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Collagenous Alzheimer amyloid plaque component impacts on the compaction of amyloid-? plaques.

ABSTRACT: Massive deposition of amyloid ? peptides (A?) as senile plaques (SP) characterizes the brain pathology of Alzheimer's disease (AD). SPs exhibit a variety of morphologies, although little is known about the SP components that determine their morphology. Collagenous Alzheimer amyloid plaque component (CLAC) is one of the major non-A? proteinaceous components of SP amyloid in AD brains. Here we show that overexpression of CLAC precursor (CLAC-P) in the brains of APP transgenic mice results in a significant remodeling of amyloid pathology, i.e., reduction in diffuse-type amyloid plaques and an increase in compact plaques laden with thioflavin S-positive amyloid cores. In vivo microdialysis revealed a significant decrease in A? in the brain interstitial fluid of CLAC-P/APP double transgenic mice compared with APP transgenic mice. These findings implicate CLAC in the compaction of A? in amyloid plaques and the brain dynamics of A?.

SUBMITTER: Hashimoto T

PROVIDER: S-EPMC7720522 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Collagenous Alzheimer amyloid plaque component impacts on the compaction of amyloid-β plaques.

Hashimoto Tadafumi T Fujii Daisuke D Naka Yasushi Y Kashiwagi-Hakozaki Mayu M Matsuo Yuko Y Matsuura Yusuke Y Wakabayashi Tomoko T Iwatsubo Takeshi T

Acta neuropathologica communications 20201207 1

Massive deposition of amyloid β peptides (Aβ) as senile plaques (SP) characterizes the brain pathology of Alzheimer's disease (AD). SPs exhibit a variety of morphologies, although little is known about the SP components that determine their morphology. Collagenous Alzheimer amyloid plaque component (CLAC) is one of the major non-Aβ proteinaceous components of SP amyloid in AD brains. Here we show that overexpression of CLAC precursor (CLAC-P) in the brains of APP transgenic mice results in a sig ...[more]

PMID: 33287899

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Project description:Alzheimer's disease (AD) is a prominent neurodegenerative disorder characterized by deposition of β-amyloid (Aβ)-containing extracellular plaques, accompanied by a microglial-mediated inflammatory response, that leads to cognitive decline. Microglia perform many disease-modifying functions such as phagocytosis of plaques, plaque compaction, and modulation of inflammation through the secretion of cytokines. Microglia are reliant upon colony-stimulating factor receptor-1 (CSF1R) activation for survival. In AD mouse models, chronic targeted depletion of microglia via CSF1R antagonism attenuates plaque formation in early disease but fails to alter plaque burden in late disease. It is unclear if acute depletion of microglia during the peak period of plaque deposition will alter disease pathogenesis, and if so, whether these effects are reversible upon microglial repopulation. To test this, we administered the CSF1R antagonist PLX5622 to the 5XFAD mouse model of AD at four months of age for approximately one month. In a subset of mice, the drug treatment was discontinued, and the mice were fed a control diet for an additional month. We evaluated plaque burden and composition, microgliosis, inflammatory marker expression, and neuritic dystrophy. In 5XFAD animals, CSF1R blockade for 28 days depleted microglia across brain regions by over 50%, suppressed microgliosis, and reduced plaque burden. In microglial-depleted AD animals, neuritic dystrophy was enhanced, and increased diffuse-like plaques and fewer compact-like plaques were observed. Removal of PLX5622 elicited microglial repopulation and subsequent plaque remodeling, resulting in more compact plaques predominating microglia-repopulated regions. We found that microglia limit diffuse plaques by maintaining compact-like plaque properties, thereby blocking the progression of neuritic dystrophy. Microglial repopulation reverses these effects. Collectively, we show that microglia are neuroprotective through maintenance of plaque compaction and morphologies during peak disease progression.

Project description:PurposeTo evaluate differences in the structural connectome among patients with normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer disease (AD) and to determine associations between the structural connectome and cortical amyloid deposition.Materials and methodsPatients enrolled in a multicenter biomarker study (Alzheimer's Disease Neuroimaging Initiative [ADNI] 2) who had both baseline diffusion-tensor (DT) and florbetapir positron emission tomography (PET) data at the time of data analyses in November 2012 were studied. All institutions received institutional review board approval. There were 102 patients in ADNI 2 who met criteria for analysis. Patients' T1-weighted images were automatically parcellated into cortical regions of interest. Standardized uptake value ratio (SUVr) was calculated from florbetapir PET images for composite cortical regions (frontal, cingulate, parietal, and temporal). Structural connectome graphs were created from DT images, and connectome topology was analyzed in each region by using graph theoretical metrics. Analysis of variance of structural connectome metrics and florbetapir SUVr across diagnostic group was performed. Linear mixed-effects models were fit to analyze the effect of florbetapir SUVr on structural connectome metrics.ResultsDiagnostic group (NC, MCI, or AD) was associated with changes in weighted structural connectome metrics, with decreases from the NC group to the MCI group to the AD group shown for (a) strength in the bilateral frontal, right parietal, and bilateral temporal regions (P < .05); (b) weighted local efficiency in the left temporal region (P < .05); and (c) weighted clustering coefficient in the bilateral frontal and left temporal regions (P < .05). Increased cortical florbetapir SUVr was associated with decreases in weighted structural connectome metrics; namely, strength (P = .00001), weighted local efficiency (P = .00001), and weighted clustering coefficient (P = .0006), independent of brain region. For every 0.1-unit increase in florbetapir SUVr, there was a 14% decrease in strength, an 11% decrease in weighted local efficiency, and a 9% decrease in weighted clustering coefficient, regardless of the analyzed cortical region or, in the case of weighted local efficiency and clustering coefficient, diagnostic group.ConclusionIncreased amyloid burden, as measured with florbetapir PET imaging, is related to changes in the topology of the large-scale cortical network architecture of the brain, as measured with graph theoretical metrics of DTI tractography, even in the preclinical stages of AD. Online supplemental material is available for this article.

Dataset Information

Collagenous Alzheimer amyloid plaque component impacts on the compaction of amyloid-? plaques.

Publications

Collagenous Alzheimer amyloid plaque component impacts on the compaction of amyloid-β plaques.

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