Dataset Information

Progressive Changes in Sleep and Its Relations to Amyloid-? Distribution and Learning in Single App Knock-In Mice.

ABSTRACT: Alzheimer's disease (AD) patients often suffer from sleep disturbances. Alterations in sleep, especially rapid eye movement sleep (REMS), can precede the onset of dementia. To accurately characterize the sleep impairments accompanying AD and their underlying mechanisms using animal models, it is crucial to use models in which brain areas are affected in a manner similar to that observed in the actual patients. Here, we focused on AppNL-G-F mice, in which expression levels and patterns of mutated amyloid precursor protein (APP) follow the endogenous patterns. We characterized the sleep architecture of male AppNL-G-F homozygous and heterozygous mice at two ages (six and 12?months). At six?months, homozygous mice exhibited reduced REMS, which was further reduced at 12?months together with a slight reduction in non-REMS (NREMS). By contrast, heterozygous mice exhibited an overall normal sleep architecture. Homozygous mice also exhibited decreased electroencephalogram ? to ? power ratio during REMS from six months, resembling the electroencephalogram slowing phenomenon observed in preclinical or early stages of AD. In addition, homozygous mice showed learning and memory impairments in the trace fear conditioning (FC) at both ages, and task performance strongly correlated with REMS amount at 12?months. Finally, histologic analyses revealed that amyloid-? accumulation in the pontine tegmental area and ventral medulla followed a course similar to that of the REMS reduction. These findings support the notion that changes in REMS are an early marker of AD and provide a starting point to address the mechanism of sleep deficits in AD and the effects on cognition.

SUBMITTER: Maezono SEB

PROVIDER: S-EPMC7196722 | biostudies-literature | 2020 Mar/Apr

REPOSITORIES: biostudies-literature

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Publications

Progressive Changes in Sleep and Its Relations to Amyloid-β Distribution and Learning in Single App Knock-In Mice.

Maezono Sakura Eri B SEB Kanuka Mika M Tatsuzawa Chika C Morita Miho M Kawano Taizo T Kashiwagi Mitsuaki M Nondhalee Pimpimon P Sakaguchi Masanori M Saito Takashi T Saido Takaomi C TC Hayashi Yu Y

eNeuro 20200301 2

Alzheimer's disease (AD) patients often suffer from sleep disturbances. Alterations in sleep, especially rapid eye movement sleep (REMS), can precede the onset of dementia. To accurately characterize the sleep impairments accompanying AD and their underlying mechanisms using animal models, it is crucial to use models in which brain areas are affected in a manner similar to that observed in the actual patients. Here, we focused on AppNL-G-F mice, in which expression levels and p ...[more]

PMID: 32321771

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Project description:BackgroundGenetic mutations underlying familial Alzheimer's disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain.MethodsWe engineered a novel App knock-in mouse model (AppSAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene. Amyloid-β pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous AppSAA mice at different ages in brain and/ or biofluids. Wild type littermate mice were used as experimental controls. We used in situ imaging technologies to define the whole-brain distribution of amyloid plaques and compare it to other AD mouse models and human brain pathology. To further explore the microglial response to AD relevant pathology, we isolated microglia with fibrillar Aβ content from the brain and performed transcriptomics and metabolomics analyses and in vivo brain imaging to measure energy metabolism and microglial response. Finally, we also characterized the mice in various behavioral assays.ResultsLeveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aβ content. The AppSAA knock-in mouse model recapitulates key pathological features of AD such as a progressive accumulation of parenchymal amyloid plaques and vascular amyloid deposits, altered astroglial and microglial responses and elevation of CSF markers of neurodegeneration. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged.DiscussionOur findings demonstrate that fibrillar Aβ in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology.

Dataset Information

Progressive Changes in Sleep and Its Relations to Amyloid-? Distribution and Learning in Single App Knock-In Mice.

Publications

Progressive Changes in Sleep and Its Relations to Amyloid-β Distribution and Learning in Single <i>App</i> Knock-In Mice.

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