Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis

Emma L Anderson*, Rebecca Richmond, Samuel E Jones, Gibran Hemani, Kaitlin H Wade, Hassan S Dashti, Jacqueline M. Lane, Heming Wang, Richa Saxena, Ben M Brumpton, Roxanna S Korologou-Linden, Jonas Bille Nielsen, Bjørn Olav Asvold, Goncalo R Abecasis, E J Coulthard, Simon D. Kyle, Robin N Beaumont, Jessica Tyrrell, Timothy Frayling, Marcus R MunafoAndrew R. Wood, Yoav Ben-Shlomo, Laura D Howe, Debbie A Lawlor, Michael N Weedon, George Davey Smith

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

INTRODUCTION: It is established that Alzheimer’s disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.

METHODS Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness) on AD risk.

RESULTS Overall, there was little evidence that sleep traits affect the risk of AD. There was some evidence to suggest that self-reported daytime napping was associated with lower AD risk (odds ratio [OR]: 0.70, 95% confidence interval [CI]: 0.50 to 0.99). Some other sleep traits (accelerometer-measured eveningness and sleep duration, and self-reported daytime sleepiness) had ORs for AD risk of a similar magnitude to daytime napping, but were less precisely estimated.

DISCUSSON Our findings provide tentative evidence that daytime napping may reduce AD risk. However, findings should be replicated using independent samples.
Original languageEnglish
JournalInternational Journal of Epidemiology
Publication statusAccepted/In press - 28 Jul 2020

Structured keywords

  • Brain and Behaviour

Keywords

  • Sleep
  • Alzheimer’s disease
  • Dementia
  • Mendelian randomization
  • Causal Inference

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