Individualized network analysis: A novel approach to investigate tau PET using graph theory in the Alzheimer's disease continuum.

ADNI Alzheimer’s disease flortaucipir PET graph theory tangle burden

Journal

Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481

Informations de publication

Date de publication:
2023
Historique:
received: 03 11 2022
accepted: 14 02 2023
entrez: 20 3 2023
pubmed: 21 3 2023
medline: 21 3 2023
Statut: epublish

Résumé

Tau PET imaging has emerged as an important tool to detect and monitor tangle burden in vivo in the study of Alzheimer's disease (AD). Previous studies demonstrated the association of tau burden with cognitive decline in probable AD cohorts. This study introduces a novel approach to analyze tau PET data by constructing individualized tau network structure and deriving its graph theory-based measures. We hypothesize that the network- based measures are a measure of the total tau load and the stage through disease. Using tau PET data from the AD Neuroimaging Initiative from 369 participants, we determine the network measures, global efficiency, global strength, and limbic strength, and compare with two regional measures entorhinal and tau composite SUVR, in the ability to differentiate, cognitively unimpaired (CU), MCI and AD. We also investigate the correlation of these network and regional measures and a measure of memory performance, auditory verbal learning test for long-term recall memory (AVLT-LTM). Finally, we determine the stages based on global efficiency and limbic strength using conditional inference trees and compare with Braak staging. We demonstrate that the derived network measures are able to differentiate three clinical stages of AD, CU, MCI, and AD. We also demonstrate that these network measures are strongly correlated with memory performance overall. Unlike regional tau measurements, the tau network measures were significantly associated with AVLT-LTM even in cognitively unimpaired individuals. Stages determined from global efficiency and limbic strength, visually resembled Braak staging. The strong correlations with memory particularly in CU suggest the proposed technique may be used to characterize subtle early tau accumulation. Further investigation is ongoing to examine this technique in a longitudinal setting.

Identifiants

pubmed: 36937677
doi: 10.3389/fnins.2023.1089134
pmc: PMC10017746
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1089134

Subventions

Organisme : NIA NIH HHS
ID : P30 AG019610
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG072980
Pays : United States

Informations de copyright

Copyright © 2023 Protas, Ghisays, Goradia, Bauer, Devadas, Chen, Reiman and Su.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Hillary Protas (H)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.

Valentina Ghisays (V)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.

Dhruman D Goradia (DD)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.

Robert Bauer (R)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.

Vivek Devadas (V)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.

Kewei Chen (K)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.
Department of Neurology, The University of Arizona, Tucson, AZ, United States.
Department of Psychiatry, The University of Arizona, Tucson, AZ, United States.
Department of Neuroscience, School of Computing and Augmented Intelligence, Biostatistical Core, School of Mathematics and Statistics, College of Health Solutions, Arizona State University, Tempe, AZ, United States.

Eric M Reiman (EM)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.
Department of Neurology, The University of Arizona, Tucson, AZ, United States.
Department of Psychiatry, The University of Arizona, Tucson, AZ, United States.
Department of Neuroscience, School of Computing and Augmented Intelligence, Biostatistical Core, School of Mathematics and Statistics, College of Health Solutions, Arizona State University, Tempe, AZ, United States.
Translational Genomics Research Institute, Phoenix, AZ, United States.

Yi Su (Y)

Banner Alzheimer's Institute, Phoenix, AZ, United States.
Arizona Alzheimer's Consortium, Phoenix, AZ, United States.
Department of Neuroscience, School of Computing and Augmented Intelligence, Biostatistical Core, School of Mathematics and Statistics, College of Health Solutions, Arizona State University, Tempe, AZ, United States.

Classifications MeSH