2020
DOI: 10.1093/sleep/zsaa137
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Alzheimer’s disease genetic risk and sleep phenotypes in healthy young men: association with more slow waves and daytime sleepiness

Abstract: Study Objectives Sleep disturbances and genetic variants have been identified as risk factors for Alzheimer’s disease. Our goal was to assess whether genome-wide polygenic risk scores (PRS) for AD associate with sleep phenotypes in young adults, decades before typical AD symptom onset. Methods We computed whole-genome Polygenic Risk Scores (PRS) for AD and extensively phenotyped sleep under different sleep conditions, includi… Show more

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Cited by 11 publications
(11 citation statements)
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References 77 publications
(103 reference statements)
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“…For example, patients with Alzheimer’s Disease (AD) have reductions in the amount of rapid eye movement (REM) and non-REM (NREM) sleep, an increase in the amount of wakefulness, more sleep fragmentation (Allen et al, 1987; Loewenstein et al, 1982; Prinz et al, 1982; Vitiello et al, 1990), and electroencephalographic (EEG) alterations in sleep features (D’Atri et al, 2021), yet these symptoms occur many years before cognitive decline and cell death (Sterniczuk et al, 2013). Healthy young men (∼22 years old) with high genome-wide polygenic risk scores for AD have higher slow wave energy during sleep (Muto et al, 2021). Similarly, both excessive daytime sleepiness and high sleep fragmentation in cognitively normal adults are associated with increased risk of Aβ deposition (Spira et al, 2018) and AD, respectively (Lim et al, 2013).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…For example, patients with Alzheimer’s Disease (AD) have reductions in the amount of rapid eye movement (REM) and non-REM (NREM) sleep, an increase in the amount of wakefulness, more sleep fragmentation (Allen et al, 1987; Loewenstein et al, 1982; Prinz et al, 1982; Vitiello et al, 1990), and electroencephalographic (EEG) alterations in sleep features (D’Atri et al, 2021), yet these symptoms occur many years before cognitive decline and cell death (Sterniczuk et al, 2013). Healthy young men (∼22 years old) with high genome-wide polygenic risk scores for AD have higher slow wave energy during sleep (Muto et al, 2021). Similarly, both excessive daytime sleepiness and high sleep fragmentation in cognitively normal adults are associated with increased risk of Aβ deposition (Spira et al, 2018) and AD, respectively (Lim et al, 2013).…”
Section: Introductionmentioning
confidence: 99%
“…Consistent with this, some transgenic AD mouse models that overproduce Aβ display sleep disruptions prior to plaque formation, even without evident neuronal loss [5][6][7][8][9][10][11] . Recently, human studies have found that harbouring a high genetic risk for AD correlates with sleep changes, such as increased sleep rebound following sleep loss, even in young adults 12 . These observations suggest that there may be underlying early biological processes important for sleep regulation that are governed by AD susceptibility genes and contribute to disease progression.…”
Section: Introductionmentioning
confidence: 99%
“…A total of 364 young healthy men were initially recruited as part of a larger project assessing the genetic background of sleep regulation (see also Berthomier et al., 2020 ; Muto et al., 2021 ). Within that context, a homogeneous sample with respect to demographic variables (age [18–31], gender [male], ethnicity [Caucasian]) and health status was recruited.…”
Section: Methodsmentioning
confidence: 99%
“…Our sample of participants was recruited in the context of a project that aimed to assess the genetic background of sleep regulation (e.g. Muto et al., 2021 ) and is thus only composed of men, mainly university students. Women have been shown to present higher sleep SWA than men, and this difference seems to be present in adults of various ages ( Carrier et al., 2001 ; Dijk, 2006 ; Dijk et al., 1989 ).…”
Section: Limitations and Perspectivesmentioning
confidence: 99%
“…with multiple algorithms [58,59] or assess sleep fragmentation via transition state probability [60].…”
Section: Plos Computational Biologymentioning
confidence: 99%