Resting state networks in the TgF344-AD rat model of Alzheimer's Disease are altered from early stages

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RECERCAT Home > Universitat de Barcelona > IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer > Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer) > View document

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dc.contributor.author	Tudela Fernández, Raúl
dc.contributor.author	Muñoz-Moreno, Emma
dc.contributor.author	Sala Llonch, Roser
dc.contributor.author	López Gil, Xavier
dc.contributor.author	Soria, Guadalupe
dc.date	2019-09-05T15:33:59Z
dc.date	2019-09-05T15:33:59Z
dc.date	2019-08-08
dc.date	2019-09-05T15:33:59Z
dc.identifier	1663-4365
dc.identifier	691267
dc.identifier	31440158
dc.identifier.uri	http://hdl.handle.net/2445/139352
dc.description	A better and non-invasive characterization of the preclinical phases of Alzheimer's disease (AD) is important to advance its diagnosis and obtain more effective benefits from potential treatments. The TgF344-AD rat model has been well characterized and shows molecular, behavioral and brain connectivity alterations that resemble the silent period of the pathology. Our aim was to longitudinally investigate functional brain connectivity in established resting-state networks (RSNs) obtained by independent component analysis (ICA) in a cohort of TgF344-AD and control rats every 3 months, from 5 to 18 months of age, to cover different stages of the disease. Before each acquisition, working memory performance was evaluated by the delayed non match-to-sample (DNMS) task. Differences in the temporal evolution were observed between groups in the amplitude and shape of the somatosensorial and sensorimotor networks but not in the whole default mode network (DMN). Subsequent high dimensional ICA analysis showed early alterations in the anterior DMN subnetwork activity of TgF344-AD rats compared to controls. Performance of DNMS task was positively correlated with somatosensorial network at 5 months of age in the wild-type animals but not in the Tg-F344 rats. At different time points, DMN showed negative correlation with cognitive performance in the control group while in the transgenic group the correlation was positive. In addition, behavioral differences observed at 5 months of age correlated with alterations in the posterior DMN subnetwork. We have demonstrated that functional connectivity using ICA represents a useful biomarker also in animal models of AD such as the TgF344AD rats, as it allows the identification of alterations associated with the progression of the disease, detecting differences in specific networks even at very early stages.
dc.format	14 p.
dc.format	application/pdf
dc.language	eng
dc.publisher	Frontiers Media
dc.relation	Reproducció del document publicat a: https://doi.org/10.3389/fnagi.2019.00213
dc.relation	Frontiers in Aging Neuroscience, 2019, vol. 11, p. 213
dc.relation	https://doi.org/10.3389/fnagi.2019.00213
dc.rights	cc-by (c) Tudela Fernández, Raúl et al., 2019
dc.rights	http://creativecommons.org/licenses/by/3.0/es
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Malaltia d'Alzheimer
dc.subject	Models animals en la investigació
dc.subject	Imatges per ressonància magnètica
dc.subject	Alzheimer's disease
dc.subject	Animal models in research
dc.subject	Magnetic resonance imaging
dc.title	Resting state networks in the TgF344-AD rat model of Alzheimer's Disease are altered from early stages
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion

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