机构：[1]School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.[2]Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.[3]Research Institute of Shandong University: Magnetic Field-free Medicine & Functional Imaging, Jinan, China.[4]Shandong Key Laboratory: Magnetic Field-free Medicine & Functional Imaging (MF), Jinan, China.[5]School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Center, Chinese Academy of Sciences, Beijing, China.[6]Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.神经科系统神经内科首都医科大学宣武医院[7]Department of Radiology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.[8]Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.[9]Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China.医技科室放射科首都医科大学宣武医院[10]Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China.[11]Department of Psychiatry, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China.[12]National Clinical Research Center for Geriatric Disorders, Beijing, China.[13]Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
The intricate spatial configurations of brain networks offer essential insights into understanding the specific patterns of brain abnormalities and the underlying biological mechanisms associated with Alzheimer's disease (AD), normal aging, and other neurodegenerative disorders. This study investigated alterations in the topographical structure of the brain related to aging and neurodegenerative diseases by analyzing brain gradients derived from structural MRI data across multiple cohorts (n = 7323). The analysis identified distinct gradient patterns in AD, aging, and other neurodegenerative conditions. Gene enrichment analysis indicated that inorganic ion transmembrane transport was the most significant term in normal aging, while chemical synaptic transmission is a common enrichment term across various neurodegenerative diseases. Moreover, the findings show that each disorder exhibits unique dysfunctional neurophysiological characteristics. These insights are pivotal for elucidating the distinct biological mechanisms underlying AD, thereby enhancing our understanding of its unique clinical phenotypes in contrast to normal aging and other neurodegenerative disorders.
基金：
Science and Technology Innovation 2030 Major Projects no. 2022ZD0211600 (to Y.L.), the Beijing Municipal Natural Science Foundation no.7244519 (to K.Z.), the Fundamental Research Funds for the Central Universities no.2021XD-A03 (to Y.L.), the National Natural Science Foundation of China no. 82172018 (to Y.L.)and no. 62333002 (to Y.L.), the Natural Science Foundation of Shandong Province no:
ZR2021MH236 (to Dawei Wang), and the Key R&D Program of Shandong Province no.2022ZLGX03 (to Dawei Wang)
第一作者机构：[1]School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
共同第一作者：
通讯作者：
通讯机构：[1]School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.[5]School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Center, Chinese Academy of Sciences, Beijing, China.
推荐引用方式(GB/T 7714)：
Zhao Kun,Wang Dawei,Wang Dong,et al.Macroscale connectome topographical structure reveals the biomechanisms of brain dysfunction in Alzheimer's disease[J].Science Advances.2024,10(41):eado8837.doi:10.1126/sciadv.ado8837.
APA：
Zhao Kun,Wang Dawei,Wang Dong,Chen Pindong,Wei Yongbin...&Liu Yong.(2024).Macroscale connectome topographical structure reveals the biomechanisms of brain dysfunction in Alzheimer's disease.Science Advances,10,(41)
MLA：
Zhao Kun,et al."Macroscale connectome topographical structure reveals the biomechanisms of brain dysfunction in Alzheimer's disease".Science Advances 10..41(2024):eado8837
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