging Initiative","doi":"10.1016/j.nbd.2025.106866","DOIUrl":null,"url":null,"abstract":"<div><div>Alzheimer's disease (AD) can be conceptualized as a network-based syndrome. Network alterations are linked to the molecular hallmarks of AD, involving amyloid-beta and tau accumulation, and consecutively neurodegeneration. By combining molecular and resting-state functional magnetic resonance imaging, we assessed whether different biological patterns of AD identified through a data-driven approach matched specific abnormalities in brain dynamic connectivity. We identified three main patient clusters. The first group displayed mild pathological alterations. The second cluster exhibited typical behavioral impairment alongside AD pathology. The third cluster demonstrated similar behavioral impairment but with a divergent tau (low) and neurodegeneration (high) profile. Univariate and multivariate analyses revealed two connectivity patterns encompassing the default mode network and the occipito-temporal cortex, linked respectively with typical and atypical patterns. These results support the key association between macro-scale and molecular alterations. Dynamic connectivity markers can assist in identifying patients with AD-like clinical profiles but with different underlying pathologies.</div></div>","PeriodicalId":19097,"journal":{"name":"Neurobiology of Disease","volume":"208 ","pages":"Article 106866"},"PeriodicalIF":5.6000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Functional dynamic network connectivity differentiates biological patterns in the Alzheimer's disease continuum\",\"authors\":\"Lorenzo Pini ,&nbsp;Lorenza Brusini ,&nbsp;Alessandra Griffa ,&nbsp;Federica Cruciani ,&nbsp;Gilles Allali ,&nbsp;Giovanni B. Frisoni ,&nbsp;Maurizio Corbetta ,&nbsp;Gloria Menegaz ,&nbsp;Ilaria Boscolo Galazzo ,&nbsp;for the Alzheimer's Disease Neuroimaging Initiative\",\"doi\":\"10.1016/j.nbd.2025.106866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Alzheimer's disease (AD) can be conceptualized as a network-based syndrome. Network alterations are linked to the molecular hallmarks of AD, involving amyloid-beta and tau accumulation, and consecutively neurodegeneration. By combining molecular and resting-state functional magnetic resonance imaging, we assessed whether different biological patterns of AD identified through a data-driven approach matched specific abnormalities in brain dynamic connectivity. We identified three main patient clusters. The first group displayed mild pathological alterations. The second cluster exhibited typical behavioral impairment alongside AD pathology. The third cluster demonstrated similar behavioral impairment but with a divergent tau (low) and neurodegeneration (high) profile. Univariate and multivariate analyses revealed two connectivity patterns encompassing the default mode network and the occipito-temporal cortex, linked respectively with typical and atypical patterns. These results support the key association between macro-scale and molecular alterations. Dynamic connectivity markers can assist in identifying patients with AD-like clinical profiles but with different underlying pathologies.</div></div>\",\"PeriodicalId\":19097,\"journal\":{\"name\":\"Neurobiology of Disease\",\"volume\":\"208 \",\"pages\":\"Article 106866\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurobiology of Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0969996125000828\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurobiology of Disease","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0969996125000828","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/11 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

阿尔茨海默病(AD)可以被定义为一种基于网络的综合征。网络改变与阿尔茨海默病的分子特征有关,包括淀粉样蛋白和tau蛋白的积累,以及连续的神经变性。通过结合分子和静息状态功能磁共振成像,我们评估了通过数据驱动方法识别的AD的不同生物学模式是否与大脑动态连接的特定异常相匹配。我们确定了三个主要的患者群。第一组表现为轻度病理改变。第二组表现出典型的行为障碍和AD病理。第三组表现出类似的行为障碍,但具有不同的tau(低)和神经变性(高)特征。单变量和多变量分析揭示了两种连接模式,包括默认模式网络和枕颞皮质,分别与典型和非典型模式相关联。这些结果支持宏观尺度和分子改变之间的关键联系。动态连接标记可以帮助识别具有ad样临床特征但具有不同基础病理的患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Functional dynamic network connectivity differentiates biological patterns in the Alzheimer's disease continuum
Alzheimer's disease (AD) can be conceptualized as a network-based syndrome. Network alterations are linked to the molecular hallmarks of AD, involving amyloid-beta and tau accumulation, and consecutively neurodegeneration. By combining molecular and resting-state functional magnetic resonance imaging, we assessed whether different biological patterns of AD identified through a data-driven approach matched specific abnormalities in brain dynamic connectivity. We identified three main patient clusters. The first group displayed mild pathological alterations. The second cluster exhibited typical behavioral impairment alongside AD pathology. The third cluster demonstrated similar behavioral impairment but with a divergent tau (low) and neurodegeneration (high) profile. Univariate and multivariate analyses revealed two connectivity patterns encompassing the default mode network and the occipito-temporal cortex, linked respectively with typical and atypical patterns. These results support the key association between macro-scale and molecular alterations. Dynamic connectivity markers can assist in identifying patients with AD-like clinical profiles but with different underlying pathologies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Neurobiology of Disease
Neurobiology of Disease 医学-神经科学
CiteScore
11.20
自引率
3.30%
发文量
270
审稿时长
76 days
期刊介绍: Neurobiology of Disease is a major international journal at the interface between basic and clinical neuroscience. The journal provides a forum for the publication of top quality research papers on: molecular and cellular definitions of disease mechanisms, the neural systems and underpinning behavioral disorders, the genetics of inherited neurological and psychiatric diseases, nervous system aging, and findings relevant to the development of new therapies.
期刊最新文献
Analysis of the involvement of RNA-binding proteins in TAU-dependent neurodegeneration DYRK1A and Parkinson’s disease, facts and hypotheses SPG11 models reveal lysosomal calcium regulation of neural progenitor proliferation Cognitive trajectories in early Parkinson's disease: A multimodal MRI study of brain structure and cognitive decline Machine learning based multi-omics analysis reveals key molecular determinants of Parkinson's disease severity
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1