Parietal Fast Sleep Spindle Density Decrease in Alzheimer's Disease and Amnesic Mild Cognitive Impairment

Sex differences in the association of sleep spindle density and cognitive performance among community-dwelling middle-aged and older adults with obstructive sleep apnea

Recent studies have found associations between obstructive sleep apnea and cognitive decline. The underlying mechanisms are still unclear. Here, we investigate the associations between changes in micro-architecture, specifically sleep spindles, and cognitive function in community-dwelling middle-aged and older adults, some with obstructive sleep apnea, with a focus on sex differences. A total of 125 voluntary participants (mean age 66.0 ± 6.4 years, 64 females) from a larger cohort (participants of the Brain in Motion Studies I and II) underwent 1 night of in-home polysomnography and a neuropsychological battery (sleep and cognitive testing were conducted within 2 weeks of each other). A semi-automatic computerized algorithm was used to score polysomnography data and detect spindle characteristics in non-rapid eye movement Stages 2 and 3 in both frontal and central electrodes. Based on their apnea-hypopnea index, participants were divided into those with no obstructive sleep apnea (apnea-hypopnea index < 5 per hr, n = 21), mild obstructive sleep apnea (5 ≥ apnea-hypopnea index < 15, n = 47), moderate obstructive sleep apnea (15 ≥ apnea-hypopnea index < 30, n = 34) and severe obstructive sleep apnea (apnea-hypopnea index ≥ 30, n = 23). There were no significant differences in spindle characteristics between the four obstructive sleep apnea severity groups. Spindle density and percentage of fast spindles were positively associated with some verbal fluency measures on the cognitive testing. Sex might be linked with these associations. Biological sex could play a role in the associations between spindle characteristics and some verbal fluency measures. Obstructive sleep apnea severity was not found to be a contributing factor in this non-clinical community-dwelling cohort.

Memory performance mediates subjective sleep quality associations with cerebrospinal fluid Alzheimer's disease biomarker levels and hippocampal volume among individuals with mild cognitive symptoms

Sleep disturbances are prevalent in Alzheimer's disease (AD), affecting individuals during its early stages. We investigated associations between subjective sleep measures and cerebrospinal fluid (CSF) biomarkers of AD in adults with mild cognitive symptoms from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study, considering the influence of memory performance. A total of 442 participants aged >50 years with a Clinical Dementia Rating (CDR) score of 0.5 completed the Pittsburgh Sleep Quality Index questionnaire and underwent neuropsychological assessment, magnetic resonance imaging acquisition, and CSF sampling. We analysed the relationship of sleep quality with CSF AD biomarkers and cognitive performance in separated multivariate linear regression models, adjusting for covariates. Poorer cross-sectional sleep quality was associated with lower CSF levels of phosphorylated tau and total tau alongside better immediate and delayed memory performance. After adjustment for delayed memory scores, associations between CSF biomarkers and sleep quality became non-significant, and further analysis revealed that memory performance mediated this relationship. In post hoc analyses, poorer subjective sleep quality was associated with lesser hippocampal atrophy, with memory performance also mediating this association. In conclusion, worse subjective sleep quality is associated with less altered AD biomarkers in adults with mild cognitive symptoms (CDR score 0.5). These results could be explained by a systematic recall bias affecting subjective sleep assessment in individuals with incipient memory impairment. Caution should therefore be exercised when interpreting subjective sleep quality measures in memory-impaired populations, emphasising the importance of complementing subjective measures with objective assessments.

Rescuing impaired hippocampal-cortical interactions and spatial reorientation learning and memory during sleep in a mouse model of Alzheimer's disease using hippocampal 40 Hz stimulation

In preclinical Alzheimer's disease (AD), spatial learning and memory is impaired. We reported similar impairments in 3xTg-AD mice on a virtual maze (VM) spatial-reorientation-task that requires using landmarks to navigate. Hippocampal (HPC)-cortical dysfunction during sleep (important for memory consolidation) is a potential mechanism for memory impairments in AD. We previously found deficits in HPC-cortical coordination during sleep coinciding with VM impairments the next day. Some forms of 40 Hz stimulation seem to clear AD pathology in mice, and improve functional connectivity in AD patients. Thus, we implanted a recording array targeting parietal cortex (PC) and HPC to assess HPC-PC coordination, and an optical fiber targeting HPC for 40 Hz or sham optogenetic stimulation in 3xTg/PV cre mice. We assessed PC delta waves (DW) and HPC sharp wave ripples (SWRs). In sham mice, SWR-DW cross-correlations were reduced, similar to 3xTg-AD mice. In 40 Hz mice, this phase-locking was rescued, as was performance on the VM. However, rescued HPC-PC coupling no longer predicted performance as in NonTg animals. Instead, DWs and SWRs independently predicted performance in 40 Hz mice. Thus, 40 Hz stimulation of HPC rescued functional interactions in the HPC-PC network, and rescued impairments in spatial navigation, but did not rescue the correlation between HPC-PC coordination during sleep and learning and memory. Together this pattern of results could inform AD treatment timing by suggesting that despite applying 40 Hz stimulation before significant tau and amyloid aggregation, pathophysiological processes led to brain changes that were not fully reversed even though cognition was recovered.

Significance Statement

One of the earliest symptoms of Alzheimer's disease (AD) is getting lost in space or experiencing deficits in spatial navigation, which involve navigation computations as well as learning and memory. We investigated cross brain region interactions supporting memory formation as a potential causative factor of impaired spatial learning and memory in AD. To assess this relationship between AD pathophysiology, brain changes, and behavioral alterations, we used a targeted approach for clearing amyloid beta and tau to rescue functional interactions in the brain. This research strongly connects brain activity patterns during sleep to tau and amyloid accumulation, and will aid in understanding the mechanisms underlying cognitive dysfunction in AD. Furthermore, the results offer insight for improving early identification and treatment strategies.

Electroencephalographic slowing during REM sleep in older adults with subjective cognitive impairment and mild cognitive impairment

STUDY OBJECTIVES

In older adults with Alzheimer's disease, slowing of electroencephalographic (EEG) activity during REM sleep has been observed. Few studies have examined EEG slowing during REM in those with mild cognitive impairment (MCI) and none have examined its relationship with cognition in this at-risk population.

METHODS

Two hundred and ten older adults (mean age = 67.0, SD = 8.2 years) underwent comprehensive neuropsychological, medical, and psychiatric assessment and overnight polysomnography. Participants were classified as subjective cognitive impairment (SCI; n = 75), non-amnestic MCI (naMCI, n = 85), and amnestic MCI (aMCI, n = 50). REM EEG slowing was defined as (δ + θ)/(α + σ + β) power and calculated for frontal, central, parietal, and occipital regions. Analysis of variance compared REM EEG slowing between groups. Correlations between REM EEG slowing and cognition, including learning and memory, visuospatial and executive functions, were examined within each subgroup.

RESULTS

The aMCI group had significantly greater REM EEG slowing in the parietal and occipital regions compared to the naMCI and SCI groups (partial η2 = 0.06, p < 0.05 and 0.06, p < 0.05, respectively), and greater EEG slowing in the central region compared to SCI group (partial η2 = 0.03, p < 0.05). Greater REM EEG slowing in parietal (r = -0.49) and occipital regions (r = -0.38 [O1/M2] and -0.33 [O2/M1]) were associated with poorer visuospatial performance in naMCI.

CONCLUSIONS

REM EEG slowing may differentiate older adults with memory impairment from those without. Longitudinal studies are now warranted to examine the prognostic utility of REM EEG slowing for cognitive and dementia trajectories.

Linking activity dyshomeostasis and sleep disturbances in Alzheimer disease

The presymptomatic phase of Alzheimer disease (AD) starts with the deposition of amyloid-β in the cortex and begins a decade or more before the emergence of cognitive decline. The trajectory towards dementia and neurodegeneration is shaped by the pathological load and the resilience of neural circuits to the effects of this pathology. In this Perspective, I focus on recent advances that have uncovered the vulnerability of neural circuits at early stages of AD to hyperexcitability, particularly when the brain is in a low-arousal states (such as sleep and anaesthesia). Notably, this hyperexcitability manifests before overt symptoms such as sleep and memory deficits. Using the principles of control theory, I analyse the bidirectional relationship between homeostasis of neuronal activity and sleep and propose that impaired activity homeostasis during sleep leads to hyperexcitability and subsequent sleep disturbances, whereas sleep disturbances mitigate hyperexcitability via negative feedback. Understanding the interplay among activity homeostasis, neuronal excitability and sleep is crucial for elucidating the mechanisms of vulnerability to and resilience against AD pathology and for identifying new therapeutic avenues.

Hippocampal ripples coincide with "up-state" and spindles in retrosplenial cortex

During NREM sleep, hippocampal sharp-wave ripple (SWR) events are thought to stabilize memory traces for long-term storage in downstream neocortical structures. Within the neocortex, a set of distributed networks organized around retrosplenial cortex (RS-network) interact preferentially with the hippocampus purportedly to consolidate those traces. Transient bouts of slow oscillations and sleep spindles in this RS-network are often observed around SWRs, suggesting that these two activities are related and that their interplay possibly contributes to memory consolidation. To investigate how SWRs interact with the RS-network and spindles, we combined cortical wide-field voltage imaging, Electrocorticography, and hippocampal LFP recordings in anesthetized and sleeping mice. Here, we show that, during SWR, "up-states" and spindles reliably co-occur in a cortical subnetwork centered around the retrosplenial cortex. Furthermore, retrosplenial transient activations and spindles predict slow gamma oscillations in CA1 during SWRs. Together, our results suggest that retrosplenial-hippocampal interaction may be a critical pathway of information exchange between the cortex and hippocampus.

Linking brain structure, cognition, and sleep: insights from clinical data

STUDY OBJECTIVES

To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition.

METHODS

We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links.

RESULTS

Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40).

CONCLUSIONS

Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.

The role of the sleep K-complex on the conversion from mild cognitive impairment to Alzheimer's disease

The present literature points to an alteration of the human K-complex during non-rapid eye movement sleep in Alzheimer's disease. Nevertheless, the few findings on the K-complex changes in mild cognitive impairment and their possible predictive role on the Alzheimer's disease conversion show mixed findings, lack of replication, and a main interest for the frontal region. The aim of the present study was to assess K-complex measures in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease over different cortical regions, comparing them with healthy controls and stable amnesic mild cognitive impairment. We assessed baseline K-complex density, amplitude, area under the curve and overnight changes in frontal, central and parietal midline derivations of 12 amnesic mild cognitive impairment subsequently converted in Alzheimer's disease, 12 stable amnesic mild cognitive impairment and 12 healthy controls. We also assessed delta electroencephalogram power, to determine if K-complex alterations in amnesic mild cognitive impairment occur with modification of the electroencephalogram power in the frequency range of the slow-wave activity. We found a reduced parietal K-complex density in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease compared with stable amnesic mild cognitive impairment and healthy controls, without changes in K-complex morphology and overnight modulation. Both amnesic mild cognitive impairment groups showed decreased slow-wave sleep percentage compared with healthy controls. No differences between groups were observed in slow-wave activity power. Our findings suggest that K-complex alterations in mild cognitive impairment may be observed earlier in parietal regions, likely mirroring the topographical progression of Alzheimer's disease-related brain pathology, and express a frontal predominance only in a full-blown phase of Alzheimer's disease. Consistently with previous results, such K-complex modification occurs in the absence of significant electroencephalogram power changes in the slow oscillations range.

Sleep spindle architecture associated with distinct clinical phenotypes in older adults at risk for dementia

Sleep spindles are a hallmark of non-REM sleep and play a fundamental role in memory consolidation. Alterations in these spindles are emerging as sensitive biomarkers for neurodegenerative diseases of ageing. Understanding the clinical presentations associated with spindle alterations may help to elucidate the functional role of these distinct electroencephalographic oscillations and the pathophysiology of sleep and neurodegenerative disorders. Here, we use a data-driven approach to examine the sleep, memory and default mode network connectivity phenotypes associated with sleep spindle architecture in older adults (mean age = 66 years). Participants were recruited from a specialist clinic for early diagnosis and intervention for cognitive decline, with a proportion showing mild cognitive deficits on neuropsychological testing. In a sample of 88 people who underwent memory assessment, overnight polysomnography and resting-state fMRI, a k-means cluster analysis was applied to spindle measures of interest: fast spindle density, spindle duration and spindle amplitude. This resulted in three clusters, characterised by preserved spindle architecture with higher fast spindle density and longer spindle duration (Cluster 1), and alterations in spindle architecture (Clusters 2 and 3). These clusters were further characterised by reduced memory (Clusters 2 and 3) and nocturnal hypoxemia, associated with sleep apnea (Cluster 3). Resting-state fMRI analysis confirmed that default mode connectivity was related to spindle architecture, although directionality of this relationship differed across the cluster groups. Together, these results confirm a diversity in spindle architecture in older adults, associated with clinically meaningful phenotypes, including memory function and sleep apnea. They suggest that resting-state default mode connectivity during the awake state can be associated with sleep spindle architecture; however, this is highly dependent on clinical phenotype. Establishing relationships between clinical and neuroimaging features and sleep spindle alterations will advance our understanding of the bidirectional relationships between sleep changes and neurodegenerative diseases of ageing.

Semi-Automatic Analysis of Specific Electroencephalographic Patterns during NREM2 Sleep in a Pediatric Population after SARS-CoV-2 Infection

The post-COVID-19 condition is defined by the World Health Organization as the persistence of symptoms or development of new symptoms three months after the initial SARS-CoV-2 infection, lasting for at least two months without a clear explanation. Neuropsychiatric disorders associated with this condition include asthenia, memory and concentration problems, and sleep disturbances. Our study aims to investigate sleep patterns following SARS-CoV-2 infection using EEG findings and a sleep quality questionnaire completed by parents (Sleep Disturbance Scale for Children-SDSC). Notably, our investigation is based on a convenience sample. The patients in our sample, aged 1 to 14 years, are not currently taking any medications; rather, they are undergoing follow-up assessments at the Child Neuropsychiatry department of the University Hospital of Messina for neurodevelopmental evaluations. Specifically, we are analyzing amplitude and power spectrum data in the first five minutes of NREM2 sleep, calculated from EEG recordings obtained via bipolar leads within three months after the onset of the disease. These results will be compared with controls performed on the same subjects in the six months preceding the infection. The focus of the study was sleep spindles, which are generated by the thalamocortical systems and play a role in sleep modulation, memory, and learning. Preliminary analysis suggests a predominant increase in the slow component of the spindles in the right-frontal lead.

Altered sleep behavior strengthens face validity in the ArcAβ mouse model for Alzheimer's disease

Demographic changes will expand the number of senior citizens suffering from Alzheimer's disease (AD). Key aspects of AD pathology are sleep impairments, associated with onset and progression of AD. AD mouse models may provide insights into mechanisms of AD-related sleep impairments. Such models may also help to establish new biomarkers predicting AD onset and monitoring AD progression. The present study aimed to establish sleep-related face validity of a widely used mouse model of AD (ArcAβ model) by comprehensively characterizing its baseline sleep/wake behavior. Chronic EEG recordings were performed continuously on four consecutive days in freely behaving mice. Spectral and temporal sleep/wake parameters were assessed and analyzed. EEG recordings showed decreased non-rapid eye movement sleep (NREMS) and increased wakefulness in transgenic mice (TG). Vigilance state transitions were different in TG mice when compared to wildtype littermates (WT). During NREMS, TG mice had lower power between 1 and 5 Hz and increased power between 5 and 30 Hz. Sleep spindle amplitudes in TG mice were lower. Our study strongly provides sleep-linked face validity for the ArcAβ model. These findings extend the potential of the mouse model to investigate mechanisms of AD-related sleep impairments and the impact of sleep impairments on the development of AD.

Reduced overnight memory consolidation and associated alterations in sleep spindles and slow oscillations in early Alzheimer's disease

Spatial navigation critically underlies hippocampal-entorhinal circuit function that is early affected in Alzheimer's disease (AD). There is growing evidence that AD pathophysiology dynamically interacts with the sleep/wake cycle impairing hippocampal memory. To elucidate sleep-dependent consolidation in a cohort of symptomatic AD patients (n = 12, 71.25 ± 2.16 years), we tested hippocampal place learning by means of a virtual reality task and verbal memory by a word-pair association task before and after a night of sleep. Our results show an impaired overnight memory retention in AD compared with controls in the verbal task, together with a significant reduction of sleep spindle activity (i.e., lower amplitude of fast sleep spindles, p = 0.016) and increased duration of the slow oscillation (SO; p = 0.019). Higher spindle density, faster down-to-upstate transitions within SOs, and the time delay between SOs and nested spindles predicted better memory performance in healthy controls but not in AD patients. Our results show that mnemonic processing and memory consolidation in AD is slightly impaired as reflected by dysfunctional oscillatory dynamics and spindle-SO coupling during NonREM sleep. In this translational study based on experimental paradigms in animals and extending previous work in healthy aging and preclinical disease stages, our results in symptomatic AD further deepen the understanding of the memory decline within a bidirectional relationship of sleep and AD pathology.

The effects of closed-loop auditory stimulation on sleep oscillatory dynamics in relation to motor procedural memory consolidation

STUDY OBJECTIVES

Healthy aging and many disorders show reduced sleep-dependent memory consolidation and corresponding alterations in non-rapid eye movement sleep oscillations. Yet sleep physiology remains a relatively neglected target for improving memory. We evaluated the effects of closed-loop auditory stimulation during sleep (CLASS) on slow oscillations (SOs), sleep spindles, and their coupling, all in relation to motor procedural memory consolidation.

METHODS

Twenty healthy young adults had two afternoon naps: one with auditory stimulation during SO upstates and another with no stimulation. Twelve returned for a third nap with stimulation at variable times in relation to SO upstates. In all sessions, participants trained on the motor sequence task prior to napping and were tested afterward.

RESULTS

Relative to epochs with no stimulation, upstate stimuli disrupted sleep and evoked SOs, spindles, and SO-coupled spindles. Stimuli that successfully evoked oscillations were delivered closer to the peak of the SO upstate and when spindle power was lower than stimuli that failed to evoke oscillations. Across conditions, participants showed similar significant post-nap performance improvement that correlated with the density of SO-coupled spindles.

CONCLUSIONS

Despite its strong effects on sleep physiology, CLASS failed to enhance motor procedural memory. Our findings suggest methods to overcome this failure, including better sound calibration to preserve sleep continuity and the use of real-time predictive algorithms to more precisely target SO upstates and to avoid disrupting endogenous SO-coupled spindles and their mnemonic function. They motivate continued development of CLASS as an intervention to manipulate sleep oscillatory dynamics and improve memory.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.

Quantitative sleep electroencephalogram and cognitive performance in Parkinson's disease with and without rapid eye movement sleep behavior disorder

Introduction

Parkinson's disease (PD) patients with REM sleep behavior disorder (RBD) are at greater risk for cognitive decline and RBD has been associated with alterations in sleep-related EEG oscillations. This study evaluates differences in sleep quantitative EEG (qEEG) and cognition in PD participants with (PD-RBD) and without RBD (PD-no-RBD).

Methods

In this cross-sectional study, polysomnography (PSG)-derived qEEG and a comprehensive level II neuropsychological assessment were compared between PD-RBD (n = 21) and PD-no-RBD (n = 31). Following artifact rejection, qEEG analysis was performed in the frontal and central leads. Measures included Scalp-slow wave (SW) density, spindle density, morphological properties of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in NREM and REM. The neurocognitive battery had at least two tests per domain, covering five cognitive domains as recommended by the Movement Disorders Society Task Force for PD-MCI diagnosis. Differences in qEEG features and cognitive performance were compared between the two groups. Stepwise linear regression was performed to evaluate predictors of cognitive performance. Multiple comparisons were corrected using the Benjamini-Hochberg method.

Results

Spindle density and SW-spindle co-occurrence percent were lower in participants with PD-RBD compared to PD-no-RBD. The PD-RBD group also demonstrated higher theta spectral power during REM. Sleep spindles and years of education, but not RBD, were predictors of cognitive performance.

Conclusion

PD participants with RBD have alterations in sleep-related qEEG compared to PD participants without RBD. Although PD-RBD participants had worse cognitive performance compared to PD-no-RBD, regression models suggest that lower sleep spindle density, rather than presence of RBD, predicts worse comprehensive cognitive score. Future studies should include longitudinal evaluation to determine whether sleep-related qEEG alterations are associated with more rapid cognitive decline in PD-RBD.

Characteristics of macroscopic sleep structure in patients with mild cognitive impairment: a systematic review

Objectives

Conducting a systematic analysis of objective measurement tools to assess the characteristics of macroscopic sleep architecture in patients with mild cognitive impairment (MCI), amnestic MCI (aMCI), and non-amnestic MCI (naMCI) in order to provide sleep disorder guidance for MCI patients.

Methods

PubMed, EMbase, Web of Science, Cochrane Library, CNKI, SinoMed, Wanfang Data, and VIP Data were examined to find literature relating to sleep in patients with MCI, aMCI, and naMCI, with a search time frame of build to April 2023. Following independent literature screening, data extraction, and quality evaluation by two researchers, statistical analysis was performed using RevMan 5.4 software.

Results

Twenty-five papers with 1,165 study subjects were included. Patients with MCI and aMCI were found to have altered total sleep time (TST), reduced sleep efficiency (SE), more wake-time after sleep onset (WASO), longer sleep latency (SL), a higher proportion of N1 stage and a lower proportion of N2 and N3 stage. naMCI was only found to have statistically significant differences in WASO.

Conclusions

The results of this study provide evidence for macroscopic sleep architecture abnormalities among MCI patients with sleep disorders. Maintaining a normal sleep time, improving SE, and reducing sleep fragmentation may have an association with a slowed development of cognitive impairment. Further exploration is required of the effects each component of macroscopic sleep structure after the intervention has on altered sleep disturbance and cognition in MCI, aMCI, and naMCI.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023401937, identifier: CRD42023401937.

Associations of Baseline Sleep Microarchitecture with Cognitive Function After 8 Years in Middle-Aged and Older Men from a Community-Based Cohort Study

Purpose

Prospective studies examining associations between baseline sleep microarchitecture and future cognitive function recruited from small samples with predominantly short follow-up. This study examined sleep microarchitecture predictors of cognitive function (visual attention, processing speed, and executive function) after 8 years in community-dwelling men.

Patients and Methods

Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (2010-2011), with 157 completing baseline (2007-2010) and follow-up (2018-2019) cognitive assessments (trail-making tests A [TMT-A] and B [TMT-B] and the standardized mini-mental state examination [SMMSE]). Whole-night F4-M1 sleep EEG recordings were processed following artifact exclusion, and quantitative EEG characteristics were obtained using validated algorithms. Associations between baseline sleep microarchitecture and future cognitive function (visual attention, processing speed, and executive function) were examined using linear regression models adjusted for baseline obstructive sleep apnoea, other risk factors, and cognition.

Results

The final sample included men aged (mean [SD]) 58.9 (8.9) years at baseline, overweight (BMI 28.5 [4.2] kg/m²), and well educated (75.2% ≥Bachelor, Certificate, or Trade), with majorly normal baseline cognition. Median (IQR) follow-up was 8.3 (7.9, 8.6) years. In adjusted analyses, NREM and REM sleep EEG spectral power was not associated with TMT-A, TMT-B, or SMMSE performance (all p>0.05). A significant association of higher N3 sleep fast spindle density with worse TMT-B performance (B=1.06, 95% CI [0.13, 2.00], p=0.026) did not persist following adjustment for baseline TMT-B performance.

Conclusion

In this sample of community-dwelling men, sleep microarchitecture was not independently associated with visual attention, processing speed, or executive function after 8 years.

Quantitative Sleep Electroencephalogram in Parkinson's Disease: A Case-Control Study

BACKGROUND

Sleep disorders are common in Parkinson's disease (PD) and include alterations in sleep-related EEG oscillations.

OBJECTIVE

This case-control study tested the hypothesis that patients with PD would have a lower density of Scalp-Slow Wave (SW) oscillations and higher slow-to-fast frequencies ratio in rapid eye movement (REM) sleep than non-PD controls. Other sleep-related quantitative EEG (qEEG) features were also examined, including SW morphology, sleep spindles, and Scalp-SW spindle phase-amplitude coupling.

METHODS

Polysomnography (PSG)-derived sleep EEG was compared between PD participants (n = 56) and non-PD controls (n = 30). Following artifact rejection, sleep qEEG analysis was performed in frontal and central leads. Measures included SW density and morphological features of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in Non-REM (NREM) and REM. Differences in qEEG features between PD and non-PD controls were compared using two-tailed Welch's t-tests, and correction for multiple comparisons was performed per the Benjamini-Hochberg method.

RESULTS

SW density was lower in PD than in non-PD controls (F = 13.5, p' = 0.003). The PD group also exhibited higher ratio of slow REM EEG frequencies (F = 4.23, p' = 0.013), higher slow spindle peak frequency (F = 24.7, p' <  0.002), and greater SW-spindle coupling angle distribution non-uniformity (strength) (F = 7.30, p' = 0.034).

CONCLUSION

This study comprehensively evaluates sleep qEEG including SW-spindle phase amplitude coupling in PD compared to non-PD controls. These findings provide novel insights into how neurodegenerative disease disrupts electrophysiological sleep rhythms. Considering the role of sleep oscillatory activity on neural plasticity, future studies should investigate the influence of these qEEG markers on cognition in PD.

The sleep and wake electroencephalogram over the lifespan

Both sleep and wake encephalograms (EEG) change over the lifespan. While prior studies have characterized age-related changes in the EEG, the datasets span a particular age group, or focused on sleep and wake macrostructure rather than the microstructure. Here, we present sex-stratified data from 3372 community-based or clinic-based otherwise neurologically and psychiatrically healthy participants ranging from 11 days to 80 years of age. We estimate age norms for key sleep and wake EEG parameters including absolute and relative powers in delta, theta, alpha, and sigma bands, as well as sleep spindle density, amplitude, duration, and frequency. To illustrate the potential use of the reference measures developed herein, we compare them to sleep EEG recordings from age-matched participants with Alzheimer's disease, severe sleep apnea, depression, osteoarthritis, and osteoporosis. Although the partially clinical nature of the datasets may bias the findings towards less normal and hence may underestimate pathology in practice, age-based EEG reference values enable objective screening of deviations from healthy aging among individuals with a variety of disorders that affect brain health.

Dementia detection from brain activity during sleep

STUDY OBJECTIVES

Dementia is a growing cause of disability and loss of independence in the elderly, yet remains largely underdiagnosed. Early detection and classification of dementia can help close this diagnostic gap and improve management of disease progression. Altered oscillations in brain activity during sleep are an early feature of neurodegenerative diseases and be used to identify those on the verge of cognitive decline.

METHODS

Our observational cross-sectional study used a clinical dataset of 10 784 polysomnography from 8044 participants. Sleep macro- and micro-structural features were extracted from the electroencephalogram (EEG). Microstructural features were engineered from spectral band powers, EEG coherence, spindle, and slow oscillations. Participants were classified as dementia (DEM), mild cognitive impairment (MCI), or cognitively normal (CN) based on clinical diagnosis, Montreal Cognitive Assessment, Mini-Mental State Exam scores, clinical dementia rating, and prescribed medications. We trained logistic regression, support vector machine, and random forest models to classify patients into DEM, MCI, and CN groups.

RESULTS

For discriminating DEM versus CN, the best model achieved an area under receiver operating characteristic curve (AUROC) of 0.78 and area under precision-recall curve (AUPRC) of 0.22. For discriminating MCI versus CN, the best model achieved an AUROC of 0.73 and AUPRC of 0.18. For discriminating DEM or MCI versus CN, the best model achieved an AUROC of 0.76 and AUPRC of 0.32.

CONCLUSIONS

Our dementia classification algorithms show promise for incorporating dementia screening techniques using routine sleep EEG. The findings strengthen the concept of sleep as a window into neurodegenerative diseases.

To sleep or not to sleep - Effects on memory in normal aging and disease

Sleep behavior undergoes significant changes across the lifespan, and aging is associated with marked alterations in sleep amounts and quality. The primary sleep changes in healthy older adults include a shift in sleep timing, reduced slow-wave sleep, and impaired sleep maintenance. However, neurodegenerative and psychiatric disorders are more common among the elderly, which further worsen their sleep health. Irrespective of the cause, insufficient sleep adversely affects various bodily functions including energy metabolism, mood, and cognition. In this review, we will focus on the cognitive changes associated with inadequate sleep during normal aging and the underlying neural mechanisms.

Sleep Spindle Characteristics and Relationship with Memory Ability in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome

Obstructive sleep apnea syndrome (OSAS) causes intermittent hypoxia and sleep disruption in the brain, resulting in cognitive dysfunction, but its pathogenesis is unclear. The sleep spindle wave is a transient neural event involved in sleep memory consolidation and synaptic plasticity. This study aimed to investigate the characteristics of sleep spindle activity and its relationship with memory ability in patients with OSAS. A total of 119 patients, who were divided into the OSAS group (n = 59, AHI ≥ 15) and control group (n = 60, AHI < 15) according to the Apnea Hypopnea Index (AHI), were enrolled and underwent polysomnography. Power spectral density (PSD) and omega complexity were used to analyze the characteristics of single and different brain regions of sleep spindles. Memory-related cognitive functions were assessed in all subjects, including logical memory, digit ordering, pattern recognition, spatial recognition and spatial working memory. The spindle PSD of the OSAS group was significantly slower than the control group, regardless of the slow, fast, or total spindle. The complexity of the spindles in the prefrontal and central region decreased significantly, whereas it increased in the occipital region. Sleep spindle PSD was positively correlated with logical memory and working memory. Spindle complexity was positively correlated with immediate logical and visual memory in the prefrontal region and positively correlated with immediate/delayed logical and working memory in the central region. In contrast, spindle complexity in the occipital region negatively correlated with delayed logical memory. Spindle hyperconnectivity in the prefrontal and central regions underlies declines in logical, visual and working memory and weak connections in the occipital spindles underlie the decline in delayed logical memory.

Dissociation of Arousal Index Between REM and NREM Sleep in Elderly Adults with Cognitive Impairment, No Dementia: A Pilot Study

BACKGROUND

Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer's disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND).

OBJECTIVE

Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages.

METHODS

Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with -2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neuropsi total score (NTS).

RESULTS

AI (REM)  was significantly higher in CU group than in CIND group. For the total sample, a positive correlation between AI (REM)  and NTS was found (r = 0.68, p = 0.006), which remained significant when controlling for the effect of age and education. In CIND group, the AI (N2)  was significantly higher than the AI (REM) .

CONCLUSION

In CIND older adults, this attenuation of normal arousal mechanisms in REM sleep are dissociated from the relative excess of arousals observed in stage N2. We propose as probable etiology an early hypoactivity at the locus coeruleus noradrenergic system, associated to its early pathological damage, present in the AD continuum.

Assessment of Cognitive Function with Sleep Spindle Characteristics in Adults with Epilepsy

Objective

Epilepsy may cause chronic cognitive impairment by disturbing sleep plasticity. Sleep spindles play a crucial role in sleep maintenance and brain plasticity. This study explored the relationship between cognition and spindle characteristics in adult epilepsy.

Methods

Participants underwent one-night sleep electroencephalogram recording and neuropsychological tests on the same day. Spindle characteristics during N2 sleep were extracted using a learning-based system for sleep staging and an automated spindle detection algorithm. We investigated the difference between cognitive subgroups in spindle characteristics. Multiple linear regressions were applied to analyze associations between cognition and spindle characteristics.

Results

Compared with no/mild cognitive impairment, epilepsy patients who developed severe cognitive impairment had lower sleep spindle density, the differences mainly distributed in central, occipital, parietal, middle temporal, and posterior temporal (P < 0.05), and had relatively long spindle duration in occipital and posterior temporal (P < 0.05). Mini-Mental State Examination (MMSE) was associated with spindle density (pars triangularis of the inferior frontal gyrus (IFGtri): β = 0.253, P = 0.015, and P.adjust = 0.074) and spindle duration (IFGtri: β = -0.262, P = 0.004, and P.adjust = 0.030). Montreal Cognitive Assessment (MoCA) was associated with spindle duration (IFGtri: β = -0.246, P = 0.010, and P.adjust = 0.055). Executive Index Score (MoCA-EIS) was associated with spindle density (IFGtri: β = 0.238, P = 0.019, and P.adjust = 0.087; parietal: β = 0.227, P = 0.017, and P.adjust = 0.082) and spindle duration (parietal: β = -0.230, P = 0.013, and P.adjust = 0.065). Attention Index Score (MoCA-AIS) was associated with spindle duration (IFGtri: β = -0.233, P = 0.017, and P.adjust = 0.081).

Conclusions

The findings suggested that the altered spindle activity in epilepsy with severe cognitive impairment, the associations between the global cognitive status of adult epilepsy and spindle characteristics, and specific cognitive domains may relate to spindle characteristics in particular brain regions.

New Metrics from Polysomnography: Precision Medicine for OSA Interventions

Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.

Inflammation, tau pathology, and synaptic integrity associated with sleep spindles and memory prior to β-amyloid positivity

STUDY OBJECTIVES

Fast frequency sleep spindles are reduced in aging and Alzheimer's disease (AD), but the mechanisms and functional relevance of these deficits remain unclear. The study objective was to identify AD biomarkers associated with fast sleep spindle deficits in cognitively unimpaired older adults at risk for AD.

METHODS

Fifty-eight cognitively unimpaired, β-amyloid-negative, older adults (mean ± SD; 61.4 ± 6.3 years, 38 female) enriched with parental history of AD (77.6%) and apolipoprotein E (APOE) ε4 positivity (25.9%) completed the study. Cerebrospinal fluid (CSF) biomarkers of central nervous system inflammation, β-amyloid and tau proteins, and neurodegeneration were combined with polysomnography (PSG) using high-density electroencephalography and assessment of overnight memory retention. Parallelized serial mediation models were used to assess indirect effects of age on fast frequency (13 to <16Hz) sleep spindle measures through these AD biomarkers.

RESULTS

Glial activation was associated with prefrontal fast frequency sleep spindle expression deficits. While adjusting for sex, APOE ε4 genotype, apnea-hypopnea index, and time between CSF sampling and sleep study, serial mediation models detected indirect effects of age on fast sleep spindle expression through microglial activation markers and then tau phosphorylation and synaptic degeneration markers. Sleep spindle expression at these electrodes was also associated with overnight memory retention in multiple regression models adjusting for covariates.

CONCLUSIONS

These findings point toward microglia dysfunction as associated with tau phosphorylation, synaptic loss, sleep spindle deficits, and memory impairment even prior to β-amyloid positivity, thus offering a promising candidate therapeutic target to arrest cognitive decline associated with aging and AD.

Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus

Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.

Sleep Quality and Aging: A Systematic Review on Healthy Older People, Mild Cognitive Impairment and Alzheimer’s Disease

Aging is characterized by changes in the structure and quality of sleep. When the alterations in sleep become substantial, they can generate or accelerate cognitive decline, even in the absence of overt pathology. In fact, impaired sleep represents one of the earliest symptoms of Alzheimer’s disease (AD). This systematic review aimed to analyze the studies on sleep quality in aging, also considering mild cognitive impairment (MCI) and AD. The review process was conducted according to the PRISMA statement. A total of 71 studies were included, and the whole sample had a mean age that ranged from 58.3 to 93.7 years (62.8–93.7 healthy participants and 61.8–86.7 pathological populations). Of these selected studies, 33 adopt subjective measurements, 31 adopt objective measures, and 10 studies used both. Pathological aging showed a worse impoverishment of sleep than older adults, in both subjective and objective measurements. The most common aspect compromised in AD and MCI were REM sleep, sleep efficiency, sleep latency, and sleep duration. These results underline that sleep alterations are associated with cognitive impairment. In conclusion, the frequency and severity of sleep disturbance appear to follow the evolution of cognitive impairment. The overall results of objective measures seem more consistent than those highlighted by subjective measurements.

Association Between Sleep Microstructure and Incident Hypertension in a Population‐Based Sample: The HypnoLaus Study

Background

Poor sleep quality is associated with increased incident hypertension. However, few studies have investigated the impact of objective sleep structure parameters on hypertension. This study investigated the association between sleep macrostructural and microstructural parameters and incident hypertension in a middle‐ to older‐aged sample.

Methods and Results

Participants from the HypnoLaus population‐based cohort without hypertension at baseline were included. Participants had at‐home polysomnography at baseline, allowing assessment of sleep macrostructure (nonrapid eye movement sleep stages 1, 2, and 3; rapid eye movement sleep stages; and total sleep time) and microstructure including power spectral density of electroencephalogram in nonrapid eye movement sleep and spindles characteristics (density, duration, frequency, amplitude) in nonrapid eye movement sleep stage 2. Associations between sleep macrostructure and microstructure parameters at baseline and incident clinical hypertension over a mean follow‐up of 5.2 years were assessed with multiple‐adjusted logistic regression. A total of 1172 participants (42% men; age 55±10 years) were included. Of these, 198 (17%) developed hypertension. After adjustment for confounders, no sleep macrostructure features were associated with incident hypertension. However, low absolute delta and sigma power were significantly associated with incident hypertension where participants in the lowest quartile of delta and sigma had a 1.69‐fold (95% CI, 1.00–2.89) and 1.72‐fold (95% CI, 1.05–2.82) increased risk of incident hypertension, respectively, versus those in the highest quartile. Lower spindle density (odds ratio, 0.87; 95% CI, 0.76–0.99) and amplitude (odds ratio, 0.98; 95% CI, 0.95–1.00) were also associated with higher incident hypertension.

Conclusions

Sleep microstructure is associated with incident hypertension. Slow‐wave activity and sleep spindles, 2 hallmarks of objective sleep continuity and quality, were inversely and consistently associated with incident hypertension. This supports the protective role of sleep continuity in the development of hypertension.

Focal epilepsy disrupts spindle structure and function

Sleep spindles are the hallmark of N2 sleep and are attributed a key role in cognition. Little is known about the impact of epilepsy on sleep oscillations underlying sleep-related functions. This study assessed changes in the global spindle rate in patients with epilepsy, analysed the distribution of spindles in relation to the epileptic focus, and performed correlations with neurocognitive function. Twenty-one patients with drug-resistant focal epilepsy (12 females; mean age 32.6 ± 10.7 years [mean ± SD]) and 12 healthy controls (3 females; 24.5 ± 3.3 years) underwent combined whole-night high-density electroencephalography and polysomnography. Global spindle rates during N2 were lower in epilepsy patients compared to controls (mean = 5.78/min ± 0.72 vs. 6.49/min ± 0.71, p = 0.02, d =  − 0.70). Within epilepsy patients, spindle rates were lower in the region of the epileptic focus compared to the contralateral region (median = 4.77/min [range 2.53–6.18] vs. 5.26/min [2.53–6.56], p = 0.02, rank biserial correlation RC =  − 0.57). This decrease was driven by fast spindles (12–16 Hz) (1.50/min [0.62–4.08] vs. 1.65/min [0.51–4.28], p = 0.002, RC =  − 0.76). The focal reduction in spindles was negatively correlated with two scales of attention (r =  − 0.54, p = 0.01; r =  − 0.51, p = 0.025). Patients with focal epilepsy show a reduction in global and local spindle rates dependent on the region of the epileptic focus. This may play a role in impaired cognitive functioning. Future work will show if the local reduction in spindles can be used as potential marker of the epileptic focus.

Sleep spindles changes in people with previous COVID-19 infection

Stage 2 sleep spindles are considered useful biomarkers for the integrity of the central nervous system and for cognitive and memory skills. We investigated sleep spindles patterns in subjects after 12 months of their hospitalization in the intensive care unit (ICU) of the Padova Teaching Hospital due to COVID-19 between March and November 2020. Before the nap, participants (13 hospitalized in ICU - ICU; 9 hospitalized who received noninvasive ventilation - nonlCU; 9 age and sex-matched healthy controls - CTRL, i.e., not infected by COVID-19) underwent a cognitive and psychological as-sessment. During the nap, high-density electroencephalography (EEG) recordings were acquired. Slow (i.e., [9]-[12] Hz) and fast (i.e.,]12-16] Hz) spindles were automatically detected. Spindle density and spindle source reconstruction in brain grey matter were extracted. The psychological assessment revealed a statistical difference comparing CTRL and nonlCU in Beck Depression Inventory score and in the Physical Quality of Life index (p_value = 0.03). The cognitive assessment revealed a trend of worsening results in executive functions in COVID-19 survivors. Slow spindle density significantly decreased comparing CTRL to COVID-19 survivors (p_value= 0.001). There were statistically significant differences in EEG source-waveforms fast spindle amplitude onset among the three groups, mainly between CTRL and nonlCU. Clinical Relevance- Our results suggest that nonlCU were more susceptible to the hospitalization experience than ICU participants with a slight effect on cognitive tests. This impacted the spindle generation revealing a decreased density of slow spindles and affecting the generators of fast spindles in COVID-19 survivors especially in nonlCU.

Sleep Biomarkers Help Predict the Development of Alzheimer Disease

SUMMARY

Middle-aged or older adults who self-report sleep-wake disorders are at an increased risk for incident dementia, mild cognitive impairment, and Alzheimer disease. Dementia in people with mild cognitive impairment and Alzheimer disease who complain of sleep-wake disorders progress faster than those without sleep-wake disorders. Removal of amyloid-beta and tau tangles occurs preferentially in non-rapid eye movement 3 sleep and fragmented or insufficient sleep may lead to accumulation of these neurotoxins even in preclinical stages. Selective atrophy in the medial temporal lobe on brain MRI has been shown to predict impaired coupling of slow oscillations and sleep spindles. Impaired slow wave-spindle coupling has been shown to correlate with impaired overnight memory consolidation. Whereas, a decrease in the amplitude of 0.6 to 1 Hz slow wave activity predicts higher cortical Aβ burden on amyloid PET scans. Overexpression of the wake-promoting neurotransmitter orexin may predispose patients with mild cognitive impairment and Alzheimer disease to increased wakefulness, decreasing time they need to clear from the brain the neurotoxic accumulation of amyloid-beta and especially tau. More research exploring these relationships is needed and continuing.

Sleep Deficiency in the Elderly

With aging, there are normative changes to sleep physiology and circadian rhythmicity that may predispose older adults to sleep deficiency, whereas many health-related and psychosocial/behavioral factors may precipitate sleep deficiency. In this article, we describe age-related changes to sleep and describe how the health-related and psychosocial/behavioral factors typical of aging may converge in older adults to increase the risk for sleep deficiency. Next, we review the consequences of sleep deficiency in older adults, focusing specifically on important age-related outcomes, including mortality, cognition, depression, and physical function. Finally, we review treatments for sleep deficiency, highlighting safe and effective nonpharmacologic interventions.

Sleep EEG-Based Approach to Detect Mild Cognitive Impairment

Mild Cognitive Impairment (MCI) is an early stage of dementia, which may lead to Alzheimer's disease (AD) in older adults. Therefore, early detection of MCI and implementation of treatment and intervention can effectively slow down or even inhibit the progression of the disease, thus minimizing the risk of AD. Currently, we know that published work relies on an analysis of awake EEG recordings. However, recent studies have suggested that changes in the structure of sleep may lead to cognitive decline. In this work, we propose a sleep EEG-based method for MCI detection, extracting specific features of sleep to characterize neuroregulatory deficit emergent with MCI. This study analyzed the EEGs of 40 subjects (20 MCI, 20 HC) with the developed algorithm. We extracted sleep slow waves and spindles features, combined with spectral and complexity features from sleep EEG, and used the SVM classifier and GRU network to identify MCI. In addition, the classification results of different feature sets (including with sleep features from sleep EEG and without sleep features from awake EEG) and different classification methods were evaluated. Finally, the MCI classification accuracy of the GRU network based on features extracted from sleep EEG was the highest, reaching 93.46%. Experimental results show that compared with the awake EEG, sleep EEG can provide more useful information to distinguish between MCI and HC. This method can not only improve the classification performance but also facilitate the early intervention of AD.

Barbeau E, Pariente J, Dahan L, Valton L. Sleep: The Tip of the Iceberg in the Bidirectional Link Between Alzheimer's Disease and Epilepsy

The observation that a pathophysiological link might exist between Alzheimer's disease (AD) and epilepsy dates back to the identification of the first cases of the pathology itself and is now strongly supported by an ever-increasing mountain of literature. An overwhelming majority of data suggests not only a higher prevalence of epilepsy in Alzheimer's disease compared to healthy aging, but also that AD patients with a comorbid epileptic syndrome, even subclinical, have a steeper cognitive decline. Moreover, clinical and preclinical investigations have revealed a marked sleep-related increase in the frequency of epileptic activities. This characteristic might provide clues to the pathophysiological pathways underlying this comorbidity. Furthermore, the preferential sleep-related occurrence of epileptic events opens up the possibility that they might hasten cognitive decline by interfering with the delicately orchestrated synchrony of oscillatory activities implicated in sleep-related memory consolidation. Therefore, we scrutinized the literature for mechanisms that might promote sleep-related epileptic activity in AD and, possibly dementia onset in epilepsy, and we also aimed to determine to what degree and through which processes such events might alter the progression of AD. Finally, we discuss the implications for patient care and try to identify a common basis for methodological considerations for future research and clinical practice.

Optimal spindle detection parameters for predicting cognitive performance

STUDY OBJECTIVES

Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition.

METHODS

Adult patients (n = 167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores.

RESULTS

Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r = 0.503) and age-adjusted fluid cognition scores (r = 0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings.

CONCLUSIONS

Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

Role of melatonin in Alzheimer's disease: From preclinical studies to novel melatonin-based therapies

Melatonin and novel melatonin-based therapies such as melatonin-containing hybrid molecules, melatonin analogues, and melatonin derivatives have been investigated as potential therapeutics against Alzheimer's disease (AD) pathogenesis. In this review, we examine the developmental trends of melatonin therapies for AD from 1997 to 2021. We then highlight the neuroprotective mechanisms of melatonin therapy derived from preclinical studies. These mechanisms include the alleviation of amyloid-related burden, neurofibrillary tangle accumulation, oxidative stress, neuroinflammation, apoptosis, mitochondrial dysfunction, and impaired neuroplasticity and neurotransmission. We further illustrate the beneficial effects of melatonin on behavior in animal models of AD. Next, we discuss the clinical effects of melatonin on sleep, cognition, behavior, psychiatric symptoms, electroencephalography findings, and molecular biomarkers in patients with mild cognitive impairment and AD. We then explore the effectiveness of novel melatonin-based therapies. Lastly, we discuss the limitations of current melatonin therapies for AD and suggest two emerging research themes for future study.

Sleep in Alzheimer's disease: a systematic review and meta-analysis of polysomnographic findings

Polysomnography (PSG) studies of sleep changes in Alzheimer's disease (AD) have reported but not fully established the relationship between sleep disturbances and AD. To better detail this relationship, we conducted a systematic review and meta-analysis of reported PSG differences between AD patients and healthy controls. An electronic literature search was conducted in EMBASE, MEDLINE, All EBM databases, CINAHL, and PsycINFO inception to Mar 2021. Twenty-eight studies were identified for systematic review, 24 of which were used for meta-analysis. Meta-analyses revealed significant reductions in total sleep time, sleep efficiency, and percentage of slow-wave sleep (SWS) and rapid eye movement (REM) sleep, and increases in sleep latency, wake time after sleep onset, number of awakenings, and REM latency in AD compared to controls. Importantly, both decreased SWS and REM were significantly associated with the severity of cognitive impairment in AD patients. Alterations in electroencephalogram (EEG) frequency components and sleep spindles were also observed in AD, although the supporting evidence for these changes was limited. Sleep in AD is compromised with increased measures of wake and decreased TST, SWS, and REM sleep relative to controls. AD-related reductions in SWS and REM sleep correlate with the degree of cognitive impairment. Alterations in sleep EEG frequency components such as sleep spindles may be possible biomarkers with relevance for diagnosing AD although their sensitivity and specificity remain to be clearly delineated. AD-related sleep changes are potential targets for early therapeutic intervention aimed at improving sleep and slowing cognitive decline.

Toward noninvasive brain stimulation 2.0 in Alzheimer's disease

Noninvasive brain stimulation techniques (NiBS) have gathered substantial interest in the study of dementia, considered their possible role in help defining diagnostic biomarkers of altered neural activity for early disease detection and monitoring of its pathophysiological course, as well as for their therapeutic potential of boosting residual cognitive functions. Nevertheless, current approaches suffer from some limitations. In this study, we review and discuss experimental NiBS applications that might help improve the efficacy of future NiBS uses in Alzheimer's Disease (AD), including perturbation-based biomarkers for early diagnosis and disease tracking, solutions to enhance synchronization of oscillatory electroencephalographic activity across brain networks, enhancement of sleep-related memory consolidation, image-guided stimulation for connectome control, protocols targeting interneuron pathology and protein clearance, and finally hybrid-brain models for in-silico modeling of AD pathology and personalized target selection. The present work aims to stress the importance of multidisciplinary, translational, model-driven interventions for precision medicine approaches in AD.

The association between sleep microarchitecture and cognitive function in middle-aged and older men: a community-based cohort study

STUDY OBJECTIVES

Sleep microarchitecture parameters determined by quantitative power spectral analysis (PSA) of electroencephalograms (EEGs) have been proposed as potential brain-specific markers of cognitive dysfunction. However, data from community samples remains limited. This study examined cross-sectional associations between sleep microarchitecture and cognitive dysfunction in community-dwelling men.

METHODS

Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (PSG) (2010-2011). All-night EEG recordings were processed using PSA following artefact exclusion. Cognitive testing (2007-2010) included the inspection time task, trail-making tests A (TMT-A) and B (TMT-B), and Fuld object memory evaluation. Complete case cognition, PSG, and covariate data were available in 366 men. Multivariable linear regression models controlling for demographic, biomedical, and behavioral confounders determined cross-sectional associations between sleep microarchitecture and cognitive dysfunction overall and by age-stratified subgroups.

RESULTS

In the overall sample, worse TMT-A performance was associated with higher NREM theta and REM theta and alpha but lower delta power (all p<0.05). In men ≥65 years, worse TMT-A performance was associated with lower NREM delta but higher NREM and REM theta and alpha power (all p<0.05). Furthermore, in men ≥65 years, worse TMT-B performance was associated with lower REM delta but higher theta and alpha power (all p<0.05).

CONCLUSIONS

Sleep microarchitecture parameters may represent important brain-specific markers of cognitive dysfunction, particularly in older community-dwelling men. Therefore, this study extends the emerging community-based cohort literature on a potentially important link between sleep microarchitecture and cognitive dysfunction. Utility of sleep microarchitecture for predicting prospective cognitive dysfunction and decline warrants further investigation.

Generalized EEG Slowing Across Phasic REM Sleep, Not Subjective RBD Severity, Predicts Neurodegeneration in Idiopathic RBD

PURPOSE

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is the prodromal marker of α-synuclein degeneration with markedly high predictive value. We aim to evaluate the value of electroencephalography (EEG) data during rapid eye movement (REM) sleep and subjective RBD severity in predicting the conversion to neurodegenerative diseases in iRBD patients.

METHODS

At the baseline, iRBD patients underwent clinical assessment and video-polysomnography (PSG). Relative spectral power for nine frequency bands during phasic and tonic REM sleep in three regions of interest, slow-to-fast ratios, clinical and PSG variables were estimated and compared between iRBD patients who converted to neurodegenerative diseases (iRBD-C) and iRBD patients who remained disease-free (iRBD-NC). Receiver operating characteristic (ROC) curves evaluated the predictive performance of slow-to-fast ratios, and subjective RBD severity as assessed with RBD Questionnaire-Hong Kong.

RESULTS

Twenty-two (33.8%) patients eventually developed neurodegenerative diseases. The iRBD-C group showed shorter total sleep time (p < 0.001), lower stage 2 sleep percentage (p = 0.044), more periodic leg-movement-related arousal index (p = 0.004), increased tonic chin electromyelographic activity (p = 0.040) and higher REM density in the third REM episode (p = 0.034) than the iRBD-NC group. EEG spectral power analyses revealed that iRBD phenoconverters showed significantly higher delta and lower alpha power, especially in central and occipital regions during the phasic REM state compared to the iRBD-NC group. Significantly higher slow-to-fast ratios were observed in a more generalized way during the phasic state in the iRBD-C group compared to the iRBD-NC group. ROC analyses of the slowing ratio in occipital areas during phasic REM sleep yielded an area under the curve of 0.749 (p = 0.001), while no significant predictive value of subjective RBD severity was observed.

CONCLUSION

Our study shows that EEG slowing, especially in a more generalized manner during the phasic period, may be a promising marker in predicting phenoconversion in iRBD, rather than subjective RBD severity.

Covering the Gap Between Sleep and Cognition – Mechanisms and Clinical Examples

A growing number of studies have shown the strong relationship between sleep and different cognitive processes, especially those that involve memory consolidation. Traditionally, these processes were attributed to mechanisms related to the macroarchitecture of sleep, as sleep cycles or the duration of specific stages, such as the REM stage. More recently, the relationship between different cognitive traits and specific waves (sleep spindles or slow oscillations) has been studied. We here present the most important physiological processes induced by sleep, with particular focus on brain electrophysiology. In addition, recent and classical literature were reviewed to cover the gap between sleep and cognition, while illustrating this relationship by means of clinical examples. Finally, we propose that future studies may focus not only on analyzing specific waves, but also on the relationship between their characteristics as potential biomarkers for multiple diseases.

The association between obstructive sleep apnea and sleep spindles in middle-aged and older men: A community-based cohort study

STUDY OBJECTIVES

Sleep spindles show morphological changes in obstructive sleep apnea (OSA). However, previous small studies have limited generalisability, leaving associations between OSA severity measures and spindle metrics uncertain. This study examined cross-sectional associations between OSA severity measures and spindle metrics among a large population-based sample of men.

METHODS

Community-dwelling men with no previous OSA diagnosis underwent home-based polysomnography. All-night EEG (F4-M1) recordings were processed for artefacts and spindle events identified using previously validated algorithms. Spindle metrics of interest included frequency (Hz), amplitude (µV 2), overall density (11-16 Hz), slow density (11-13 Hz), and fast density (13-16 Hz) (number/minute). Multivariable linear regression models controlling for demographic, biomedical, and behavioural confounders were used to examine cross-sectional associations between OSA severity measures and spindle metrics.

RESULTS

In adjusted analyses, higher apnea-hypopnea index (AHI/h, as a continuous variable) and percentage total sleep time with oxygen saturation <90% (TST90) were associated with decreased slow spindle density (AHI, B= -0.003, p=0.032; TST90, B= -0.004, p=0.047) but increased frequency (AHI, B=0.002, p=0.009; TST90, B=0.002, p=0.043). Higher TST90 was also associated with greater spindle amplitude (N2 sleep, B=0.04, p=0.011; N3 sleep, B=0.11, p<0.001). Furthermore, higher arousal index was associated with greater spindle amplitude during N2 sleep (B=0.31, p<0.001) but decreased overall density (B= -1.27, p=0.030) and fast density (B= -4.36, p=0.028) during N3 sleep.

CONCLUSIONS

Among this large population-based sample of men, OSA severity measures were independently associated with spindle abnormalities. Further population studies are needed to determine associations between spindle metrics and functional outcomes.

How non-rapid eye movement sleep and Alzheimer pathology are linked

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by the presence of senile plaques and neurofibrillary tangles. Research attempts to identify characteristic factors that are associated with the presence of the AD pathology on the one hand and that increase the risk of developing AD on the other. Changes in non-rapid eye movement (NREM) sleep may meet both requirements for various reasons. First, NREM-sleep is important for optimal memory function. In addition, studies report that the presence of AD pathology is associated with NREM-sleep changes. Finally, more and more results appear to suggest that sleep problems are not only a symptom of AD but can also increase the risk of AD. Several of these studies suggest that it is primarily a lack of NREM-sleep that is responsible for this increased risk. However, the majority investigated sleep only through subjective reporting, as a result of which NREM-sleep could not be analyzed separately. The aim of this literature study is therefore to present the results of the studies that relate the AD pathology and NREM-sleep (registered by electroencephalography). Furthermore, we try to evaluate whether NREM-sleep analysis could be used to support the diagnosis of AD and whether NREM-sleep deficiency could be a causal factor in the development of AD.

Restoring activity in the thalamic reticular nucleus improves sleep architecture and reduces Aβ accumulation in mice

Sleep disruptions promote increases of amyloid β (Aβ) and tau in the brain and increase Alzheimer’s disease (AD) risk, but the precise mechanisms that give rise to sleep disturbances have yet to be defined. The thalamic reticular nucleus (TRN) is essential for sleep maintenance and for the regulation of slow-wave sleep (SWS). We examined the TRN in transgenic mice that express mutant human amyloid precursor protein (APP) and found reduced neuronal activity, increased sleep fragmentation, and decreased SWS time as compared to nontransgenic littermates. Selective activation of the TRN using excitatory DREADDs restored sleep maintenance, increased time in SWS, and reduced amyloid plaque load in both hippocampus and cortex. Our findings suggest that the TRN may play a major role in symptoms associated with AD. Enhancing TRN activity might be a promising therapeutic strategy for AD.

New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences

Current approaches to quantify and diagnose sleep disorders and circadian rhythm disruption are imprecise, laborious, and often do not relate well to key clinical and health outcomes. Newer emerging approaches that aim to overcome the practical and technical constraints of current sleep metrics have considerable potential to better explain sleep disorder pathophysiology and thus to more precisely align diagnostic, treatment and management approaches to underlying pathology. These include more fine-grained and continuous EEG signal feature detection and novel oxygenation metrics to better encapsulate hypoxia duration, frequency, and magnitude readily possible via more advanced data acquisition and scoring algorithm approaches. Recent technological advances may also soon facilitate simple assessment of circadian rhythm physiology at home to enable sleep disorder diagnostics even for “non-circadian rhythm” sleep disorders, such as chronic insomnia and sleep apnea, which in many cases also include a circadian disruption component. Bringing these novel approaches into the clinic and the home settings should be a priority for the field. Modern sleep tracking technology can also further facilitate the transition of sleep diagnostics from the laboratory to the home, where environmental factors such as noise and light could usefully inform clinical decision-making. The “endpoint” of these new and emerging assessments will be better targeted therapies that directly address underlying sleep disorder pathophysiology via an individualized, precision medicine approach. This review outlines the current state-of-the-art in sleep and circadian monitoring and diagnostics and covers several new and emerging approaches to better define sleep disruption and its consequences.

The Regional EEG Pattern of the Sleep Onset Process in Older Adults

Healthy aging is characterized by macrostructural sleep changes and alterations of regional electroencephalographic (EEG) sleep features. However, the spatiotemporal EEG pattern of the wake-sleep transition has never been described in the elderly. The present study aimed to assess the topographical and temporal features of the EEG during the sleep onset (SO) in a group of 36 older participants (59–81 years). The topography of the 1 Hz bins’ EEG power and the time course of the EEG frequency bands were assessed. Moreover, we compared the delta activity and delta/beta ratio between the older participants and a group of young adults. The results point to several peculiarities in the elderly: (a) the generalized post-SO power increase in the slowest frequencies did not include the 7 Hz bin; (b) the alpha power revealed a frequency-specific pattern of post-SO modifications; (c) the sigma activity exhibited only a slight post-SO increase, and its highest bins showed a frontotemporal power decrease. Older adults showed a generalized reduction of delta power and delta/beta ratio in both pre- and post-SO intervals compared to young adults. From a clinical standpoint, the regional EEG activity may represent a target for brain stimulation techniques to reduce SO latency and sleep fragmentation.