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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doaj-4c4c1f6c75d34206a2034602569eb9d12020-11-25T01:49:48ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652019-08-011110.3389/fnagi.2019.00213475162Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early StagesRaúl Tudela0Emma Muñoz-Moreno1Roser Sala-Llonch2Xavier López-Gil3Guadalupe Soria4Guadalupe Soria5Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Group of Biomedical Imaging, University of Barcelona, Barcelona, SpainExperimental 7T MRI Unit, Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, SpainDepartment of Biomedicine, Faculty of Medicine, University of Barcelona, Barcelona, SpainExperimental 7T MRI Unit, Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, SpainConsorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Group of Biomedical Imaging, University of Barcelona, Barcelona, SpainExperimental 7T MRI Unit, Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, SpainA 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.https://www.frontiersin.org/article/10.3389/fnagi.2019.00213/fullAlzheimer’s diseaseanimal modelmagnetic resonance imagingresting stateconnectivityindependent component analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Raúl Tudela Emma Muñoz-Moreno Roser Sala-Llonch Xavier López-Gil Guadalupe Soria Guadalupe Soria |
spellingShingle |
Raúl Tudela Emma Muñoz-Moreno Roser Sala-Llonch Xavier López-Gil Guadalupe Soria Guadalupe Soria Resting State Networks in the TgF344-AD Rat Model of Alzheimer’s Disease Are Altered From Early Stages Frontiers in Aging Neuroscience Alzheimer’s disease animal model magnetic resonance imaging resting state connectivity independent component analysis |
author_facet |
Raúl Tudela Emma Muñoz-Moreno Roser Sala-Llonch Xavier López-Gil Guadalupe Soria Guadalupe Soria |
author_sort |
Raúl Tudela |
title |
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_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_sort |
resting state networks in the tgf344-ad rat model of alzheimer’s disease are altered from early stages |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Aging Neuroscience |
issn |
1663-4365 |
publishDate |
2019-08-01 |
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. |
topic |
Alzheimer’s disease animal model magnetic resonance imaging resting state connectivity independent component analysis |
url |
https://www.frontiersin.org/article/10.3389/fnagi.2019.00213/full |
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