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Neuroinflammation and related neuropathologies in APP(SL) mice: further value of this in vivo model of Alzheimer’s disease
BACKGROUND: Beyond cognitive decline, Alzheimer’s disease (AD) is characterized by numerous neuropathological changes in the brain. Although animal models generally do not fully reflect the broad spectrum of disease-specific alterations, the APP(SL) mouse model is well known to display early plaque...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4108132/ https://www.ncbi.nlm.nih.gov/pubmed/24886182 http://dx.doi.org/10.1186/1742-2094-11-84 |
Sumario: | BACKGROUND: Beyond cognitive decline, Alzheimer’s disease (AD) is characterized by numerous neuropathological changes in the brain. Although animal models generally do not fully reflect the broad spectrum of disease-specific alterations, the APP(SL) mouse model is well known to display early plaque formation and to exhibit spatial learning and memory deficits. However, important neuropathological features, such as neuroinflammation and lipid peroxidation, and their progression over age, have not yet been described in this AD mouse model. METHODS: Hippocampal and neocortical tissues of APP(SL) mice at different ages were evaluated. One hemisphere from each mouse was examined for micro- and astrogliosis as well as concomitant plaque load. The other hemisphere was evaluated for lipid peroxidation (quantified by a thiobarbituric acid reactive substances (TBARS) assay), changes in Aβ abundance (Aβ38, Aβ40 and Aβ42 analyses), as well as determination of aggregated Aβ content (Amorfix A(4) assay). Finally, correlation analyses were performed to illustrate the time-dependent correlation between neuroinflammation and Aβ load (soluble, insoluble, fibrils), or lipid peroxidation, respectively. RESULTS: As is consistent with previous findings, neuroinflammation starts early and shows strong progression over age in the APP(SL) mouse model. An analyses of concomitant Aβ load and plaque deposition revealed a similar progression, and high correlations between neuroinflammation markers and soluble or insoluble Aβ or fibrillar amyloid plaque loads were observed. Lipid peroxidation, as measured by TBARS levels, correlates well with neuroinflammation in the neocortex but not the hippocampus. The hippocampal lipid peroxidation correlated strongly with the increase of LOC positive fiber load, whereas neocortical TBARS levels were unrelated to amyloidosis. CONCLUSIONS: These data illustrate for the first time the progression of major AD related neuropathological features other than plaque load in the APP(SL) mouse model. Specifically, we demonstrate that microgliosis and astrocytosis are prominent aspects of this AD mouse model. The strong correlation of neuroinflammation with amyloid burden and lipid peroxidation underlines the importance of these pathological factors for the development of AD. The new finding of a different relation of lipid peroxidation in the hippocampus and neocortical regions show that the model might contribute to the understanding of complex pathological mechanisms and their interplay in AD. |
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