Microglial extracellular vesicles induce Alzheimer's disease-related cortico-hippocampal network dysfunction.

Alzheimer’s disease cortical-hippocampal network entorhinal cortex extracellular vesicles microglia

Journal

Brain communications
ISSN: 2632-1297
Titre abrégé: Brain Commun
Pays: England
ID NLM: 101755125

Informations de publication

Date de publication:
2023
Historique:
received: 05 01 2023
revised: 06 04 2023
accepted: 30 05 2023
medline: 8 6 2023
pubmed: 8 6 2023
entrez: 8 6 2023
Statut: epublish

Résumé

β-Amyloid is one of the main pathological hallmarks of Alzheimer's disease and plays a major role in synaptic dysfunction. It has been demonstrated that β-amyloid can elicit aberrant excitatory activity in cortical-hippocampal networks, which is associated with behavioural abnormalities. However, the mechanism of the spreading of β-amyloid action within a specific circuitry has not been elucidated yet. We have previously demonstrated that the motion of microglia-derived large extracellular vesicles carrying β-amyloid, at the neuronal surface, is crucial for the initiation and propagation of synaptic dysfunction along the entorhinal-hippocampal circuit. Here, using chronic EEG recordings, we show that a single injection of extracellular vesicles carrying β-amyloid into the mouse entorhinal cortex could trigger alterations in the cortical and hippocampal activity that are reminiscent of those found in Alzheimer's disease mouse models and human patients. The development of EEG abnormalities was associated with progressive memory impairment as assessed by an associative (object-place context recognition) and non-associative (object recognition) task. Importantly, when the motility of extracellular vesicles, carrying β-amyloid, was inhibited, the effect on network stability and memory function was significantly reduced. Our model proposes a new biological mechanism based on the extracellular vesicles-mediated progression of β-amyloid pathology and offers the opportunity to test pharmacological treatments targeting the early stages of Alzheimer's disease.

Identifiants

pubmed: 37288314
doi: 10.1093/braincomms/fcad170
pii: fcad170
pmc: PMC10243901
doi:

Types de publication

Journal Article

Langues

eng

Pagination

fcad170

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.

Déclaration de conflit d'intérêts

The authors declare no confilct of interests.

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Auteurs

Chiara Falcicchia (C)

National Research Council (CNR) Institute of Neuroscience, Pisa 56124, Italy.

Francesca Tozzi (F)

National Research Council (CNR) Institute of Neuroscience, Pisa 56124, Italy.
Bio@SNS laboratory, Scuola Normale Superiore, Pisa 56124, Italy.

Martina Gabrielli (M)

National Research Council (CNR) Institute of Neuroscience, Vedano al Lambro, Monza (MB) 20854, Italy.

Stefano Amoretti (S)

National Research Council (CNR) Institute of Neuroscience, Pisa 56124, Italy.

Greta Masini (G)

National Research Council (CNR) Institute of Neuroscience, Pisa 56124, Italy.

Gabriele Nardi (G)

National Enterprise for nanoScience and nanoTechnology (NEST), Istituto Nanoscienze, Consiglio Nazionale delle Ricerche (CNR) and Scuola Normale Superiore Pisa, Pisa 56127, Italy.

Stefano Guglielmo (S)

National Research Council (CNR) Institute of Neuroscience, Pisa 56124, Italy.
Bio@SNS laboratory, Scuola Normale Superiore, Pisa 56124, Italy.

Gian Michele Ratto (GM)

National Enterprise for nanoScience and nanoTechnology (NEST), Istituto Nanoscienze, Consiglio Nazionale delle Ricerche (CNR) and Scuola Normale Superiore Pisa, Pisa 56127, Italy.

Ottavio Arancio (O)

Department of Pathology and Cell Biology, The Taub Institute for Research on Alzheimer's Disease and the Aging Brain and Department of Medicine, Columbia University, New York, NY 10032, USA.

Claudia Verderio (C)

National Research Council (CNR) Institute of Neuroscience, Vedano al Lambro, Monza (MB) 20854, Italy.

Nicola Origlia (N)

National Research Council (CNR) Institute of Neuroscience, Pisa 56124, Italy.

Classifications MeSH