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Structural and functional connectivity abnormalities of the default mode network in patients with Alzheimer's disease and mild cognitive impairment within two independent datasets.
Zhou, Bo; Dou, Xuejiao; Wang, Wei; Yao, Hongxiang; Feng, Feng; Wang, Pan; Yang, Zhengyi; An, Ningyu; Liu, Bing; Zhang, Xi; Liu, Yong.
Afiliação
  • Zhou B; Department of Neurology, the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
  • Dou X; Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • Wang W; Department of Neurology, the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
  • Yao H; Department of Radiology, the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
  • Feng F; Department of Neurology, the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
  • Wang P; Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, China.
  • Yang Z; Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • An N; Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • Liu B; State Key Lab of Cognition Neuroscience & Learning, Beijing Normal University, Beijing, China.
  • Zhang X; Department of Neurology, the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
  • Liu Y; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China. Electronic address: yongliu@bupt.edu.cn.
Methods ; 205: 29-38, 2022 09.
Article em En | MEDLINE | ID: mdl-35671900
ABSTRACT
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as a transitional stage between normal aging and AD. Accumulating evidence has shown that altered functional connectivity (FC) and structural connectivity (SC) in the default mode network (DMN) is the prominent hallmarks of AD. However, the relationship between the changes in SC and FC of the DMN is not yet clear. In the present study, we derived the FC and SC matrices of the DMN with functional magnetic resonance imaging (fMRI) and diffusion-weighted imaging (DWI) data and further assessed FC and SC abnormalities within a discovery dataset of 120 participants (39 normal controls, 34 patients with aMCI and 47 patients with AD), as well as a replication dataset of 122 participants (43 normal controls, 37 patients with aMCI and 42 patients with AD). Disrupted SC and FC were found among DMN components (e.g., the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), and hippocampus) in patients in the aMCI and AD groups in the discovery dataset; most of the disrupted connections were also identified in the replication dataset. More importantly, some SC and FC elements were significantly correlated with the cognitive ability of patients with aMCI and AD. In addition, we found structural-functional decoupling between the PCC and the right hippocampus in patients in the aMCI and AD groups. These findings of the alteration of DMN connectivity in neurodegenerative cohorts deepen our understanding of the pathophysiological mechanisms of AD.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças Neurodegenerativas / Doença de Alzheimer / Disfunção Cognitiva Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças Neurodegenerativas / Doença de Alzheimer / Disfunção Cognitiva Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article