Andrew W Varga1, Margaret E Wohlleber2, Sandra Giménez3, Sergio Romero3,4, Joan F Alonso4,5,6, Emma L Ducca1, Korey Kam7, Clifton Lewis1,2, Emily B Tanzi2, Samuel Tweardy2, Akifumi Kishi8, Ankit Parekh9, Esther Fischer2, Tyler Gumb1,2, Daniel Alcolea3, Juan Fortea3,10, Alberto Lleó3,10, Kaj Blennow11, Henrik Zetterberg11, Lisa Mosconi2, Lidia Glodzik2, Elizabeth Pirraglia2, Omar E Burschtin1, Mony J de Leon2, David M Rapoport1, Shou-En Lu12, Indu Ayappa1, Ricardo S Osorio2. 1. Division of Pulmonary, Critical Care, and Sleep Medicine, NYU Langone Medical Center, New York, NY. 2. Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY. 3. Department of Neurology, Hospital de la Santa Creu i Sant Pau-Biomedical Research Institute Sant Pau- Universitat Autònoma de Barcelona, Spain. 4. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politecnica de Catalunya (UPC), Barcelona, Spain. 5. Escola Universitària d'Enginyeria Tècnica Industrial de Barcelona, UPC, Barcelona, Spain. 6. CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain. 7. The Nathan Kline Institute for Psychiatric Research, Orangeburg, NY. 8. Graduate School of Education, The University of Tokyo, Tokyo, Japan. 9. NYU Polytechnic School of Engineering, Brooklyn, NY. 10. Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED. 11. Institute of Neuroscience and Psychiatry, Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden. 12. Department of Biostatistics, Rutgers School of Public Health, Piscataway, NJ.
Abstract
STUDY OBJECTIVES: Emerging evidence suggests a role for sleep in contributing to the progression of Alzheimer disease (AD). Slow wave sleep (SWS) is the stage during which synaptic activity is minimal and clearance of neuronal metabolites is high, making it an ideal state to regulate levels of amyloid beta (Aβ). We thus aimed to examine relationships between concentrations of Aβ42 in the cerebrospinal fluid (CSF) and measures of SWS in cognitively normal elderly subjects. METHODS: Thirty-six subjects underwent a clinical and cognitive assessment, a structural MRI, a morning to early afternoon lumbar puncture, and nocturnal polysomnography. Correlations and linear regression analyses were used to assess for associations between CSF Aβ42 levels and measures of SWS controlling for potential confounders. Resulting models were compared to each other using ordinary least squared linear regression analysis. Additionally, the participant sample was dichotomized into "high" and "low" Aβ42 groups to compare SWS bout length using survival analyses. RESULTS: A significant inverse correlation was found between CSF Aβ42 levels, SWS duration and other SWS characteristics. Collectively, total SWA in the frontal lead was the best predictor of reduced CSF Aβ42 levels when controlling for age and ApoE status. Total sleep time, time spent in NREM1, NREM2, or REM sleep were not correlated with CSF Aβ42. CONCLUSIONS: In cognitively normal elderly, reduced and fragmented SWS is associated with increases in CSF Aβ42, suggesting that disturbed sleep might drive an increase in soluble brain Aβ levels prior to amyloid deposition.
STUDY OBJECTIVES: Emerging evidence suggests a role for sleep in contributing to the progression of Alzheimer disease (AD). Slow wave sleep (SWS) is the stage during which synaptic activity is minimal and clearance of neuronal metabolites is high, making it an ideal state to regulate levels of amyloid beta (Aβ). We thus aimed to examine relationships between concentrations of Aβ42 in the cerebrospinal fluid (CSF) and measures of SWS in cognitively normal elderly subjects. METHODS: Thirty-six subjects underwent a clinical and cognitive assessment, a structural MRI, a morning to early afternoon lumbar puncture, and nocturnal polysomnography. Correlations and linear regression analyses were used to assess for associations between CSF Aβ42 levels and measures of SWS controlling for potential confounders. Resulting models were compared to each other using ordinary least squared linear regression analysis. Additionally, the participant sample was dichotomized into "high" and "low" Aβ42 groups to compare SWS bout length using survival analyses. RESULTS: A significant inverse correlation was found between CSF Aβ42 levels, SWS duration and other SWS characteristics. Collectively, total SWA in the frontal lead was the best predictor of reduced CSF Aβ42 levels when controlling for age and ApoE status. Total sleep time, time spent in NREM1, NREM2, or REM sleep were not correlated with CSF Aβ42. CONCLUSIONS: In cognitively normal elderly, reduced and fragmented SWS is associated with increases in CSF Aβ42, suggesting that disturbed sleep might drive an increase in soluble brain Aβ levels prior to amyloid deposition.
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