Journal Article

DZNE-2024-00067

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Validity and value of metabolic connectivity in mouse models of β-amyloid and tauopathy.

Ruch, F. ; Gnörich, J.DZNE* ; Wind, K.DZNE* ; Köhler, M. ; Zatcepin, A.DZNE* ; Wiedemann, T. ; Gildehaus, F.-J. ; Lindner, S. ; Boening, G. ; von Ungern-Sternberg, B. ; Beyer, L. ; Herms, J.DZNE* ; Bartenstein, P.DZNE* ; Brendel, M.DZNE* ; Eckenweber, F.

2024
Academic Press Orlando, Fla.

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Please use a persistent id in citations: doi:10.1016/j.neuroimage.2024.120513

Abstract: Among functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (β-amyloid and tau) by use of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging. We compared the results of FDG-µPET MC with conventional VOI-based analysis and behavioral assessment in the Morris water maze (MWM). The impact of awake versus anesthesia conditions on MC read-outs was studied and the robustness of MC data deriving from different scanners was tested. MC proved to be an accurate and robust indicator of functional connectivity loss when sample sizes ≥12 were considered. MC readouts were robust across scanners and in awake/ anesthesia conditions. MC loss was observed throughout all brain regions in tauopathy mice, whereas β-amyloid indicated MC loss mainly in spatial learning areas and subcortical networks. This study established a methodological basis for the utilization of MC in different β-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.

Keyword(s): Mice (MeSH) ; Animals (MeSH) ; Fluorodeoxyglucose F18: metabolism (MeSH) ; Amyloid beta-Peptides: metabolism (MeSH) ; Alzheimer Disease: pathology (MeSH) ; Tauopathies: pathology (MeSH) ; Brain: metabolism (MeSH) ; Neurodegenerative Diseases: metabolism (MeSH) ; Positron-Emission Tomography: methods (MeSH) ; tau Proteins: metabolism (MeSH) ; Fluorodeoxyglucose F18 ; Alzheimer's disease ; Amyloidosis ; Metabolic connectivity ; Morris water maze ; Small-animal PET ; Tauopathy ; Amyloid beta-Peptides ; tau Proteins

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Contributing Institute(s):

1. Molecular Neurodegeneration (AG Haass)
2. Translational Brain Research (AG Herms)

Research Program(s):

1. 352 - Disease Mechanisms (POF4-352) (POF4-352)

Appears in the scientific report 2024

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Database coverage:
; ; ; ; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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Linked articles:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Dataset Ruch, F.DZNE* ; Ruch, F. (Other)
Dataset: Validity and value of metabolic connectivity in mouse models of β-amyloid and tauopathy, v2
Mendeley (2023) [10.17632/25v8kcrvkx.2]2023 BibTeX | EndNote: XML, Text | RIS

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