ѻý

Alzheimer's Disease and Sleep Patterns

<ѻý class="mpt-content-deck">— Study suggests independent links between sleep features and tau, amyloid burden
Last Updated June 18, 2019
MedpageToday
An EEG of the brain activity of a sleeping person.

Sleep patterns predicted levels of Alzheimer's pathology proteins tau and amyloid beta (Aβ), a preliminary study of cognitively normal older adults suggested.

A decrease in slow oscillations and sleep spindle synchronization on electroencephalogram (EEG) sleep recordings was linked with higher tau, while reduced slow-wave-activity amplitude was tied to higher Aβ levels, reported Matthew Walker, PhD, of the University of California Berkeley, and colleagues.

Changes in sleep duration over decades also predicted Aβ and tau burden later in life, they added.

"These results suggest that a night of polysomnography may aid in evaluating tau and Aβ burden, and that treating sleep deficiencies within decade-specific time windows may serve in delaying Alzheimer's disease progression," they wrote in the .

Two types of hippocampal sleep waves, slow oscillations and sleep spindles, are synced in young people, but may become uncoordinated in old age. Several studies have linked to the progression of Alzheimer's disease; recently, non-rapid eye movement (non-REM) sleep slow wave activity was shown to be inversely related to Alzheimer's pathology.

But these studies leave key questions unanswered, Walker and colleagues observed: it's unclear whether certain sleep features are tied to tau only -- separate from those linked to Aβ -- and it's unknown when sleep changes may signal elevated pathology later.

In this analysis, researchers used polysomnography and retrospective questionnaires to study 101 cognitively normal adults from the longitudinal Berkeley Aging Cohort Study who had concurrent PET and MRI data available. A subset of 31 participants completed a sleep EEG assessment, and 95 people completed a retrospective questionnaire about lifespan sleep duration and sleep quality change.

The EEG data showed that the severity of impaired slow oscillation-sleep spindle coupling predicted greater medial temporal lobe tau burden. This coupling impairment was unique and specific to tau accumulation, with no association with Aβ burden.

A non-REM EEG signature -- specifically, impairments in 0.6-1Hz slow-wave-activity -- predicted cortical Aβ, but this slow-wave-activity was not associated with tau in the medial temporal lobe or any other cortical region.

When Alzheimer's pathology and retrospective, self-reported changes in sleep duration were compared, sleep patterns across the lifespan appeared to predict late-life Aβ and tau burden, not only on a decade-by-decade basis, but in overall changes across the adult lifespan. "This finding may suggest that decreasing sleep duration in mid to late life is significantly associated with an increased risk of late-life Aβ burden, and that a profile of maintained (or even subtle increase) in sleep duration throughout this time period is statistically associated with a reduced predicted risk of Aβ accumulation in late life," the researchers noted.

These preliminary results are limited by small sample sizes and subjective bias, but may signify periods when targeted sleep treatment could be most effective, Walker and colleagues added. "If validated in larger longitudinal studies, these sleep-sensitive windows would have the potential to be included in public health recommendations with the goal shifting from a model of late-stage Alzheimer's disease treatment to earlier-life Alzheimer's disease prevention," they wrote.

Disclosures

The study was supported by the National Institutes of Health. Avid 35 Radiopharmaceuticals enabled the use of the 18F-flortaucipir radiotracer, but did not provide direct funding and were not involved in data analysis or interpretation.

The authors disclosed no relevant relationships with industry.

Primary Source

Journal of Neuroscience

Winer J, et al "Sleep as a potential biomarker of tau and β-amyloid burden in the human brain" J Neurosci 2019; DOI: 10.1523/JNEUROSCI.0503-19.2019.