机构:[1]School of Biological Science and Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China[2]Department of Neurology, Tangshan Gongren Hospital, Tangshan, China[3]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[4]School of Electrical Engineering, Yanshan University, Qinhuangdao, China[5]Measurement Technology and Instrumentation Key Laboratory of Hebei Province, Qinhuangdao, China[6]School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China[7]Biomedical Engineering Institute, Hainan University, Haikou, China[8]Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China[9]National Clinical Research Center for Geriatric Disorders, Beijing, China
Alzheimer's disease (AD) has a long preclinical stage that can last for decades prior to progressing toward amnestic mild cognitive impairment (aMCI) and/or dementia. Subjective cognitive decline (SCD) is characterized by self-experienced memory decline without any evidence of objective cognitive decline and is regarded as the later stage of preclinical AD. It has been reported that the changes in structural covariance patterns are affected by AD pathology in the patients with AD and aMCI within the specific large-scale brain networks. However, the changes in structural covariance patterns including normal control (NC), SCD, aMCI, and AD are still poorly understood. In this study, we recruited 42 NCs, 35 individuals with SCD, 43 patients with aMCI, and 41 patients with AD. Gray matter (GM) volumes were extracted from 10 readily identifiable regions of interest involved in high-order cognitive function and AD-related dysfunctional structures. The volume values were used to predict the regional densities in the whole brain by using voxel-based statistical and multiple linear regression models. Decreased structural covariance and weakened connectivity strength were observed in individuals with SCD compared with NCs. Structural covariance networks (SCNs) seeding from the default mode network (DMN), salience network, subfields of the hippocampus, and cholinergic basal forebrain showed increased structural covariance at the early stage of AD (referring to aMCI) and decreased structural covariance at the dementia stage (referring to AD). Moreover, the SCN seeding from the executive control network (ECN) showed a linearly increased extent of the structural covariance during the early and dementia stages. The results suggest that changes in structural covariance patterns as the order of NC-SCD-aMCI-AD are divergent and dynamic, and support the structural disconnection hypothesis in individuals with SCD.
基金:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [81972160, 61633018, 82020108013, 82001773, 81622025]; Hebei Provincial Natural Science Foundation, China [F2019203515]
第一作者机构:[1]School of Biological Science and Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
通讯作者:
通讯机构:[3]Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China[7]Biomedical Engineering Institute, Hainan University, Haikou, China[8]Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China[9]National Clinical Research Center for Geriatric Disorders, Beijing, China
推荐引用方式(GB/T 7714):
Fu Zhenrong,Zhao Mingyan,He Yirong,et al.Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease[J].FRONTIERS IN AGING NEUROSCIENCE.2021,13:686598.doi:10.3389/fnagi.2021.686598.
APA:
Fu, Zhenrong,Zhao, Mingyan,He, Yirong,Wang, Xuetong,Lu, Jiadong...&Li, Shuyu.(2021).Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease.FRONTIERS IN AGING NEUROSCIENCE,13,
MLA:
Fu, Zhenrong,et al."Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease".FRONTIERS IN AGING NEUROSCIENCE 13.(2021):686598