Characterizing sleep-wake activity patterns to detect early Alzheimer's disease in normal older individuals

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PROJECT SUMMARY/ABSTRACT Recent work has established a connection between disrupted sleep and Alzheimer’s disease that begins many years before memory impairment or dementia. Many of the brain regions involved in regulating daily patterns of sleep-wake behavior are also the earliest to be affected in the progression of Alzheimer’s disease. Therefore, understanding how sleep-wake patterns change during the earliest stages of Alzheimer’s disease may lead to better disease detection and treatment intervention strategies. Actigraphy watches, which use technology similar to the accelerometers in our phones and smartwatches, can be used to collect sleep-wake activity data outside the laboratory on a massive scale. By analyzing sleep-wake activity collected from thousands of cognitively healthy older adults, this project will determine whether differences in daily activity patterns are able to forecast subsequent memory decline and Alzheimer’s disease diagnosis. Additionally, in order to understand how early Alzheimer’s disease-related changes in the brain affect sleep, we will collect brain imaging and fluid markers of Alzheimer’s disease along with sleep-wake rhythm data from a local cohort of older adults. High-resolution structural brain imaging, combined with sleep-wake activity phenotypes, will allow for the identification of sleep- wake dysfunction signatures linked to specific pathological brain changes. This research proposal leverages big data in parallel with rich neuroimaging in a multimodal approach which will advance our understanding of the relationship between sleep and Alzheimer’s disease with important clinical implications.