Sleep disturbances and Alzheimer’s disease: a multiscale approach from exposome to neurobiology and precision medicine

Comprehensive Summary

In this review, Tahmasian et al. examines the link between sleep problems and Alzheimer’s disease (AD) and proposes a “stream-like” model for this relationship. They explain the role of genetics, the environment, lifestyle factors, and the process of aging in accelerating the process of brain aging and the body's internal clock, increasing wake-promoting factors like orexin, interfering with metabolism, and inducing low-grade inflammation. All these factors cause sleep to become fragmented and deep slow-wave sleep to decrease, leading to brain-wide inflammation, problems with the brain's waste removal system, and the accumulation of beta amyloid and tau. The authors also summarize recent neuroimaging work that shows how poor sleep is linked to changes in brain structure and function in AD. Finally, they emphasize the importance of taking individual differences into consideration and explain how artificial intelligence and other computer-based tools can integrate exposome, sleep, imaging, and biomarkers to provide a precise and individualized understanding of the risk for sleep and AD.

Outcomes and Implications

This article is important because sleep problems may be linked to how Alzheimer’s develops, not just to what happens later. Poor sleep may play a role in amyloid and tau buildup and gradual brain damage. Additionally, the paper explores the potential of AI/machine learning in identifying patterns within large amounts of data and identifying potential risks. Although these ideas still require stronger clinical evidence, the authors suggest that sleep monitoring and AI-based risk tools could be incorporated into the treatment of people who are at risk of developing AD.