A Structural Connectivity Disruption One Decade before the Typical Age for Dementia: A Study in Healthy Subjects with Family History of Alzheimer's Disease.

Alzheimer’s disease cascading network failure diffusion-weighted imaging early detection family history of Alzheimer’s disease

Journal

Cerebral cortex communications
ISSN: 2632-7376
Titre abrégé: Cereb Cortex Commun
Pays: United States
ID NLM: 101767128

Informations de publication

Date de publication:
2021
Historique:
received: 20 05 2021
revised: 23 07 2021
accepted: 26 07 2021
entrez: 14 10 2021
pubmed: 15 10 2021
medline: 15 10 2021
Statut: epublish

Résumé

The concept of the brain has shifted to a complex system where different subnetworks support the human cognitive functions. Neurodegenerative diseases would affect the interactions among these subnetworks and, the evolution of impairment and the subnetworks involved would be unique for each neurodegenerative disease. In this study, we seek for structural connectivity traits associated with the family history of Alzheimer's disease, that is, early signs of subnetworks impairment due to Alzheimer's disease. The sample in this study consisted of 123 first-degree Alzheimer's disease relatives and 61 nonrelatives. For each subject, structural connectomes were obtained using classical diffusion tensor imaging measures and different resolutions of cortical parcellation. For the whole sample, independent structural-connectome-traits were obtained under the framework of

Identifiants

pubmed: 34647029
doi: 10.1093/texcom/tgab051
pii: tgab051
pmc: PMC8501268
doi:

Types de publication

Journal Article

Langues

eng

Pagination

tgab051

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press.

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Auteurs

F Ramírez-Toraño (F)

Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain.

Kausar Abbas (K)

Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, IN 46202, USA.

Ricardo Bruña (R)

Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain.

Silvia Marcos de Pedro (S)

Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain.

Natividad Gómez-Ruiz (N)

Sección Neurorradiología, Servicio de Diagnóstico por Imagen, Hospital Clínico San Carlos, Madrid 28040, Comunidad de Madrid, Spain.

Ana Barabash (A)

Endocrinology and Nutrition Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid 28040, Comunidad de Madrid, Spain.

Ernesto Pereda (E)

Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain.

Alberto Marcos (A)

Neurology Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid 28040, Comunidad de Madrid, Spain.

Ramón López-Higes (R)

Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid 28223, Comunidad de Madrid, Spain.

Fernando Maestu (F)

Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain.

Joaquín Goñi (J)

Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, IN 46202, USA.

Classifications MeSH