Paul R. Territo

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Articles (1)

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.

Year:

2023

Collaborators (1)

Mattia Veronese

King’s College London

UNITED KINGDOM
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