Longitudinal relationships between Alzheimer's disease pathophysiology, local sleep expression, and sleep-dependent memory across preclinical stages

About This Grant

PROJECT SUMMARY Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-β (Aβ) plaques, brain inflammation, and neurofibrillary tau tangles beginning up to two decades prior to clinical symptom onset. Increasing evidence indicates that sleep disturbance may be a modifiable risk factor impacting Alzheimer’s disease risk. Recent cross-sectional data has identified signature deficits in the local expression of sleep that may track with the buildup of Aβ, brain inflammation, and tau. However, typical approaches quantifying local sleep expression conflate contributions from distinct biological sources, including the overall rate of background spiking activity in brain cells, the balance between excitatory and inhibitory neurons, and the regulation of brain oscillations, all of which may be differentially impacted by distinct components of Alzheimer’s disease pathophysiology. For example, Aβ and tau impact the excitability of brain cells in opposing ways. This means that local sleep deficits likely change longitudinally as AD biomarkers buildup in the brain. Careful characterization of these effects longitudinally are critical to isolate the biological mechanisms linking local sleep expression with the evolution of Alzheimer’s disease pathophysiology throughout the brain and impairments in cognitive function. However, there are no published data linking longitudinal changes in local sleep expression with the progression of AD pathophysiology over time. To address this critical knowledge gap, we will use an innovative multimodal neuroimaging design combining polysomnography with high-density electroencephalography and high-resolution structural magnetic resonance imaging of medial temporal lobe (MTL) neurite density and structural volume combined with fluid biomarkers of brain inflammation, AD pathology, and neuronal integrity and episodic and procedural sleep-dependent memory tasks. Using these methods, we will map how local sleep changes in relation to the buildup of AD pathophysiology and memory decline over a two-year period. We will test the following hypotheses. (1) Increasing frontal deficits in slow waves will be apparent in individuals with Aβ plaques, while deficits in sleep spindles, slow wave-sleep spindle coupling, and measures of background spiking activity and the balance between excitatory and inhibitory neuron firing over parietal cortex will be more apparent in those with more brain inflammation, tau pathology, and MTL atrophy. (2) Distinct local deficits in sleep expression will predict longitudinal episodic and procedural memory decline. Findings from the proposed study will provide novel insight into how the buildup of AD pathophysiology relates to the change in local sleep expression and sleep-dependent memory over time, providing a map of candidate modifiable sleep targets for interventions to preserve cognition in a manner specific to AD pathophysiological feature and biomarker-defined preclinical stage.