Absence of Relationship Between Self-Reported Sleep Measures and Amyloid Load in Elderly Subjects

How Do Modifiable Risk Factors Affect Alzheimer's Disease Pathology or Mitigate Its Effect on Clinical Symptom Expression?

Epidemiological studies show that modifiable risk factors account for approximately 40% of the population variability in risk of developing dementia, including sporadic Alzheimer's disease (AD). Recent findings suggest that these factors may also modify disease trajectories of people with autosomal-dominant AD. With positron emission tomography imaging, it is now possible to study the disease many years before its clinical onset. Such studies can provide key knowledge regarding pathways for either the prevention of pathology or the postponement of its clinical expression. The former "resistance pathway" suggests that modifiable risk factors could affect amyloid and tau burden decades before the appearance of cognitive impairment. Alternatively, the resilience pathway suggests that modifiable risk factors may mitigate the symptomatic expression of AD pathology on cognition. These pathways are not mutually exclusive and may appear at different disease stages. Here, in a narrative review, we present neuroimaging evidence that supports both pathways in sporadic AD and autosomal-dominant AD. We then propose mechanisms for their protective effect. Among possible mechanisms, we examine neural and vascular mechanisms for the resistance pathway. We also describe brain maintenance and functional compensation as bases for the resilience pathway. Improved mechanistic understanding of both pathways may suggest new interventions.

Sleep duration, sleep efficiency, and amyloid β among cognitively healthy later-life adults: a systematic review and meta-analysis

BACKGROUND

Abnormal amyloid β (Aβ) deposits in the brain are a hallmark of Alzheimer's disease (AD). Insufficient sleep duration and poor sleep quality are risk factors for developing AD. Sleep may play a role in Aβ regulation, but the magnitude of the relationship between sleep and Aβ deposition remains unclear. This systematic review examines the relationship between sleep (i.e., duration and efficiency) with Aβ deposition in later-life adults.

METHODS

A search of PubMed, CINAHL, Embase, and PsycINFO generated 5,005 published articles. Fifteen studies met the inclusion criteria for qualitative syntheses; thirteen studies for quantitative syntheses related to sleep duration and Aβ; and nine studies for quantitative syntheses related to sleep efficiency and Aβ.

RESULTS

Mean ages of the samples ranged from 63 to 76 years. Studies measured Aβ using cerebrospinal fluid, serum, and positron emission tomography scans with two tracers: Carbone 11-labeled Pittsburgh compound B or fluorine 18-labeled. Sleep duration was measured subjectively using interviews or questionnaires, or objectively using polysomnography or actigraphy. Study analyses accounted for demographic and lifestyle factors. Based on 13 eligible articles, our synthesis demonstrated that the average association between sleep duration and Aβ was not statistically significant (Fisher's Z = -0.055, 95% CI = -0.117 ~ 0.008). We found that longer self-report sleep duration is associated with lower Aβ (Fisher's Z = -0.062, 95% CI = -0.119 ~ -0.005), whereas the objectively measured sleep duration was not associated with Aβ (Fisher's Z = 0.002, 95% CI = -0.108 ~ 0.113). Based on 9 eligible articles for sleep efficiency, our synthesis also demonstrated that the average association between sleep efficiency and Aβ was not statistically significant (Fisher's Z = 0.048, 95% CI = -0.066 ~ 0.161).

CONCLUSION

The findings from this review suggest that shorter self-reported sleep duration is associated with higher Aβ levels. Given the heterogeneous nature of the sleep measures and outcomes, it is still difficult to determine the exact relationship between sleep and Aβ. Future studies with larger sample sizes should focus on comprehensive sleep characteristics and use longitudinal designs to better understand the relationship between sleep and AD.

Multimodal neuroimaging correlates of spectral power in NREM sleep delta sub-bands in cognitively unimpaired older adults

STUDY OBJECTIVES

In aging, reduced delta power (0.5-4 Hz) during N2 and N3 sleep has been associated with gray matter (GM) atrophy and hypometabolism within frontal regions. Some studies have also reported associations between N2 and N3 sleep delta power in specific sub-bands and amyloid pathology. Our objective was to better understand the relationships between spectral power in delta sub-bands during N2-N3 sleep and brain integrity using multimodal neuroimaging.

METHODS

In-home polysomnography was performed in 127 cognitively unimpaired older adults (mean age ± SD: 69.0 ± 3.8 years). N2-N3 sleep EEG power was calculated in delta (0.5-4 Hz), slow delta (0.5-1 Hz), and fast delta (1-4 Hz) frequency bands. Participants also underwent magnetic resonance imaging and Florbetapir-PET (early and late acquisitions) scans to assess GM volume, brain perfusion, and amyloid burden. Amyloid accumulation over ~21 months was also quantified.

RESULTS

Higher delta power was associated with higher GM volume mainly in fronto-cingular regions. Specifically, slow delta power was positively correlated with GM volume and perfusion in these regions, while the inverse association was observed with fast delta power. Delta power was neither associated with amyloid burden at baseline nor its accumulation over time, whatever the frequency band considered.

CONCLUSIONS

Our results show that slow delta is particularly associated with preserved brain structure, and highlight the importance of analyzing delta power sub-bands to better understand the associations between delta power and brain integrity. Further longitudinal investigations with long follow-ups are needed to disentangle the associations among sleep, amyloid pathology, and dementia risk in older populations.

CLINICAL TRIAL INFORMATION

Name: Study in Cognitively Intact Seniors Aiming to Assess the Effects of Meditation Training (Age-Well). URL: https://clinicaltrials.gov/ct2/show/NCT02977819?term=Age-Well&draw=2&rank=1. See STROBE_statement_AGEWELL in supplemental materials.

REGISTRATION

EudraCT: 2016-002441-36; IDRCB: 2016-A01767-44; ClinicalTrials.gov Identifier: NCT02977819.

Association of Sleep Duration and Change Over Time With Imaging Biomarkers of Cerebrovascular, Amyloid, Tau, and Neurodegenerative Pathology

BACKGROUND AND OBJECTIVES

Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration, and (V)ascular neuroimaging markers of Alzheimer disease.

METHODS

Two Framingham Heart Study overlapping samples were studied: participants who underwent 11C-Pittsburg Compound B amyloid and 18F-flortaucipir tau PET imaging and participants who underwent an MRI. MRI metrics estimated neurodegeneration (total brain volume) and cerebrovascular injuries (white matter hyperintensities [WMHs] volume, covert brain infarcts, free-water [FW] fraction). Self-reported sleep duration was assessed and split into categories both at the time of neuroimaging testing and approximately 13 years before: short ≤6 hours. average 7-8 hours, and long ≥9 hours. Logistic and linear regression models were used to examine sleep duration and neuroimaging metrics.

RESULTS

The tested cohort was composed of 271 participants (age 53.6 ± 8.0 years; 51% male) in the PET imaging sample and 2,165 participants (age 61.3 ± 11.1 years; 45% male) in the MRI sample. No fully adjusted association was observed between cross-sectional sleep duration and neuroimaging metrics. In fully adjusted models compared with consistently sleeping 7-8 hours, groups transitioning to a longer sleep duration category over time had higher FW fraction (short to average β [SE] 0.0062 [0.0024], p = 0.009; short to long β [SE] 0.0164 [0.0076], p = 0.031; average to long β [SE] 0.0083 [0.0022], p = 0.002), and those specifically going from average to long sleep duration also had higher WMH burden (β [SE] 0.29 [0.11], p = 0.007). The opposite associations (lower WMH and FW) were observed in participants consistently sleeping ≥9 hours as compared with people consistently sleeping 7-8 hours in fully adjusted models (β [SE] -0.43 [0.20], p = 0.028; β [SE] -0.019 [0.004], p = 0.020). Each hour of increasing sleep (continuous, β [SE] 0.12 [0.04], p = 0.003; β [SE] 0.002 [0.001], p = 0.021) and extensive increase in sleep duration (≥2 hours vs 0 ± 1 hour change; β [SE] 0.24 [0.10], p = 0.019; β [SE] 0.0081 [0.0025], p = 0.001) over time was associated with higher WMH burden and FW fraction in fully adjusted models. Sleep duration change was not associated with PET amyloid or tau outcomes.

DISCUSSION

Longer self-reported sleep duration over time was associated with neuroimaging biomarkers of cerebrovascular pathology as evidenced by higher WMH burden and FW fraction. A longer sleep duration extending over time may be an early change in the neurodegenerative trajectory.

Association of Sleep Disturbances With Brain Amyloid and Tau Burden, Cortical Atrophy, and Cognitive Dysfunction Across the AD Continuum

BACKGROUND AND OBJECTIVES

Patients with Alzheimer disease (AD) frequently suffer from various sleep disturbances. However, how sleep disturbance is associated with AD and its progression remains poorly investigated. We investigated the association of total sleep time with brain amyloid and tau burden, cortical atrophy, cognitive dysfunction, and their longitudinal changes in the AD spectrum.

METHODS

In this retrospective cohort study, we enrolled participants on the AD spectrum who were positive on 18F-florbetaben (FBB) PET. All participants underwent the Pittsburgh Sleep Quality Index, brain MRI, FBB PET, 18F-flortaucipir (FTP) PET, and detailed neuropsychological testing. In addition, a subset of participants completed follow-up assessments. We analyzed the association of total sleep time with the baseline and longitudinal FBB-standardized uptake value ratio (SUVR), FTP-SUVR, cortical thickness, and cognitive domain composite scores.

RESULTS

We examined 138 participants on the AD spectrum (15 with preclinical AD, 62 with prodromal AD, and 61 with AD dementia; mean age 73.4 ± 8.0 years; female 58.7%). Total sleep time was longer in the AD dementia group (7.4 ± 1.6 hours) compared with the preclinical (6.5 ± 1.4 hours; p = 0.026) and prodromal groups (6.6 ± 1.4 hours; p = 0.001), whereas other sleep parameters did not differ between groups. Longer total sleep time was not associated with amyloid accumulation but rather with tau accumulation, especially in the amygdala, hippocampus, basal forebrain, insular, cingulate, occipital, inferior temporal cortices, and precuneus. Longer total sleep time predicted faster tau accumulation in Braak regions V-VI (β = 0.016, p = 0.007) and disease progression to mild cognitive impairment or dementia (hazard ratio = 1.554, p = 0.024). Longer total sleep time was also associated with memory deficit (β = -0.19, p = 0.008).

DISCUSSION

Prolonged total sleep time was associated with tau accumulation in sleep-related cortical and subcortical areas as well as memory dysfunction. It also predicted faster disease progression with tau accumulation. Our study highlights the clinical importance of assessing total sleep time as a marker for disease severity and prognosis in the AD spectrum.

Associations between self-reported sleep patterns and health, cognition and amyloid measures: results from the Wisconsin Registry for Alzheimer's Prevention

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.

Relationship Between Physical Exercise and Cognitive Impairment Among Older Adults with Type 2 Diabetes: Chain Mediating Roles of Sleep Quality and Depression

Objective

Although physical exercise has been shown to boost physical, psychological, and psychiatric conditions in older adults, there is a relative lack of research on the mechanisms involved in this process for older adults with type 2 diabetes mellitus (T2DM). We thus evaluated whether sleep quality and depression mediated the relationship between physical exercise and cognitive impairment in older adults with T2DM by focusing on the exercise-physiology-psychology and psychiatry connection.

Methods

Self-reported data were collected from 2646 older adults with T2DM in Weifang, Shandong, China. Regression and bootstrap analyses were conducted to explore the chain mediator model including physical exercise, cognitive impairment, sleep quality, and depression.

Results

Engaging in physical exercise (coefficient = -0.6858, p < 0.001), high levels of sleep quality (coefficient = -0.3397, p = 0.015), and low levels of depression (coefficient = 0.3866, p < 0.001) were significantly associated with a low level of cognitive impairment. Sleep quality and depression mediated the chain effect between physical exercise and cognitive impairment (total effect = -1.0732, 95% CI [-1.3652, -0.7862]; direct effect = -0.6858, 95% CI [-0.9702, -0.3974]; indirect effect = -0.3875, 95% CI [-0.5369, -0.2521]).

Conclusion

Physical exercise may improve sleep quality in older adults with T2DM, alleviating depression and delaying the development of cognitive impairment. Physical exercise can enhance patients' ability to resist depression and cognitive impairment, and creating comfortable sleep environments can also reinforce the effects of this process. These findings have important implications for promoting healthy aging in older adults with T2DM.

The impact of sleep components, quality and patterns on glymphatic system functioning in healthy adults: A systematic review

OBJECTIVE

The glymphatic system is thought to be responsible for waste clearance in the brain. As it is primarily active during sleep, different components of sleep, subjective sleep quality, and sleep patterns may contribute to glymphatic functioning. This systematic review aimed at exploring the effect of sleep components, sleep quality, and sleep patterns on outcomes associated with the glymphatic system in healthy adults.

METHODS

PubMed®, Scopus, and Web of Science were searched for studies published in English until December 2021. Articles subjectively or objectively investigating sleep components (total sleep time, time in bed, sleep efficiency, sleep onset latency, wake-up after sleep onset, sleep stage, awakenings), sleep quality, or sleep pattern in healthy individuals, on outcomes associated with glymphatic system (levels of amyloid-β, tau, α-synuclein; cerebrospinal fluid, perivascular spaces; apolipoprotein E) were selected.

RESULTS

Out of 8359 records screened, 51 studies were included. Overall, contradictory findings were observed according to different sleep assessment method. The most frequently assessed sleep parameters were total sleep time, sleep quality, and sleep efficiency. No association was found between sleep efficiency and amyloid-β, and between slow-wave activity and tau. Most of the studies did not find any correlation between total sleep time and amyloid-β nor tau level. Opposing results correlated sleep quality with amyloid-β and tau.

CONCLUSIONS

This review highlighted inconsistent results across the studies; as such, the specific association between the glymphatic system and sleep parameters in healthy adults remains poorly understood. Due to the heterogeneity of sleep assessment methods and the self-reported data representing the majority of the observations, future studies with universal study design and sleep methodology in healthy individuals are advocated.

Complaints of daytime sleepiness, insomnia, hypnotic use, and risk of dementia: a prospective cohort study in the elderly

Background

Sleep disturbances are common in elderly and occur frequently in dementia. The impact of excessive daytime sleepiness (EDS), insomnia complaints, sleep quality, and hypnotics on the risk of all-cause dementia, Alzheimer disease (AD), and dementia with vascular component (DVC) remains unclear, as does the association between sleep profile and plasma β-amyloid levels.

Methods

Analyses were carried out on 6851 participants aged 65 years and over randomly recruited from three French cities and free of dementia at baseline. A structured interview and self-questionnaire assessed sleep complaints (EDS, insomnia complaints, sleep quality) and medications at baseline. Incident cases of dementia were diagnosed systematically over a 12-year period. Multivariate Cox models were used to estimate the risk of dementia associated with the sleep complaints considered individually and globally. Plasma β-amyloid levels were measured by an xMAP-based assay technology in 984 subjects.

Results

After adjustment for socio-demographic characteristics, lifestyle, APOE-ε4, cardiovascular factors, and depressive status, EDS had a higher risk of all-cause dementia (HR = 1.21; 95%CI = [1.01–1.46]) and DVC (HR = 1.58; 95%CI = [1.07–2.32]) but not AD. Persistent use of hypnotics increased the risk for all-cause dementia, specifically AD (HR = 1.28; 95%CI = [1.04–1.58]), but not DVC. No association was found for insomnia complaints and sleep quality taken as individual factors or combined with EDS on the risk of dementia. No association was found between β-amyloid, sleep complaints, and incident dementia.

Conclusions

The results suggest a deleterious role of EDS and hypnotics on dementia. Further studies are required to elucidate the mechanisms involved in these associations and whether its management can prevent the risk of dementia.

Associations Between Self-Reported Sleep Disturbances and Cognitive Impairment: A Population-Based Cross-Sectional Study

OBJECTIVE

Cognitive impairment is a rapidly growing global public health problem in China and worldwide. In the recent decades, emerging studies have explored the associations between sleep disturbances and cognitive impairment. However, the variety of the results imply us that further studies should be conducted for the associations.

METHODS

This is a cross-sectional study conducted between August and October 2018 in five cities in Hebei province, China. Subjects were 21,376 community residents. Cognitive impairment was screened by the Chinese version of the Mini-Mental State Examination (MMSE). Scales of Athens Insomnia Scale (AIS), Berlin Questionnaire (BQ), REM (rapid eye movement) Sleep Behavior Disorder Questionnaire (RBDQ-HK), Ullanlinna Narcolepsy Scale (CUNS), and Cambridge-Hopkins Restless Legs Syndrome Questionnaire (CH-RLSq) were used to access insomnia, sleep apnea, REM sleep behavior disorder, narcolepsy, and restless leg syndrome.

RESULTS

The mean ± SD (standard error) of MMSE, AIS, RBDQ-HK, and CUNS were 27.95 ± 4.79, 2.16 ± 3.39, 5.55 ± 7.75, and 3.76 ± 2.31, respectively. Among the participants, 10.6% and 1.5% of the participants were identified as having a high risk of sleep apnea and restless leg syndrome, respectively. The results of multiple linear regression showed that cognitive impairment was associated with insomnia (β = -0.037, p < 0.001) and narcolepsy (β = -0.023, p < 0.001). The association between sleep apnea (β = -0.002, p > 0.05), REM sleep behavior disorder (β = 0.006, p > 0.05), restless leg syndrome (β = -0.007, p > 0.05), and cognitive impairment were not supported. Other factors associated with cognitive impairment were gender, age, education level, married status, and region.

CONCLUSION

This study provides some epidemiological evidence for the association between sleep disturbances and cognitive impairment among community residents in central China. In this study, the associations between insomnia, narcolepsy, and cognitive impairment were identified, but the associations between sleep apnea, REM sleep behavior disorder, narcolepsy, restless leg syndrome, and cognitive impairment were not supported among community residents.

Association of Sleep and β-Amyloid Pathology Among Older Cognitively Unimpaired Adults

IMPORTANCE

Disrupted sleep commonly occurs with progressing neurodegenerative disease. Large, well-characterized neuroimaging studies of cognitively unimpaired adults are warranted to clarify the magnitude and onset of the association between sleep and emerging β-amyloid (Aβ) pathology.

OBJECTIVE

To evaluate the associations between daytime and nighttime sleep duration with regional Aβ pathology in older cognitively unimpaired adults.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, screening data were collected between April 1, 2014, and December 31, 2017, from healthy, cognitively unimpaired adults 65 to 85 years of age who underwent florbetapir F 18 positron emission tomography (PET), had APOE genotype information, scored between 25 and 30 on the Mini-Mental State Examination, and had a Clinical Dementia Rating of 0 for the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study. Data analysis was performed from December 1, 2019, to May 10, 2021.

EXPOSURES

Self-reported daytime and nighttime sleep duration.

MAIN OUTCOMES AND MEASURES

Regional Aβ pathology, measured by florbetapir PET standardized uptake value ratio.

RESULTS

Amyloid PET and sleep duration information was acquired on 4425 cognitively unimpaired participants (mean [SD] age, 71.3 [4.7] years; 2628 [59.4%] female; 1509 [34.1%] tested Aβ positive). Each additional hour of nighttime sleep was associated with a 0.005 reduction of global Aβ standardized uptake value ratio (F1, 4419 = 5.0; P = .03), a 0.009 reduction of medial orbitofrontal Aβ (F1, 4419 = 17.4; P < .001), and a 0.011 reduction of anterior cingulate Aβ (F1, 4419 = 15.9; P < .001). When restricting analyses to participants who tested Aβ negative, nighttime sleep was associated with a 0.006 reduction of medial orbitofrontal Aβ (F1,2910 = 16.9; P < .001) and a 0.005 reduction of anterior cingulate Aβ (F1,2910 = 7.6; P = .03). Daytime sleep was associated with a 0.013 increase of precuneus Aβ (F1,2910 = 7.3; P = .03) and a 0.024 increase of posterior cingulate Aβ (F1,2910 = 14.2; P = .001) in participants who tested Aβ negative.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, the increased risk of Aβ deposition with reduced nighttime sleep duration occurred early, before cognitive impairment or significant Aβ deposition. Daytime sleep may be associated with an increase in risk for early Aβ accumulation and did not appear to be corrective for loss of nighttime sleep, demonstrating a circadian rhythm dependence of sleep in preventing Aβ accumulation. Treatments that improve sleep may reduce early Aβ accumulation and aid in delaying the onset of cognitive dysfunction associated with early Alzheimer disease.

Brain changes associated with sleep disruption in cognitively unimpaired older adults: A short review of neuroimaging studies

Ageing is characterized by a progressive decline of sleep quality. Sleep difficulties are increasingly recognized as a risk factor for Alzheimer's disease (AD), and have been associated with cognitive decline. However, the brain substrates underlying this association remain unclear. In this review, our objective was to provide a comprehensive overview of the relationships between sleep changes and brain structural, functional and molecular integrity, including amyloid and tau pathologies in cognitively unimpaired older adults. We especially discuss the topography and causality of these associations, as well as the potential underlying mechanisms. Taken together, current findings converge to a link between several sleep parameters, amyloid and tau levels in the CSF, and neurodegeneration in diffuse frontal, temporal and parietal areas. However, the existing literature remains heterogeneous, and the specific sleep changes associated with early AD pathological changes, in terms of topography and neuroimaging modality, is not clearly established yet. Notably, if slow wave sleep disruption seems to be related to frontal amyloid deposition, the brain correlates of sleep-disordered breathing and REM sleep disruption remain unclear. Moreover, sleep parameters associated with tau- and FDG-PET imaging are largely unexplored. Lastly, whether sleep disruption is a cause or a consequence of brain alterations remains an open question.

Gray matter volume and estimated brain age gap are not linked with sleep-disordered breathing

Alzheimer's disease (AD) and sleep-disordered breathing (SDB) are prevalent conditions with a rising burden. It is suggested that SDB may contribute to cognitive decline and advanced aging. Here, we assessed the link between self-reported SDB and gray matter volume in patients with AD, mild cognitive impairment (MCI) and healthy controls (HCs). We further investigated whether SDB was associated with advanced brain aging. We included a total of 330 participants, divided based on self-reported history of SDB, and matched across diagnoses for age, sex and presence of the Apolipoprotein E4 allele, from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Gray-matter volume was measured using voxel-wise morphometry and group differences in terms of SDB, cognitive status, and their interaction were assessed. Further, using an age-prediction model fitted on gray-matter data of external datasets, we predicted study participants' age from their structural images. Cognitive decline and advanced age were associated with lower gray matter volume in various regions, particularly in the bilateral temporal lobes. Brains age was well predicted from the morphological data in HCs and, as expected, elevated in MCI and particularly in AD subjects. However, there was neither a significant difference between regional gray matter volume in any diagnostic group related to the SDB status, nor in SDB-by-cognitive status interaction. Moreover, we found no difference in estimated chronological age gap related to SDB, or by-cognitive status interaction. Contrary to our hypothesis, we were not able to find a general or a diagnostic-dependent association of SDB with either gray-matter volumetric or brain aging.