CASIA OpenIR  > 脑网络组研究
Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease
Jin, Dan1,2; Wang, Pan3; Zalesky, Andrew4,5; Liu, Bing1,2,6; Song, Chengyuan7; Wang, Dawei8; Xu, Kaibin1; Yang, Hongwei9; Zhang, Zengqiang10; Yao, Hongxiang11; Zhou Bo12; Han, Tong13; Zuo, Nianming1,2; Han, Ying14,15,16,17; Lu, Jie9; Wang, Qing8; Yu, Chunshui18; Zhang, Xinqing14; Zhang, Xi12; Jiang, Tainzi1,2,6; Zhou, Yuying3; Liu, Yong1,2,6
Source PublicationHuman Brain Mapping
2020-05
Issue0Pages:0
Subtype期刊论文
Abstract

Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to elucidate the core disease mechanisms. In this study, we aim to comprehensively characterize AD-associated functional brain alterations using one of the world's largest resting-state functional MRI (fMRI) biobank for the disorder. The biobank includes fMRI data from six neuroimaging centers, with a total of 252 AD patients, 221 mild cognitive impairment (MCI) patients and 215 healthy comparison individuals. Metaanalytic techniques were used to unveil reliable differences in brain function among the three groups. Relative to the healthy comparison group, AD was associated with significantly reduced functional connectivity and local activity in the default-mode network, basal ganglia and cingulate gyrus, along with increased connectivity or local activity in the prefrontal lobe and hippocampus (p < .05, Bonferroni corrected). Moreover, these functional alterations were significantly correlated with the degree of cognitive impairment (AD and MCI groups) and amyloid-β burden. Machine learning models were trained to recognize key fMRI features to predict individual diagnostic status and clinical score. Leave-one-site-out cross-validation established that diagnostic status (mean area under the receiver operating characteristic curve: 0.85) and clinical score (mean correlation coefficient between predicted and actual Mini-Mental State Examination scores: 0.56, p < .0001) could be predicted with high accuracy. Collectively, our findings highlight the potential for a reproducible and generalizable functional brain imaging biomarker to aid the early diagnosis of AD and track its progression.
 

Keywordactivity Alzheimer's disease functional connectivity multicenter resting-state fMRI
Language英语
WOS IDWOS:000530441400001
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/39153
Collection脑网络组研究
Corresponding AuthorLiu, Yong
Affiliation1.Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
3.Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, China
4.Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
5.Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
6.Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
7.Department of Neurology, Qilu Hospital of Shandong University, Ji'nan, China
8.Department of Radiology, Qilu Hospital of Shandong University, Ji'nan, China
9.Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
10.Branch of Chinese PLA General Hospital, Sanya, China
11.Department of Radiology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
12.Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
13.Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
14.Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
15.Beijing Institute of Geriatrics, Beijing, China
16.National Clinical Research Center for Geriatric Disorders, Beijing, China
17.Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
18.Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China;  Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Jin, Dan,Wang, Pan,Zalesky, Andrew,et al. Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease[J]. Human Brain Mapping,2020(0):0.
APA Jin, Dan.,Wang, Pan.,Zalesky, Andrew.,Liu, Bing.,Song, Chengyuan.,...&Liu, Yong.(2020).Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.Human Brain Mapping(0),0.
MLA Jin, Dan,et al."Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease".Human Brain Mapping .0(2020):0.
Files in This Item: Download All
File Name/Size DocType Version Access License
hbm.pdf(7097KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Jin, Dan]'s Articles
[Wang, Pan]'s Articles
[Zalesky, Andrew]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jin, Dan]'s Articles
[Wang, Pan]'s Articles
[Zalesky, Andrew]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jin, Dan]'s Articles
[Wang, Pan]'s Articles
[Zalesky, Andrew]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: hbm.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.