Understanding the interplay of sleep and aging: Methodological challenges

Muehlroth, Beate E.; Werkle‐Bergner, Markus

doi:10.1111/psyp.13523

Cited by 73 publications

(61 citation statements)

References 181 publications

(312 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the literature, there is no agreement on which approach is to be preferred [31][32][33]. In the present study, we applied both methods: a visual identification of spindles by two independent scorers and, then, an automatic algorithm (with default settings) for sleep spindle quantification [34] to artifact-free stage S2 epochs at Cz channel. The following statistical analyses involved only patients with at least one clearly present visually detected sleep spindle in the recording.…”

Section: Discussionmentioning

confidence: 99%

Sleep in disorders of consciousness: behavioral and polysomnographic recording

Mertel

Pavlov

Barner

et al. 2020

BMC Med

View full text Add to dashboard Cite

Background Sleep-wakefulness cycles are an essential diagnostic criterion for disorders of consciousness (DOC), differentiating prolonged DOC from coma. Specific sleep features, like the presence of sleep spindles, are an important marker for the prognosis of recovery from DOC. Based on increasing evidence for a link between sleep and neuronal plasticity, understanding sleep in DOC might facilitate the development of novel methods for rehabilitation. Yet, well-controlled studies of sleep in DOC are lacking. Here, we aimed to quantify, on a reliable evaluation basis, the distribution of behavioral and neurophysiological sleep patterns in DOC over a 24-h period while controlling for environmental factors (by recruiting a group of conscious tetraplegic patients who resided in the same hospital). Methods We evaluated the distribution of sleep and wakefulness by means of polysomnography (EEG, EOG, EMG) and video recordings in 32 DOC patients (16 unresponsive wakefulness syndrome [UWS], 16 minimally conscious state [MCS]), and 10 clinical control patients with severe tetraplegia. Three independent raters scored the patients’ polysomnographic recordings. Results All but one patient (UWS) showed behavioral and electrophysiological signs of sleep. Control and MCS patients spent significantly more time in sleep during the night than during daytime, a pattern that was not evident in UWS. DOC patients (particularly UWS) exhibited less REM sleep than control patients. Forty-four percent of UWS patients and 12% of MCS patients did not have any REM sleep, while all control patients (100%) showed signs of all sleep stages and sleep spindles. Furthermore, no sleep spindles were found in 62% of UWS patients and 21% of MCS patients. In the remaining DOC patients who had spindles, their number and amplitude were significantly lower than in controls. Conclusions The distribution of sleep signs in DOC over 24 h differs significantly from the normal sleep-wakefulness pattern. These abnormalities of sleep in DOC are independent of external factors such as severe immobility and hospital environment.

show abstract

Section: Discussionmentioning

confidence: 99%

Sleep in disorders of consciousness: behavioral and polysomnographic recording

Mertel

Pavlov

Barner

et al. 2020

BMC Med

View full text Add to dashboard Cite

show abstract

“…55 The decrement in slow wave amplitude also produces a well-described loss of stage 2 sleep scoring due to technical limitations with use of an absolute slow wave size threshold rule for scoring each segment of NREM sleep as stage N2 vs N3 sleep. 40,46 These considerations certainly influence the interpretation of our observations demonstrating a shift in coupling subtypes in stage N2 sleep with increasing age. The stage N2 mix of slow wave subtypes is expected to include more N3 slow wave subtypes as age increases due to these sleep stage scoring rules.…”

Section: Discussionmentioning

confidence: 90%

“…Aging is associated with decreased amplitude of slow waves, 46 and changes in slow wave morphology have also been described with increasing age. 55 The decrement in slow wave amplitude also produces a well-described loss of stage 2 sleep scoring due to technical limitations with use of an absolute slow wave size threshold rule for scoring each segment of NREM sleep as stage N2 vs N3 sleep.…”

Section: Discussionmentioning

confidence: 99%

“…[36][37][38][39] Notably, the distinction between sleep stages is imperfect, and most often a mixing of lighter and deeper sleep occurs, particularly in transitions between sleep stages. 46,47 Further, individual variability of slow waves and spindles has been demonstrated with regard to frequency and timing aspects of coupling. 48 Nonetheless, dividing sleep into stages N2 and N3 sleep demonstrated that distinct slow wave and spindle coupling features can be distinguished among the composition of slow waves from stages N2 and N3 sleep (Illustrated in Figure 2).…”

Section: Stage N2 and Stage N3 Slow Waves Demonstrate Distinct Composmentioning

confidence: 99%

See 1 more Smart Citation

The Aging Slow Wave: A Shifting Amalgam of Distinct Slow Wave and Spindle Coupling Subtypes Define Slow Wave Sleep Across the Human Lifespan

McConnell

Kronberg

Teale

et al. 2020

Preprint

View full text Add to dashboard Cite

Study ObjectivesSlow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan. MethodsCoupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles. ResultsTwo different subtypes of spindles were identified during the upstates of (distinct) slow waves: an "early-fast" spindle, more common in stage N2 sleep, and a "late-fast" spindle, more common in stage N3. We further found stages N2 and N3 sleep are composed of two discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails during old age. ConclusionsDistinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep.Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease. Statement of SignificanceSlow waves of nonrapid eye movement sleep couple with sleep spindles in a process hypothesized to support memory functions. This coupling has recently gained interest as a possible biomarker of cognitive aging and onset of Alzheimer's disease. Most studies have been limited by an assumption that all slow waves (and coupled spindles) are fundamentally the same physiological events. Here we demonstrate that distinct subtypes of slow waves and their coupled spindles can be identified in human sleep. A mixture of different slow wave and spindle subtypes shifts in composition during lighter versus deeper sleep, and aging favors the deep sleep subtypes. These data should inform any future attempts to use slow wave sleep as a biomarker or clinical interventional target. Background: Slow waves occur during stages N2 and N3 Non-Rapid Eye Movement (NREM) sleep and are associated with large-scale synchronization of neuronal populations. 1-3 Spindlesare generated and propagated via cortical-thalamic loops, with timing input from the reticular nucleus of the thalamus. 4,5 In the process of aging, loss of slow waves and sleep spindles is highly correlated with cognitive decline, and abnormal slow wave neuronal circuitry is implicated in the pathogenesis of Alzheimer's disease 6 .

show abstract

“…Causes and appearance of age-related changes in sleep are manifold and diverse 83 . There is no perfect way to measure sleep without disrupting routine 84 .…”

Section: Discussionmentioning

confidence: 99%

Self-reported sleep problems are related to cortical thinning in aging but not memory decline and amyloid-β accumulation – results from the Lifebrain consortium

Fjell

Sørensen

Amlien

et al. 2020

Preprint

View full text Add to dashboard Cite

BackgroundOlder persons with poor sleep are more likely to develop neurodegenerative disease, but the causality underlying this association is unclear. To move towards explanation, we examine whether sleep quality and quantity are similarly associated with brain changes across the adult lifespan.MethodsAssociations between self-reported sleep parameters (Pittsburgh Sleep Quality Index;PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n=2205, 4363 MRIs, 18-92 years). Analyses were augmented by considering episodic memory change, gene expression from the Allen Human Brain Atlas, and amyloid-beta (Aβ) accumulation (n=1980).ResultsPSQI components sleep problems and low sleep quality were related to thinning of the right lateral temporal cortex. The association with sleep problems emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. BMI and symptoms of depression had negligible effects. Sleep problems were neither related to longitudinal change in episodic memory function nor to Aβ accumulation, suggesting that sleep-related cortical changes were independent of AD neuropathology and cognitive decline.ConclusionWorse self-reported sleep in later adulthood was associated with more cortical thinning in regions of high expression of genes related to oligodendrocytes and S1 pyramidal neurons, but not to Aβ accumulation or memory decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes, except for a few restricted regions, indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

show abstract

Understanding the interplay of sleep and aging: Methodological challenges

Cited by 73 publications

References 181 publications

Sleep in disorders of consciousness: behavioral and polysomnographic recording

Sleep in disorders of consciousness: behavioral and polysomnographic recording

The Aging Slow Wave: A Shifting Amalgam of Distinct Slow Wave and Spindle Coupling Subtypes Define Slow Wave Sleep Across the Human Lifespan

Self-reported sleep problems are related to cortical thinning in aging but not memory decline and amyloid-β accumulation – results from the Lifebrain consortium

Contact Info

Product

Resources

About