1
|
Cavaillès C, Dintica C, Habes M, Leng Y, Carnethon MR, Yaffe K. Association of Self-Reported Sleep Characteristics With Neuroimaging Markers of Brain Aging Years Later in Middle-Aged Adults. Neurology 2024; 103:e209988. [PMID: 39442064 PMCID: PMC11498938 DOI: 10.1212/wnl.0000000000209988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 08/26/2024] [Indexed: 10/25/2024] Open
Abstract
OBJECTIVES To determine the association between early midlife sleep and advanced brain aging patterns in late midlife. METHODS Using the CARDIA study, we analyzed sleep data at baseline and 5 years later, focusing on short sleep duration, bad sleep quality (SQ), difficulty initiating and maintaining sleep (DIS and DMS), early morning awakening (EMA), and daytime sleepiness. These were categorized into 0-1, 2-3, and >3 poor sleep characteristics (PSC). Brain MRIs obtained 15 years later were used to determine brain age through a machine learning approach based on age-related atrophy. RESULTS This cohort study included 589 participants (mean age 40.4 ± 3.4 years, 53% women). At baseline, around 70% reported 0-1 PSC, 22% reported 2%-3%, and 8% reported >3 PSC. In multivariable linear regression analyses, participants with 2-3 or >3 PSC had 1.6-year (β = 1.61, 95% CI 0.28-2.93) and 2.6-year (β = 2.64, 95% CI 0.59-4.69) older brain age, respectively, compared with those with 0-1 PSC. Of the individual characteristics, bad SQ, DIS, DMS, and EMA were associated with greater brain age, especially when persistent over the 5-year follow-up. DISCUSSION Poor sleep was associated with advanced brain age in midlife, highlighting the importance of investigating early sleep interventions for preserving brain health.
Collapse
Affiliation(s)
- Clémence Cavaillès
- From the Departments of Psychiatry and Behavioral Sciences (C.C., C.D., Y.L., K.Y.), Neurology (K.Y.), and Epidemiology (K.Y.), University of California, San Francisco; Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core (M.H.), Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio; Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics (M.H.), University of Pennsylvania, Philadelphia; and Department of Preventive Medicine (M.R.C.), Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Christina Dintica
- From the Departments of Psychiatry and Behavioral Sciences (C.C., C.D., Y.L., K.Y.), Neurology (K.Y.), and Epidemiology (K.Y.), University of California, San Francisco; Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core (M.H.), Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio; Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics (M.H.), University of Pennsylvania, Philadelphia; and Department of Preventive Medicine (M.R.C.), Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Mohamad Habes
- From the Departments of Psychiatry and Behavioral Sciences (C.C., C.D., Y.L., K.Y.), Neurology (K.Y.), and Epidemiology (K.Y.), University of California, San Francisco; Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core (M.H.), Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio; Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics (M.H.), University of Pennsylvania, Philadelphia; and Department of Preventive Medicine (M.R.C.), Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Yue Leng
- From the Departments of Psychiatry and Behavioral Sciences (C.C., C.D., Y.L., K.Y.), Neurology (K.Y.), and Epidemiology (K.Y.), University of California, San Francisco; Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core (M.H.), Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio; Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics (M.H.), University of Pennsylvania, Philadelphia; and Department of Preventive Medicine (M.R.C.), Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Mercedes R Carnethon
- From the Departments of Psychiatry and Behavioral Sciences (C.C., C.D., Y.L., K.Y.), Neurology (K.Y.), and Epidemiology (K.Y.), University of California, San Francisco; Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core (M.H.), Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio; Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics (M.H.), University of Pennsylvania, Philadelphia; and Department of Preventive Medicine (M.R.C.), Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Kristine Yaffe
- From the Departments of Psychiatry and Behavioral Sciences (C.C., C.D., Y.L., K.Y.), Neurology (K.Y.), and Epidemiology (K.Y.), University of California, San Francisco; Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core (M.H.), Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio; Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics (M.H.), University of Pennsylvania, Philadelphia; and Department of Preventive Medicine (M.R.C.), Northwestern University Feinberg School of Medicine, Chicago, IL
| |
Collapse
|
2
|
Golombek DA, Eyre H, Spiousas I, Casiraghi LP, Hartikainen KM, Partonen T, Pyykkö M, Reynolds CF, Hynes WM, Bassetti CLA, Berk M, Hu K, Ibañez A. Sleep Capital: Linking Brain Health to Wellbeing and Economic Productivity Across the Lifespan. Am J Geriatr Psychiatry 2024:S1064-7481(24)00405-6. [PMID: 39117505 DOI: 10.1016/j.jagp.2024.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Revised: 07/12/2024] [Accepted: 07/13/2024] [Indexed: 08/10/2024]
Abstract
INTRODUCTION AND FRAMEWORK Sleep capital contributes to individual and societal wellbeing, productivity, and economic outcomes and involves a novel aspect of brain capital. It encompasses the quality and quantity of sleep as integral components that influence cognitive abilities, mental and brain health, and physical health, affecting workplace productivity, learning, decision-making, and overall economic performance. Here, we bring a framework to understand the complex relationship between sleep quality, health, wellbeing, and economic productivity. Then we outline the multilevel impact of sleep on cognitive abilities, mental/brain health, and economic indicators, providing evidence for the substantial returns on investment in sleep health initiatives. Moreover, sleep capital is a key factor when considering brain health across the lifespan, especially for the aging population. DISCUSSION We propose specific elements and main variables to develop specific indexes of sleep capital to address its impacts on health, wellbeing and productivity. CONCLUSION Finally, we suggest policy recommendations, workplace interventions, and individual strategies to promote sleep health and brain capital. Investing in sleep capital is essential for fostering a healthier, happier, fairer and more productive society.
Collapse
Affiliation(s)
- Diego A Golombek
- Laboratorio Interdisciplinario del Tiempo (LITERA) (DAG, IS, LPC), Universidad de San Andrés/CONICET, Buenos Aires, Argentina.
| | - Harris Eyre
- Baker Institute for Public Policy (HE), Rice University, Houston, TX, USA; Global Brain Health Institute (HE), University of California San Francisco (UCSF), San Francisco, CA, USA; Department of Psychiatry and Behavioral Science (HE), (UCSF), San Francisco, CA, USA; Department of Psychiatry and Behavioral Science (HE), Baylor College of Medicine, Houston, TX, USA; Department of Psychiatry and Behavioral Science (HE), Houston Methodist, Houston, TX, USA; Department of Psychiatry and Behavioral Science (HE), The University of Texas Health Sciences Center at Houston, Houston, TX, USA; Institute for Mental and Physical Health and Clinical Translation (IMPACT) (HE), Deakin University, Geelong, Victoria, Australia; Euro-Mediterranean Economists Association (HE), Barcelona, Spain; Meadows Mental Health Policy Institute (HE), Dallas, TX, USA; Frontier Technology Lab, School of Engineering (HE), Stanford University, Palo Alto, CA, USA
| | - Ignacio Spiousas
- Laboratorio Interdisciplinario del Tiempo (LITERA) (DAG, IS, LPC), Universidad de San Andrés/CONICET, Buenos Aires, Argentina
| | - Leandro P Casiraghi
- Laboratorio Interdisciplinario del Tiempo (LITERA) (DAG, IS, LPC), Universidad de San Andrés/CONICET, Buenos Aires, Argentina
| | - Kaisa M Hartikainen
- Faculty of Medicine and Health Technology (KMH), Tampere University, Tampere, Finland; Behavioral Neurology Research Group (KMH), Tampere University Hospital, Wellbeing Services County of Pirkanmaa, Tampere, Finland; National Brain Health Programme (KMH), Helsinki, Finland
| | - Timo Partonen
- Finnish Institute for Health and Welfare (TP), Helsinki, Finland; Department of Psychiatry (TP), University of Helsinki, Helsinki, Finland
| | - Mika Pyykkö
- Finnish Brain Association and Finnish Centre for Health Promotion (MP), Helsinki, Finland
| | - Charles F Reynolds
- Graduate School of Public Health, University of Pittsburgh School of Medicine (CFR), Pittsburgh, PA, USA
| | - William M Hynes
- Institute for Global Prosperity (MH), University College London, London, UK; Santa Fe Institute (MH), Santa Fe, NM, USA; World Bank (MH), Washington, DC, USA
| | - Claudio L A Bassetti
- Neurology Department, Inselspital (CLAB), University of Bern, Bern, Switzerland; Swiss Brain Health Plan (CLAB), Bern, Switzerland
| | - Michael Berk
- School of Medicine (MB), Deakin University and Barwon Health. Institute for Mental and Physical Health and Clinical Translation (IMPACT), Victoria, Australia
| | - Kun Hu
- Division of Sleep Medicine (KH), Harvard Medical School, Boston, MA, USA; Medical Biodynamics Center (KH), Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Agustín Ibañez
- Latin American Brain Health institute (Brainlat) (CSCN) (AI), Universidad Adolfo Ibanez, Santiago, Chile; ChileGlobal Brain Health Institute, Trinity College Dublin, Ireland; Center for Social and Cognitive Neuroscience (CSCN) (AI), Universidad Adolfo Ibanez, Santiago, Chile; Universidad de San Andrés (AI), Buenos Aires, Argentina
| |
Collapse
|
3
|
Misrani A, Tabassum S, Zhang ZY, Tan SH, Long C. Urolithin A Prevents Sleep-deprivation-induced Neuroinflammation and Mitochondrial Dysfunction in Young and Aged Mice. Mol Neurobiol 2024; 61:1448-1466. [PMID: 37725214 DOI: 10.1007/s12035-023-03651-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 09/10/2023] [Indexed: 09/21/2023]
Abstract
Sleep deprivation (SD) has reached epidemic proportions worldwide and negatively affects people of all ages. Cognitive impairment induced by SD involves neuroinflammation and mitochondrial dysfunction, but the underlying mechanisms are largely unknown. Urolithin A (UA) is a natural compound that can reduce neuroinflammation and improve mitochondrial health, but its therapeutic effects in a SD model have not yet been studied. Young (3-months old) and aged (12-months old) mice were sleep deprived for 24 h, and UA (2.5 mg/kg or 10 mg/kg) was injected intraperitoneally for 7 consecutive days before the SD period. Immunofluorescent staining, western blotting, and RT-PCR were employed to evaluate levels of proteins involved in neuroinflammation and mitochondrial function. Transmission electron microscope and Golgi-Cox staining were used to evaluate mitochondrial and neuronal morphology, respectively. Finally, contextual fear conditioning and the Morris water maze test were conducted to assess hippocampal learning and memory. In the hippocampus of young (3 months-old) and aged (12 months-old) mice subjected to 24 h SD, pretreatment with UA prevented the activation of microglia and astrocytes, NF-κB-NLRP3 signaling and IL-1β, IL6, TNF-α cytokine production, thus ameliorating neuroinflammation. Furthermore, UA also attenuated SD-induced mitochondrial dysfunction, normalized autophagy and mitophagy and protected hippocampal neuronal morphology. Finally, UA prevented SD-induced hippocampal memory impairment. Cumulatively, the results show that UA imparts cognitive protection by reducing neuroinflammation and enhancing mitochondrial function in SD mice. This suggests that UA shows promise as a therapeutic for the treatment of SD-induced neurological disorders.
Collapse
Affiliation(s)
- Afzal Misrani
- South China Normal University-Panyu Central Hospital Joint Laboratory of Translational Medical Research, Panyu Central Hospital, Guangzhou, 511400, China
- School of Life Sciences, South China Normal University, Guangzhou, 510631, China
| | - Sidra Tabassum
- South China Normal University-Panyu Central Hospital Joint Laboratory of Translational Medical Research, Panyu Central Hospital, Guangzhou, 511400, China
- School of Life Sciences, South China Normal University, Guangzhou, 510631, China
| | - Zai-Yong Zhang
- Department of Cardiology, Panyu Central Hospital, Guangzhou, 511400, China
- Cardiovascular Institute of Panyu District, Guangzhou, 511400, China
| | - Shao-Hua Tan
- Department of Neurology, Panyu District Central Hospital, Guangzhou, 511400, China
| | - Cheng Long
- South China Normal University-Panyu Central Hospital Joint Laboratory of Translational Medical Research, Panyu Central Hospital, Guangzhou, 511400, China.
- School of Life Sciences, South China Normal University, Guangzhou, 510631, China.
| |
Collapse
|
4
|
Stolicyn A, Lyall LM, Lyall DM, Høier NK, Adams MJ, Shen X, Cole JH, McIntosh AM, Whalley HC, Smith DJ. Comprehensive assessment of sleep duration, insomnia, and brain structure within the UK Biobank cohort. Sleep 2024; 47:zsad274. [PMID: 37889226 PMCID: PMC10851840 DOI: 10.1093/sleep/zsad274] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/22/2023] [Indexed: 10/28/2023] Open
Abstract
STUDY OBJECTIVES To assess for associations between sleeping more than or less than recommended by the National Sleep Foundation (NSF), and self-reported insomnia, with brain structure. METHODS Data from the UK Biobank cohort were analyzed (N between 9K and 32K, dependent on availability, aged 44 to 82 years). Sleep measures included self-reported adherence to NSF guidelines on sleep duration (sleeping between 7 and 9 hours per night), and self-reported difficulty falling or staying asleep (insomnia). Brain structural measures included global and regional cortical or subcortical morphometry (thickness, surface area, volume), global and tract-related white matter microstructure, brain age gap (difference between chronological age and age estimated from brain scan), and total volume of white matter lesions. RESULTS Longer-than-recommended sleep duration was associated with lower overall grey and white matter volumes, lower global and regional cortical thickness and volume measures, higher brain age gap, higher volume of white matter lesions, higher mean diffusivity globally and in thalamic and association fibers, and lower volume of the hippocampus. Shorter-than-recommended sleep duration was related to higher global and cerebellar white matter volumes, lower global and regional cortical surface areas, and lower fractional anisotropy in projection fibers. Self-reported insomnia was associated with higher global gray and white matter volumes, and with higher volumes of the amygdala, hippocampus, and putamen. CONCLUSIONS Sleeping longer than recommended by the NSF is associated with a wide range of differences in brain structure, potentially indicative of poorer brain health. Sleeping less than recommended is distinctly associated with lower cortical surface areas. Future studies should assess the potential mechanisms of these differences and investigate long sleep duration as a putative marker of brain health.
Collapse
Affiliation(s)
- Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Laura M Lyall
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - Donald M Lyall
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - Nikolaj Kjær Høier
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Copenhagen Research Center for Mental Health CORE, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mark J Adams
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - James H Cole
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Heather C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Daniel J Smith
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| |
Collapse
|
5
|
Ramasubbu K, Ramanathan G, Venkatraman G, Rajeswari VD. Sleep-associated insulin resistance promotes neurodegeneration. Mol Biol Rep 2023; 50:8665-8681. [PMID: 37580496 DOI: 10.1007/s11033-023-08710-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/25/2023] [Indexed: 08/16/2023]
Abstract
Lifestyle modification can lead to numerous health issues closely associated with sleep. Sleep deprivation and disturbances significantly affect inflammation, immunity, neurodegeneration, cognitive depletion, memory impairment, neuroplasticity, and insulin resistance. Sleep significantly impacts brain and memory formation, toxin excretion, hormonal function, metabolism, and motor and cognitive functions. Sleep restriction associated with insulin resistance affects these functions by interfering with the insulin signalling pathway, neurotransmission, inflammatory pathways, and plasticity of neurons. So, in this review, We discuss the evidence that suggests that neurodegeneration occurs via sleep and is associated with insulin resistance, along with the insulin signalling pathways involved in neurodegeneration and neuroplasticity, while exploring the role of hormones in these conditions.
Collapse
Affiliation(s)
- Kanagavalli Ramasubbu
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - Gnanasambandan Ramanathan
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - Ganesh Venkatraman
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - V Devi Rajeswari
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
| |
Collapse
|
6
|
Lian J, Xu L, Song T, Peng Z, Zhang Z, An X, Chen S, Zhong X, Shao Y. Reduced Resting-State EEG Power Spectra and Functional Connectivity after 24 and 36 Hours of Sleep Deprivation. Brain Sci 2023; 13:949. [PMID: 37371427 DOI: 10.3390/brainsci13060949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
Total sleep deprivation (TSD) leads to cognitive decline; however, the neurophysiological mechanisms underlying resting-state electroencephalogram (EEG) changes after TSD remain unclear. In this study, 42 healthy adult participants were subjected to 36 h of sleep deprivation (36 h TSD), and resting-state EEG data were recorded at baseline, after 24 h of sleep deprivation (24 h TSD), and after 36 h TSD. The analysis of resting-state EEG at baseline, after 24 h TSD, and after 36 h TSD using source localization analysis, power spectrum analysis, and functional connectivity analysis revealed a decrease in alpha-band power and a significant increase in delta-band power after TSD and impaired functional connectivity in the default mode network, precuneus, and inferior parietal lobule. The cortical activities of the precuneus, inferior parietal lobule, and superior parietal lobule were significantly reduced, but no difference was found between the 24 h and 36 h TSD groups. This may indicate that TSD caused some damage to the participants, but this damage temporarily slowed during the 24 h to 36 h TSD period.
Collapse
Affiliation(s)
- Jie Lian
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Lin Xu
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Tao Song
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Ziyi Peng
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Zheyuan Zhang
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Xin An
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Shufang Chen
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Xiao Zhong
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing 100084, China
| |
Collapse
|
7
|
Nollet M, Franks NP, Wisden W. Understanding Sleep Regulation in Normal and Pathological Conditions, and Why It Matters. J Huntingtons Dis 2023; 12:105-119. [PMID: 37302038 PMCID: PMC10473105 DOI: 10.3233/jhd-230564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/22/2023] [Indexed: 06/12/2023]
Abstract
Sleep occupies a peculiar place in our lives and in science, being both eminently familiar and profoundly enigmatic. Historically, philosophers, scientists and artists questioned the meaning and purpose of sleep. If Shakespeare's verses from MacBeth depicting "Sleep that soothes away all our worries" and "relieves the weary laborer and heals hurt minds" perfectly epitomize the alleviating benefits of sleep, it is only during the last two decades that the growing understanding of the sophisticated sleep regulatory mechanisms allows us to glimpse putative biological functions of sleep. Sleep control brings into play various brain-wide processes occurring at the molecular, cellular, circuit, and system levels, some of them overlapping with a number of disease-signaling pathways. Pathogenic processes, including mood disorders (e.g., major depression) and neurodegenerative illnesses such Huntington's or Alzheimer's diseases, can therefore affect sleep-modulating networks which disrupt the sleep-wake architecture, whereas sleep disturbances may also trigger various brain disorders. In this review, we describe the mechanisms underlying sleep regulation and the main hypotheses drawn about its functions. Comprehending sleep physiological orchestration and functions could ultimately help deliver better treatments for people living with neurodegenerative diseases.
Collapse
Affiliation(s)
- Mathieu Nollet
- UK Dementia Research Institute and Department of Life Sciences, Imperial College London, London, UK
| | - Nicholas P. Franks
- UK Dementia Research Institute and Department of Life Sciences, Imperial College London, London, UK
| | - William Wisden
- UK Dementia Research Institute and Department of Life Sciences, Imperial College London, London, UK
| |
Collapse
|