Sleep and its regulation: An emerging pathogenic and treatment frontier in Alzheimer’s disease
Introduction
Alzheimer’s disease (AD) is clinically heterogeneous, with numerous risk factors that affect its clinical and neuropathologic course. Recent advances in neuroimaging and biomarkers, have led to AD being re-conceptualized with pathological processes that begin well before clinical symptoms and which evolve with progressive neuropathological neurodegenerative changes. The clinical symptoms manifest through a spectrum that can include subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and mild-severe AD dementia (Bateman et al., 2012; Jack et al., 2018). Table 1 provides the nomenclature associated with the AD continuum as outlined by Jack and colleagues (2018) (Jack et al., 2018). The long asymptomatic period of AD pathophysiology opens up opportunities for early intervention to prevent clinical symptom evolution and dementia.
Recently, there has been growing interest in the sleep disruption associated with AD across this continuum, and as an important component of AD pathophysiology (Mander et al., 2016). It is hypothesized that sleep disturbances might present prior to other clinical symptoms, contribute to the preclinical cascade of neuropathology, and emerge when individuals have objective measurable impairment in cognition (Fig. 1).
Sleep disturbances are common in AD, highly disruptive to quality of life (Petrovsky et al., 2018), increase caregiver burden (Okuda et al., 2019), and are reported to be a leading cause of patients requiring institutional care (Bianchetti et al., 1995). A recent meta-analysis of 27 observational studies concluded that ∼15 % of AD cases could be delayed in onset or potentially prevented through effective approaches to address sleep disorders (Bubu et al., 2017). While broad disturbances in sleep have been recognized in AD for decades, more recent efforts have elucidated overlapping mechanisms underlying sleep disturbances and AD pathophysiology, highlighting the potential of treating specific aspects of sleep disruption as a disease modifying therapy (reviewed by Cedernaes et al., 2017; Mander et al., 2016).
In this review, we critically evaluate the evidence for the emerging link between sleep and AD pathophysiology (Box 1). We review subjective and objective methods for sleep assessment in patients along the spectrum of AD, the evidence for sleep disorders as a risk factor for AD, as well as the relationship between sleep and disease pathogenesis. We conclude with a review of potential treatment targets.
The historical and current evaluation of the literature is complicated by the different reference standards for AD diagnosis, from clinically-based diagnosis with lower rates of accuracy, to the new evolving biomarker-based diagnosis and the longstanding historical gold standard of neuropathologically verified disease. Only recently have well-validated and accurate CSF assays and PET biomarkers become available for diagnostic purposes (Jack et al., 2018). Within the biomarker-based criteria there are still challenges to address including studies that have relied exclusively on CSF Aβ for diagnostic reporting. While low levels of CSF Aβ42 are commonly reported for diagnostic purposes, assays and studies vary in the cut-off points used to indicate plaque accumulation (Ju et al., 2013; Molano et al., 2017; Varga et al., 2016). Furthermore, an increase of CSF Aβ42 prior to plaque formation has been proposed (Varga et al., 2016), but requires further validation.
Section snippets
Sleep across the Alzheimer’s disease spectrum
Estimates of the prevalence of sleep disorders in AD vary between studies, with one study reporting that 65% of patients with AD or MCI met the diagnostic criteria for a major sleep disorder, including insomnia, sleep disordered breathing, REM sleep behaviour disorder, restless legs syndrome, and excessive daytime sleepiness (Guarnieri et al., 2012). With the increasing availability and utilization of a wide variety of tools including wearables to evaluate sleep, the prevalence of specific
Sleep disturbance as a risk factor for cognitive decline or dementia
In addition to the evidence that sleep disturbances are associated with AD biomarkers in cognitively normal individuals (e.g., Branger et al., 2016; Carvalho et al., 2018; Spira et al., 2013), which suggests that sleep disturbances are an early symptom in the preclinical stage of the AD continuum, longitudinal studies also identify sleep as a risk factor for dementia. Most of these longitudinal studies do not measure AD biomarkers, so it is unknown whether the sleep disturbances occur prior to
Beyond a symptom: Sleep disruption contributes to Alzheimer’s disease pathogenesis
Although the precise mechanisms leading to AD are still a major focus of investigation and debate, the accumulation of misfolded Aβ and tau proteins remain the key pathological hallmarks of the disease (Ittner and Götz, 2011), with evidence that sleep disturbances directly contribute to Aβ metabolism, clearance, and deposition (Ju et al., 2014).
Mechanisms underlying the relationship between sleep disturbances and Alzheimer’s disease
There is substantial evidence that sleep disturbances occur throughout the AD spectrum and that sleep may directly affect the accumulation of Aβ and tau. Table 5 summarizes some of the proposed mechanisms driving the relationship between AD and sleep.
Treating sleep disorders
Treating sleep disorders in patients with AD is becoming a topic of greater importance given its potential role in the pathogenesis and course of the disease. There are several potential mechanisms underlying the relationship between sleep and AD from neurodegeneration of sleep promoting brain regions to changes in neurotransmitters and circadian rhythms, while there is also growing evidence that sleep is not only a symptom of the underlying pathology but that sleep disturbances contribute to
Conclusion
There is growing evidence suggesting that sleep is a potential therapeutic target and novel outcome measure for AD. Sleep will be an important component of a prevention platform for dementia: personalizing treatment and stratifying risk. Given AD is a heterogenous multifactorial disease, we predict only a subset of AD cases have sleep as a critical risk factor. The goal will be to identify those individuals who would benefit most from interventions targeting sleep as a way to change the
Acknowledgments
The authors gratefully acknowledge funding from Michael Smith Foundation for Health Research, Canada (BAK, HBN), CIHR Banting, Canada (#378933) (BAK), Pacific Alzheimer Research Foundation (HBN), The Association for Frontotemporal Dementia (HBN), and NIH-NINDS, United States (#K99NS109909) (BAK). The authors would also like to thank Meghan Chen for her input and editing support as well as Alexandre Shadyab for help with Fig. 1.
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