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Rescue of sleep-dependent brain rhythm function to slow Alzheimer’s disease

Patients with Alzheimer’s disease (AD) experience sleep disturbances, including disruption in slow-wave sleep (SWS). Slow oscillations (≤1 Hz), a brain rhythm prevalent during SWS, play a role in memory consolidation. Interestingly, patients with AD exhibit slow oscillations of low amplitude, which might contribute to their memory impairments. The mechanisms underlying slow-wave disruptions in AD remain unknown. Slow oscillations originate in the neocortex. Cortical neurons from all layers oscillate between UP and DOWN states during slow oscillations. Astrocytes are known to support neuronal circuit functions, and disruptions in astrocyte activity might contribute to slow-wave aberrations. Here, we investigated astrocytic contributions to slow-wave disruptions in an animal model of beta-amyloidosis (APP mice). First, we monitored astrocytic calcium transients to determine whether astrocytic calcium dynamics were disrupted in APP mice. Fourier transform analysis revealed that the power, but not the frequency of astrocytic calcium transients, was disrupted in young APP mice. This suggested calcium dynamic of astrocytic network was altered and might contribute to the disruption of slow waves in APP mice. Second, we used optogenetics to synchronize cortical astrocyte activity at 0.6 Hz to drive slow oscillations in APP mice. Our results showed that optogenetic activation of ChR2-expressing astrocytes at the endogenous frequency of slow waves restored slow-wave power. Furthermore, chronic optogenetic stimulation of astrocytes at 0.6Hz for 14 or 28 days reduced amyloid plaque deposition, prevented calcium overload in neurites, and improved memory performance in APP mice. These results revealed a malfunction of the astrocytic network driving slow-wave disruptions, and suggested a novel target to restore slow-wave power in APP mice, with translational potential to treat AD.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/45512
Date24 January 2023
CreatorsLee, Yee Fun
ContributorsBacskai, Brian, Kastanenka, Ksenia
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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