Literature DB >> 33844192

Distinct impaired patterns of intrinsic functional network centrality in patients with early- and late-onset Alzheimer's disease.

Jiong Zhou1, Kaicheng Li2, Xiao Luo2, Qingze Zeng2, Yerfan Jiaerken2, Shuyue Wang2, Xiaopei Xu2, Xiaocao Liu2, Zheyu Li1, Tianyi Zhang1, Yanv Fu1, Shuai Zhao1, Peiyu Huang3, Minming Zhang4.   

Abstract

Early-onset Alzheimer's disease (EOAD) involves multiple cognitive domains and shows more rapid progression than late-onset Alzheimer's disease (LOAD). However, the difference in pathogenesis between EOAD and LOAD is still unclear. Accordingly, we applied intrinsic network analysis to explore the potential neuropathological mechanism underlying distinct clinical phenotypes. According to the cut-off age of 65, we included 20 EOAD patients, 20 LOAD patients, and 36 age-matched controls (19 young and 17 old controls). We employed resting-state functional MRI and network centrality analysis to explore the local (degree centrality (DC)) and global (eigenvector centrality (EC)) functional integrity. Two-sample t-test analysis was performed, with gray matter volume, age, gender, and education as covariates. Furthermore, we performed a correlation analysis between network metrics and cognition. Compared to young controls, EOAD patients exhibited lower DC in the middle temporal gyrus (MTG), parahippocampal gyrus (PHG), superior temporal gyrus (STG), and lower EC in the MTG, PHG, and postcentral gyrus. In contrast, LOAD patients exhibited lower DC in the STG and anterior cingulum gyrus and higher DC in the middle frontal gyrus compared to old controls. No significant difference in EC was observed in LOAD patients. Furthermore, both DC and EC correlated with cognitive performance. Our study demonstrated divergent functional network impairments in EOAD and LOAD patients. EOAD patients showed more complex network damage involving both local and global centrality properties, while LOAD patients mainly featured local functional connectivity changes. Such centrality impairments are related to poor cognition, especially regarding memory performance.

Entities:  

Keywords:  Early‐onset alzheimer’s disease; Functional connectivity; Late‐onset alzheimer’s disease; Network centrality; Resting‐state fMRI

Year:  2021        PMID: 33844192     DOI: 10.1007/s11682-021-00470-3

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  2 in total

Review 1.  Patterns of compensation and vulnerability in normal subjects at risk of Alzheimer's disease.

Authors:  Oscar L Lopez; James T Becker; Lewis H Kuller
Journal:  J Alzheimers Dis       Date:  2013       Impact factor: 4.472

2.  DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

Authors:  Yan Chao-Gan; Zang Yu-Feng
Journal:  Front Syst Neurosci       Date:  2010-05-14
  2 in total
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1.  The Internal Connection Analysis of Information Sharing and Investment Performance in the Venture Capital Network Community.

Authors:  Bing Feng; Kaiyang Sun; Ziqi Zhong; Min Chen
Journal:  Int J Environ Res Public Health       Date:  2021-11-13       Impact factor: 3.390

  1 in total

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