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Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages

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 connectiv...

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Autores principales: Tudela, Raúl, Muñoz-Moreno, Emma, Sala-Llonch, Roser, López-Gil, Xavier, Soria, Guadalupe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694297/
https://www.ncbi.nlm.nih.gov/pubmed/31440158
http://dx.doi.org/10.3389/fnagi.2019.00213
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author Tudela, Raúl
Muñoz-Moreno, Emma
Sala-Llonch, Roser
López-Gil, Xavier
Soria, Guadalupe
author_facet Tudela, Raúl
Muñoz-Moreno, Emma
Sala-Llonch, Roser
López-Gil, Xavier
Soria, Guadalupe
author_sort Tudela, Raúl
collection PubMed
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 (WT) 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.
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spelling pubmed-66942972019-08-22 Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages Tudela, Raúl Muñoz-Moreno, Emma Sala-Llonch, Roser López-Gil, Xavier Soria, Guadalupe Front Aging Neurosci Neuroscience 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 (WT) 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. Frontiers Media S.A. 2019-08-08 /pmc/articles/PMC6694297/ /pubmed/31440158 http://dx.doi.org/10.3389/fnagi.2019.00213 Text en Copyright © 2019 Tudela, Muñoz-Moreno, Sala-Llonch, López-Gil and Soria. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Tudela, Raúl
Muñoz-Moreno, Emma
Sala-Llonch, Roser
López-Gil, Xavier
Soria, Guadalupe
Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages
title Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages
title_full Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages
title_fullStr Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages
title_full_unstemmed Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages
title_short Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages
title_sort resting state networks in the tgf344-ad rat model of alzheimer’s disease are altered from early stages
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694297/
https://www.ncbi.nlm.nih.gov/pubmed/31440158
http://dx.doi.org/10.3389/fnagi.2019.00213
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