Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease.
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ABSTRACT: Introduction
Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage.Methods
We performed 18 F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis.Results
The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model.Discussion
The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.
SUBMITTER: Chumin EJ
PROVIDER: S-EPMC10984484 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
Publications
Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease.
Chumin Evgeny J EJ Burton Charles P CP Silvola Rebecca R Miner Ethan W EW Persohn Scott C SC Veronese Mattia M Territo Paul R PR
Alzheimer's & dementia : the journal of the Alzheimer's Association 20231130 3
<h4>Introduction</h4>Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage.<h4>Methods</h4>We performed <sup>18</sup> F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD a ...[more]
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