| Literature DB >> 28500878 |
Sarah N Fontaine1, Alexandria Ingram2, Ryan A Cloyd2, Shelby E Meier3, Emily Miller2, Danielle Lyons4, Grant K Nation2, Elizabeth Mechas2, Blaine Weiss2, Chiara Lanzillotta5, Fabio Di Domenico5, Frederick Schmitt2, David K Powell6, Moriel Vandsburger7, Jose F Abisambra8.
Abstract
Tauopathies, the most common of which is Alzheimer's disease (AD), constitute the most crippling neurodegenerative threat to our aging population. Tauopathic patients have significant cognitive decline accompanied by irreversible and severe brain atrophy, and it is thought that neuronal dysfunction begins years before diagnosis. Our current understanding of tauopathies has yielded promising therapeutic interventions but have all failed in clinical trials. This is partly due to the inability to identify and intervene in an effective therapeutic window early in the disease process. A major challenge that contributes to the definition of an early therapeutic window is limited technologies. To address these challenges, we modified and adapted a manganese-enhanced magnetic resonance imaging (MEMRI) approach to provide sensitive and quantitative power to detect changes in broad neuronal function in aging mice. Considering that tau tangle burden correlates well with cognitive impairment in Alzheimer's patients, we performed our MEMRI approach in a time course of aging mice and an accelerated mouse model of tauopathy. We measured significant changes in broad neuronal function as a consequence of age, and in transgenic mice, before the deposition of bona fide tangles. This MEMRI approach represents the first diagnostic measure of neuronal dysfunction in mice. Successful translation of this technology in the clinic could serve as a sensitive diagnostic tool for the definition of effective therapeutic windows.Entities:
Keywords: Alzheimer; MEMRI; Manganese; Tangles; Tau; rTg4510
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Year: 2017 PMID: 28500878 PMCID: PMC5524451 DOI: 10.1016/j.neurobiolaging.2017.04.007
Source DB: PubMed Journal: Neurobiol Aging ISSN: 0197-4580 Impact factor: 4.673