Alzheimer's Disease and Sleep–Wake Disturbances: Amyloid, Astrocytes, and Animal Models

Vanderheyden, William M.; Lim, Miranda M.; Musiek, Erik S.; Gerstner, Jason R.

doi:10.1523/jneurosci.1135-17.2017

Cited by 58 publications

(55 citation statements)

References 137 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…( Supplementary Table 5). This finding is inconsistent with the observational association between cognitive decline in older age and poorer sleep quality [33][34][35][36] . We also noted that the APOE Table 6 and Supplementary Methods).…”

Section: P=0001)contrasting

confidence: 73%

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

VTv

et al. 2018

Preprint

View full text Add to dashboard Cite

Sleep is an essential human function but its regulation is poorly understood. Identifying genetic variants associated with quality, quantity and timing of sleep will provide biological insights into the regulation of sleep and potential links with disease. Using accelerometer data from 85,670 individuals in the UK Biobank, we performed a genome-wide association study of 8 accelerometer-derived sleep traits. We identified 47 genetic associations across the sleep traits (P<5x10 -8 ) and replicated our findings in 5,819 individuals from 3 independent studies. These included 10 novel associations for sleep duration and 26 for sleep quality. Most newly identified variants were associated with a single sleep trait, but variants previously associated with restless legs syndrome were observed to be associated with multiple sleep traits. As a group, sleep quality loci were enriched for serotonin processing genes and all sleep traits were enriched for cerebellar-expressed genes. These findings provide new biological insights into sleep characteristics.

show abstract

Section: P=0001)contrasting

confidence: 73%

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

VTv

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…However, even in cognitively healthy participants a shorter sleep duration and poor sleep quality was associated with beta amyloid burden 60 . In concordance, animal models showed that sleep deprivation increases interstitial fluid beta amyloid levels 61,62 . These studies indicate that poor sleep might also promote beta amyloid deposition and neurocognitive decline and impairment.…”

Section: Discussionmentioning

confidence: 67%

Associations between self-reported sleep characteristics and incident mild cognitive impairment: The Heinz Nixdorf Recall Cohort Study

Brachem

Winkler

Tebrügge

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Associations of sleep characteristics with mild cognitive impairment (Mci) have been examined in cross-sectional, but rarely in longitudinal studies. incident Mci and sleep characteristics were assessed in 1,890 participants of the first and second follow-up of the Heinz Nixdorf Recall study, a populationbased cohort study in Germany (age at first follow-up 50−80 years, mean follow-up 5.2 years). MCI was assessed with extensive cognitive tests. Sleep questionnaires including pSQi (pittsburgh Sleep Quality index) were used to assess sleep quality, sleep disturbances, time asleep, and time in bed. Relative risks (RR) of developing Mci when exposed to sleep characteristics were assessed in regression models adjusted for sociodemographic and cardiovascular risk factors. poor sleep quality (pSQi > 5) (RR = 1.43, 95% CI: 1.12−1.82, fully adjusted, reference: PSQI ≤ 5) and difficulties initiating sleep (almost nightly versus never) (RR = 1.40, 0.94−2.08) were associated with incident MCI. For time in bed, the risk of MCI was increased for ≤ 5 hours (RR = 2.86, 1.24─6.60, reference:7 to <8 hours). In this longitudinal study with older participants, MCI risk was increased in persons with poor sleep quality, difficulties initiating sleep, and short time in bed. Dementia is a growing public health burden worldwide. In 2013 an estimated 44.35 million persons had a prevalent dementia 1. By 2050 it is expected that this number triples to 135.46 million prevalent dementia cases 2,3. Because no effective causal medical therapies are available for dementia, primary prevention of dementia and of its early precursors is the most promising option currently available to cap the rising prevalence 4,5. Subjects with mild cognitive impairment (MCI) have an increased risk of progression to Alzheimer's disease (AD) and other forms of dementia. Therefore, identification of modifiable risk factors for incident MCI is important, and poor sleep is considered a potential risk factor for cognitive decline and disease progression 6-13. Sleep characteristics were suggested as modifiable risk factors for cognitive decline, for example by influencing hippocampal volume 14,15. Two up-to-date reviews on this relationship indicate an association between cognitive decline and sleep problems, such as poor sleep quality, short or long sleep duration, and sleep disturbances 12,16. However, both reviews concluded that there is still a need for long term prospective studies to ensure that sleep problems precede cognitive decline 12,16. Two recently published cohort studies on sleep characteristics and dementia were not included in these reviews 17,18. Both suggest that self-reported long sleep duration as well as self-reported sleep disturbances increase the risk of dementia. Additionally, Jackowska and Cadar 19 found an association between decreased cognitive function and self-reported long and short sleep duration in their

show abstract

“…Some studies in animal models of neurodegenerative diseases tackle this important issue ( Vanderheyden et al, 2018 ; Medeiros et al, 2019 ) but few are specific for ALS models. It is therefore crucial to provide evidence of this early symptom and to propose a suitable tool to investigate circadian and sleep related disruption in a classical mouse model of ALS as the SOD1G93A transgenic strain ( Gurney et al, 1994 ).…”

Section: Introductionmentioning

confidence: 99%

A Non-invasive Digital Biomarker for the Detection of Rest Disturbances in the SOD1G93A Mouse Model of ALS

Golini

Rigamonti²,

Iannello³

et al. 2020

Front. Neurosci.

View full text Add to dashboard Cite

Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease that affects both central and peripheral nervous system, leading to the degeneration of motor neurons, which eventually results in muscle atrophy, paralysis, and death. Sleep disturbances are common in patients with ALS, leading to even further deteriorated quality of life. Investigating methods to potentially assess sleep and rest disturbances in animal models of ALS is thus of crucial interest. We used an automated home cage monitoring system (DVC ® ) to capture irregular activity patterns that can potentially be associated with sleep and rest disturbances and thus to the progression of ALS in the SOD1G93A mouse model. DVC ® enables non-intrusive 24/7 long term animal activity monitoring, which we assessed together with body weight decline and neuromuscular function deterioration measured by grid hanging and grip strength tests in male and female mice from 7 until 24 weeks of age. We show that as the ALS progresses over time in SOD1G93A mice, activity patterns start becoming irregular, especially during day time, with frequent activity bouts that are neither observed in control mice nor in SOD1G93A at a younger age. The increasing irregularities of activity pattern are quantitatively captured by designing a novel digital biomarker, referred to as Regularity Disruption Index (RDI). We show that RDI is a robust measure capable of detecting home cage activity patterns that could be related to rest/sleep-related disturbances during the disease progression. Moreover, the RDI rise during the early symptomatic stage parallels grid hanging and body weight decline. The non-intrusive long-term continuous monitoring of animal activity enabled by DVC ® has been instrumental in discovering novel activity patterns potentially correlated, once validated, with sleep and rest disturbances in the SOD1G93A mouse model of the ALS disease.

show abstract

Alzheimer's Disease and Sleep–Wake Disturbances: Amyloid, Astrocytes, and Animal Models

Cited by 58 publications

References 137 publications

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

Associations between self-reported sleep characteristics and incident mild cognitive impairment: The Heinz Nixdorf Recall Cohort Study

A Non-invasive Digital Biomarker for the Detection of Rest Disturbances in the SOD1G93A Mouse Model of ALS

Contact Info

Product

Resources

About