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Chabal SA, Markwald RR, Chinoy ED. Life onboard a submarine: Sleep, fatigue, and lifestyle behaviors of sailors on a circadian-aligned watchstanding schedule. APPLIED ERGONOMICS 2024; 119:104321. [PMID: 38820921 DOI: 10.1016/j.apergo.2024.104321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 03/11/2024] [Accepted: 05/22/2024] [Indexed: 06/02/2024]
Abstract
This study characterizes, for the first time, the lives of U.S. Navy submariners engaged in normal, sea-based operations while following a circadian-aligned 24-h watchstanding schedule. Fifty-eight submarine crewmembers provided objective (actigraphy) and subjective (questionnaires) sleep data, and information about mood and lifestyle behaviors during 30 days underway. Projected performance scores and estimated circadian phase times were also calculated from actigraphy-based sleep/wake data. Submariners' objective (6.62 ± 0.94 h; mean ± SD) and subjective (5.90 ± 1.38 h) daily sleep quantities while underway were largely comparable to the sleep reportedly received by Sailors across other Navy platforms and watchstanding schedules. Additionally, submariners' actigraphy-predicted circadian phases shifted progressively toward better alignment with watchstanding schedules across time. Nevertheless, subjective sleep quality was low, submariners engaged in unfavorable lifestyle behaviors (lack of regular meals and exercise), and participants reported decreased mood at the completion of their underway time. Recommendations for countermeasure development are provided.
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Affiliation(s)
- Sarah A Chabal
- Naval Submarine Medical Research Laboratory, Groton, CT, USA; Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA; Leidos, Inc., Reston, VA, USA.
| | - Rachel R Markwald
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
| | - Evan D Chinoy
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
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2
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de Zambotti M, Goldstein C, Cook J, Menghini L, Altini M, Cheng P, Robillard R. State of the science and recommendations for using wearable technology in sleep and circadian research. Sleep 2024; 47:zsad325. [PMID: 38149978 DOI: 10.1093/sleep/zsad325] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/21/2023] [Indexed: 12/28/2023] Open
Abstract
Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.
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Affiliation(s)
- Massimiliano de Zambotti
- Center for Health Sciences, SRI International, Menlo Park, CA, USA
- Lisa Health Inc., Oakland, CA, USA
| | - Cathy Goldstein
- Sleep Disorders Center, Department of Neurology, University of Michigan-Ann Arbor, Ann Arbor, MI, USA
| | - Jesse Cook
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Luca Menghini
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
| | - Marco Altini
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Cheng
- Sleep Disorders and Research Center, Henry Ford Health, Detroit, MI, USA
| | - Rebecca Robillard
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
- Canadian Sleep Research Consortium, Canada
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3
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Song YM, Jeong J, de Los Reyes AA, Lim D, Cho CH, Yeom JW, Lee T, Lee JB, Lee HJ, Kim JK. Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data. EBioMedicine 2024; 103:105094. [PMID: 38579366 PMCID: PMC11002811 DOI: 10.1016/j.ebiom.2024.105094] [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: 10/02/2023] [Revised: 03/14/2024] [Accepted: 03/17/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown. METHODS We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method. FINDINGS The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms. INTERPRETATION Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively. FUNDING Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.
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Affiliation(s)
- Yun Min Song
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea; Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Jaegwon Jeong
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea
| | - Aurelio A de Los Reyes
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea; Institute of Mathematics, University of the Philippines Diliman, Quezon City, 1101, Philippines
| | - Dongju Lim
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea; Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Chul-Hyun Cho
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea
| | - Ji Won Yeom
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea
| | - Taek Lee
- Division of Computer Science and Engineering, Sun Moon University, Asan, 31460, Republic of Korea
| | - Jung-Been Lee
- Division of Computer Science and Engineering, Sun Moon University, Asan, 31460, Republic of Korea
| | - Heon-Jeong Lee
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea.
| | - Jae Kyoung Kim
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea; Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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4
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Usmani IM, Dijk DJ, Skeldon AC. Mathematical Analysis of Light-sensitivity Related Challenges in Assessment of the Intrinsic Period of the Human Circadian Pacemaker. J Biol Rhythms 2024; 39:166-182. [PMID: 38317600 PMCID: PMC10996302 DOI: 10.1177/07487304231215844] [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] [Indexed: 02/07/2024]
Abstract
Accurate assessment of the intrinsic period of the human circadian pacemaker is essential for a quantitative understanding of how our circadian rhythms are synchronized to exposure to natural and man-made light-dark (LD) cycles. The gold standard method for assessing intrinsic period in humans is forced desynchrony (FD) which assumes that the confounding effect of lights-on assessment of intrinsic period is removed by scheduling sleep-wake and associated dim LD cycles to periods outside the range of entrainment of the circadian pacemaker. However, the observation that the mean period of free-running blind people is longer than the mean period of sighted people assessed by FD (24.50 ± 0.17 h vs 24.15 ± 0.20 h, p < 0.001) appears inconsistent with this assertion. Here, we present a mathematical analysis using a simple parametric model of the circadian pacemaker with a sinusoidal velocity response curve (VRC) describing the effect of light on the speed of the oscillator. The analysis shows that the shorter period in FD may be explained by exquisite sensitivity of the human circadian pacemaker to low light intensities and a VRC with a larger advance region than delay region. The main implication of this analysis, which generates new and testable predictions, is that current quantitative models for predicting how light exposure affects entrainment of the human circadian system may not accurately capture the effect of dim light. The mathematical analysis generates new predictions which can be tested in laboratory experiments. These findings have implications for managing healthy entrainment of human circadian clocks in societies with abundant access to light sources with powerful biological effects.
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Affiliation(s)
- Imran M. Usmani
- Department of Mathematics, University of Surrey, Guildford, UK
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
- UK Dementia Research Institute Care Research & Technology Centre, Imperial College London and the University of Surrey, Guildford, UK
| | - Anne C. Skeldon
- Department of Mathematics, University of Surrey, Guildford, UK
- UK Dementia Research Institute Care Research & Technology Centre, Imperial College London and the University of Surrey, Guildford, UK
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5
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Meyer N, Lok R, Schmidt C, Kyle SD, McClung CA, Cajochen C, Scheer FAJL, Jones MW, Chellappa SL. The sleep-circadian interface: A window into mental disorders. Proc Natl Acad Sci U S A 2024; 121:e2214756121. [PMID: 38394243 PMCID: PMC10907245 DOI: 10.1073/pnas.2214756121] [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] [Indexed: 02/25/2024] Open
Abstract
Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.
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Affiliation(s)
- Nicholas Meyer
- Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, LondonWC1N 3HR, United Kingdom
- Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Renske Lok
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Christina Schmidt
- Sleep & Chronobiology Group, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology, Speech and Language, University of Liège, Liège4000, Belgium
| | - Simon D. Kyle
- Sir Jules Thorn Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, OxfordOX1 3QU, United Kingdom
| | - Colleen A. McClung
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA15219
| | - Christian Cajochen
- Centre for Chronobiology, Department for Adult Psychiatry, Psychiatric Hospital of the University of Basel, BaselCH-4002, Switzerland
- Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, BaselCH-4055, Switzerland
| | - Frank A. J. L. Scheer
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA02115
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Department of Neurology, Brigham and Women’s Hospital, Boston, MA02115
- Division of Sleep Medicine, Harvard Medical School, Boston, MA02115
| | - Matthew W. Jones
- School of Physiology, Pharmacology and Neuroscience, Faculty of Health and Life Sciences, University of Bristol, BristolBS8 1TD, United Kingdom
| | - Sarah L. Chellappa
- School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
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6
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Duraccio KM, Kamhout S, Baron KG, Reutrakul S, Depner CM. Sleep extension and cardiometabolic health: what it is, possible mechanisms and real-world applications. J Physiol 2024. [PMID: 38268197 DOI: 10.1113/jp284911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 01/08/2024] [Indexed: 01/26/2024] Open
Abstract
Short sleep duration is associated with heightened cardiometabolic disease risk and has reached epidemic proportions among children, adolescents and adults. Potential mechanisms underlying this association are complex and multifaceted, including disturbances in circadian timing, food intake and appetitive hormones, brain regions linked to control of hedonic eating, physical activity, an altered microbiome and impaired insulin sensitivity. Sleep extension, or increasing total sleep duration, is an emerging and ecologically relevant intervention with significant potential to advance our understanding of the mechanisms underlying the association between short sleep duration and the risk of cardiometabolic disease. If effective, sleep extension interventions have potential to improve cardiometabolic health across the lifespan. Existing data show that sleep extension is feasible and might have potential cardiometabolic health benefits, although there are limitations that the field must overcome. Notably, most existing studies are short term (2-8 weeks), use different sleep extension strategies, analyse a wide array of cardiometabolic health outcomes in different populations and, frequently, lack adequate statistical power, thus limiting robust scientific conclusions. Overcoming these limitations will require fully powered, randomized studies conducted in people with habitual short sleep duration and existing cardiometabolic risk factors. Additionally, randomized controlled trials comparing different sleep extension strategies are essential to determine the most effective interventions. Ongoing and future research should focus on elucidating the potential cardiometabolic health benefits of sleep extension. Such studies have high potential to generate crucial knowledge with potential to improve health and quality of life for those struggling with short sleep duration.
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Affiliation(s)
- Kara M Duraccio
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | - Sarah Kamhout
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | - Kelly G Baron
- Division of Public Health, Department of Family and Preventative Medicine, University of Utah, Salt Lake City, UT, USA
| | - Sirimon Reutrakul
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Illinois Chicago, Chicago, IL, USA
- Department of Biobehavioral Nursing Science, College of Nursing, University of Illinois Chicago, Chicago, IL, USA
| | - Christopher M Depner
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA
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7
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Goodman MO, Dashti HS, Lane JM, Windred DP, Burns A, Jones SE, Sofer T, Purcell SM, Zhu X, Ollila HM, Kyle SD, Spiegelhalder K, Peker Y, Huang T, Cain SW, Phillips AJK, Saxena R, Rutter MK, Redline S, Wang H. Causal Association Between Subtypes of Excessive Daytime Sleepiness and Risk of Cardiovascular Diseases. J Am Heart Assoc 2023; 12:e030568. [PMID: 38084713 PMCID: PMC10863774 DOI: 10.1161/jaha.122.030568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/03/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND Excessive daytime sleepiness (EDS), experienced in 10% to 20% of the population, has been associated with cardiovascular disease and death. However, the condition is heterogeneous and is prevalent in individuals having short and long sleep duration. We sought to clarify the relationship between sleep duration subtypes of EDS with cardiovascular outcomes, accounting for these subtypes. METHODS AND RESULTS We defined 3 sleep duration subtypes of excessive daytime sleepiness: normal (6-9 hours), short (<6 hours), and long (>9 hours), and compared these with a nonsleepy, normal-sleep-duration reference group. We analyzed their associations with incident myocardial infarction (MI) and stroke using medical records of 355 901 UK Biobank participants and performed 2-sample Mendelian randomization for each outcome. Compared with healthy sleep, long-sleep EDS was associated with an 83% increased rate of MI (hazard ratio, 1.83 [95% CI, 1.21-2.77]) during 8.2-year median follow-up, adjusting for multiple health and sociodemographic factors. Mendelian randomization analysis provided supporting evidence of a causal role for a genetic long-sleep EDS subtype in MI (inverse-variance weighted β=1.995, P=0.001). In contrast, we did not find evidence that other subtypes of EDS were associated with incident MI or any associations with stroke (P>0.05). CONCLUSIONS Our study suggests the previous evidence linking EDS with increased cardiovascular disease risk may be primarily driven by the effect of its long-sleep subtype on higher risk of MI. Underlying mechanisms remain to be investigated but may involve sleep irregularity and circadian disruption, suggesting a need for novel interventions in this population.
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Affiliation(s)
- Matthew O. Goodman
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Broad InstituteCambridgeMA
| | - Hassan S. Dashti
- Broad InstituteCambridgeMA
- Center for Genomic MedicineMassachusetts General Hospital and Harvard Medical SchoolBostonMA
- Department of Anesthesia, Critical Care and Pain MedicineMassachusetts General HospitalBostonMA
| | - Jacqueline M. Lane
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Broad InstituteCambridgeMA
- Center for Genomic MedicineMassachusetts General Hospital and Harvard Medical SchoolBostonMA
| | - Daniel P. Windred
- School of Psychological SciencesTurner Institute for Brain and Mental Health, Monash UniversityMelbourneVictoriaAustralia
| | - Angus Burns
- Broad InstituteCambridgeMA
- Center for Genomic MedicineMassachusetts General Hospital and Harvard Medical SchoolBostonMA
- School of Psychological SciencesTurner Institute for Brain and Mental Health, Monash UniversityMelbourneVictoriaAustralia
| | - Samuel E. Jones
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiFinland
- University of Exeter Medical SchoolExeterUnited Kingdom
| | - Tamar Sofer
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonMA
| | - Shaun M. Purcell
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Broad InstituteCambridgeMA
- Department of PsychiatryBrigham and Women’s HospitalBostonMA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health SciencesCase Western Reserve UniversityClevelandOH
| | - Hanna M. Ollila
- Broad InstituteCambridgeMA
- Center for Genomic MedicineMassachusetts General Hospital and Harvard Medical SchoolBostonMA
- Department of Anesthesia, Critical Care and Pain MedicineMassachusetts General HospitalBostonMA
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiFinland
| | - Simon D. Kyle
- Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical NeurosciencesUniversity of OxfordUnited Kingdom
| | - Kai Spiegelhalder
- Department of Psychiatry and PsychotherapyMedical Centre–University of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Yuksel Peker
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Department of Pulmonary MedicineKoç University School of MedicineIstanbulTurkey
- Sahlgrenska AcademyUniversity of GothenburgSweden
- Department of Clinical Sciences, Respiratory Medicine and Allergology, Faculty of MedicineLund UniversityLundSweden
- Division of Pulmonary, Allergy, and Critical Care MedicineUniversity of Pittsburgh School of MedicinePittsburghPA
| | - Tianyi Huang
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Channing Division of Network MedicineBrigham and Women’s Hospital, Harvard Medical SchoolBostonMA
| | - Sean W. Cain
- School of Psychological SciencesTurner Institute for Brain and Mental Health, Monash UniversityMelbourneVictoriaAustralia
| | - Andrew J. K. Phillips
- School of Psychological SciencesTurner Institute for Brain and Mental Health, Monash UniversityMelbourneVictoriaAustralia
| | - Richa Saxena
- Broad InstituteCambridgeMA
- Center for Genomic MedicineMassachusetts General Hospital and Harvard Medical SchoolBostonMA
- Department of Anesthesia, Critical Care and Pain MedicineMassachusetts General HospitalBostonMA
| | - Martin K. Rutter
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUnited Kingdom
- Diabetes, Endocrinology and Metabolism CentreManchester University NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science CentreManchesterUnited Kingdom
| | - Susan Redline
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
| | - Heming Wang
- Division of Sleep and Circadian DisordersBrigham and Women’s HospitalBostonMA
- Department of Neurology and MedicineHarvard Medical School, Brigham and Women’s HospitalBostonMA
- Broad InstituteCambridgeMA
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8
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Song YM, Choi SJ, Park SH, Lee SJ, Joo EY, Kim JK. A real-time, personalized sleep intervention using mathematical modeling and wearable devices. Sleep 2023; 46:zsad179. [PMID: 37422720 DOI: 10.1093/sleep/zsad179] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 06/03/2023] [Indexed: 07/10/2023] Open
Abstract
The prevalence of artificial light exposure has enabled us to be active any time of the day or night, leading to the need for high alertness outside of traditional daytime hours. To address this need, we developed a personalized sleep intervention framework that analyzes real-world sleep-wake patterns obtained from wearable devices to maximize alertness during specific target periods. Our framework utilizes a mathematical model that tracks the dynamic sleep pressure and circadian rhythm based on the user's sleep history. In this way, the model accurately predicts real-time alertness, even for shift workers with complex sleep and work schedules (N = 71, t = 13~21 days). This allowed us to discover a new sleep-wake pattern called the adaptive circadian split sleep, which incorporates a main sleep period and a late nap to enable high alertness during both work and non-work periods of shift workers. We further developed a mobile application that integrates this framework to recommend practical, personalized sleep schedules for individual users to maximize their alertness during a targeted activity time based on their desired sleep onset and available sleep duration. This can reduce the risk of errors for those who require high alertness during nontraditional activity times and improve the health and quality of life for those leading shift work-like lifestyles.
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Affiliation(s)
- Yun Min Song
- Department of Mathematical Sciences, KAIST, Daejeon, Republic of Korea
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon, Republic of Korea
| | - Su Jung Choi
- Graduate School of Clinical Nursing Science, Sungkyunkwan University, Seoul, Republic of Korea
| | - Se Ho Park
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon, Republic of Korea
- Department of Mathematics, University of Wisconsin-Madison, Madison, WI, USA
| | - Soo Jin Lee
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Samsung Biomedical Research Institute, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea
| | - Eun Yeon Joo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Samsung Biomedical Research Institute, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea
| | - Jae Kyoung Kim
- Department of Mathematical Sciences, KAIST, Daejeon, Republic of Korea
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon, Republic of Korea
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9
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Cui S, Lin Q, Gui Y, Zhang Y, Lu H, Zhao H, Wang X, Li X, Jiang F. CARE as a wearable derived feature linking circadian amplitude to human cognitive functions. NPJ Digit Med 2023; 6:123. [PMID: 37433859 DOI: 10.1038/s41746-023-00865-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 06/26/2023] [Indexed: 07/13/2023] Open
Abstract
Circadian rhythms are crucial for regulating physiological and behavioral processes. Pineal hormone melatonin is often used to measure circadian amplitude but its collection is costly and time-consuming. Wearable activity data are promising alternative, but the most commonly used measure, relative amplitude, is subject to behavioral masking. In this study, we firstly derive a feature named circadian activity rhythm energy (CARE) to better characterize circadian amplitude and validate CARE by correlating it with melatonin amplitude (Pearson's r = 0.46, P = 0.007) among 33 healthy participants. Then we investigate its association with cognitive functions in an adolescent dataset (Chinese SCHEDULE-A, n = 1703) and an adult dataset (UK Biobank, n = 92,202), and find that CARE is significantly associated with Global Executive Composite (β = 30.86, P = 0.016) in adolescents, and reasoning ability, short-term memory, and prospective memory (OR = 0.01, 3.42, and 11.47 respectively, all P < 0.001) in adults. Finally, we identify one genetic locus with 126 CARE-associated SNPs using the genome-wide association study, of which 109 variants are used as instrumental variables in the Mendelian Randomization analysis, and the results show a significant causal effect of CARE on reasoning ability, short-term memory, and prospective memory (β = -59.91, 7.94, and 16.85 respectively, all P < 0.0001). The present study suggests that CARE is an effective wearable-based metric of circadian amplitude with a strong genetic basis and clinical significance, and its adoption can facilitate future circadian studies and potential intervention strategies to improve circadian rhythms and cognitive functions.
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Affiliation(s)
- Shuya Cui
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qingmin Lin
- Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yuanyuan Gui
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yunting Zhang
- Developmental and Behavioral Pediatrics, Child Health Advocacy Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hui Lu
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hongyu Zhao
- Department of Biostatistics, Yale University, New Haven, CT, USA
| | - Xiaolei Wang
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
- SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Xinyue Li
- School of Data Science, City University of Hong Kong, Hong Kong SAR, China.
| | - Fan Jiang
- Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
- MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
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10
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Baum L, Johns M, Poikela M, Möller R, Ananthasubramaniam B, Prasser F. Data integration and analysis for circadian medicine. Acta Physiol (Oxf) 2023; 237:e13951. [PMID: 36790321 DOI: 10.1111/apha.13951] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 02/04/2023] [Accepted: 02/12/2023] [Indexed: 02/16/2023]
Abstract
Data integration, data sharing, and standardized analyses are important enablers for data-driven medical research. Circadian medicine is an emerging field with a particularly high need for coordinated and systematic collaboration between researchers from different disciplines. Datasets in circadian medicine are multimodal, ranging from molecular circadian profiles and clinical parameters to physiological measurements and data obtained from (wearable) sensors or reported by patients. Uniquely, data spanning both the time dimension and the spatial dimension (across tissues) are needed to obtain a holistic view of the circadian system. The study of human rhythms in the context of circadian medicine has to confront the heterogeneity of clock properties within and across subjects and our inability to repeatedly obtain relevant biosamples from one subject. This requires informatics solutions for integrating and visualizing relevant data types at various temporal resolutions ranging from milliseconds and seconds to minutes and several hours. Associated challenges range from a lack of standards that can be used to represent all required data in a common interoperable form, to challenges related to data storage, to the need to perform transformations for integrated visualizations, and to privacy issues. The downstream analysis of circadian rhythms requires specialized approaches for the identification, characterization, and discrimination of rhythms. We conclude that circadian medicine research provides an ideal environment for developing innovative methods to address challenges related to the collection, integration, visualization, and analysis of multimodal multidimensional biomedical data.
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Affiliation(s)
- Lena Baum
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Marco Johns
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Maija Poikela
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ralf Möller
- Institute of Information Systems, University of Lübeck, Lübeck, Germany
| | | | - Fabian Prasser
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
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11
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Moreno JP, Hannay KM, Goetz AR, Walch O, Cheng P. Validation of the Entrainment Signal Regularity Index and associations with children's changes in BMI. Obesity (Silver Spring) 2023; 31:642-651. [PMID: 36628610 PMCID: PMC9975028 DOI: 10.1002/oby.23641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 10/12/2022] [Accepted: 10/30/2022] [Indexed: 01/12/2023]
Abstract
OBJECTIVE This study examined the validity of a novel metric of circadian health, the Entrainment Signal Regularity Index (ESRI), and its relationship to changes in BMI during the school year and summer. METHODS In a longitudinal observational data set, this study examined the relationship between ESRI score and children's (n = 119, 5- to 8-year-olds) sleep and physical activity levels during the school year and summer, differences in ESRI score during the school year and summer, and the association of ESRI score during the school year and summer with changes in BMI across those time periods. RESULTS The ESRI score was higher during the school year (0.70 ± 0.10) compared with summer (0.63 ± 0.11); t(111) = 5.484, p < 0.001. Whereas the ESRI score at the beginning of the school year did not significantly predict BMI change during the school year (β = 0.05 ± 0.09 SE, p = 0.57), having a higher ESRI score during summer predicted smaller increases in BMI during summer (β = -0.22 ± 0.10 SE, p = 0.03). CONCLUSIONS Overall, children demonstrated higher entrainment regularity during the school year compared with the summer. During summer, having a higher entrainment signal was associated with smaller changes in summertime BMI. This effect was independent of the effects of children's sleep midpoint, sleep regularity, and physical activity on children's BMI.
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Affiliation(s)
- Jennette P. Moreno
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Kevin M. Hannay
- Department of Mathematics, University of Michigan, Ann Arbor, MI, USA
- Arcascope; Chantilly, VA, USA
| | - Amy R. Goetz
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Olivia Walch
- Arcascope; Chantilly, VA, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Philip Cheng
- Sleep Disorders and Research Center, Henry Ford Health, Detroit, MI, USA
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12
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Zhou SJ, Yang R, Wang LL, Qi M, Yuan XF, Wang TT, Song TH, Zhuang YY, Li HJ, Tan YL, Wang X, Chen JX. Measuring Sleep Stages and Screening for Obstructive Sleep Apnea with a Wearable Multi-Sensor System in Comparison to Polysomnography. Nat Sci Sleep 2023; 15:353-362. [PMID: 37193215 PMCID: PMC10182819 DOI: 10.2147/nss.s406359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 05/04/2023] [Indexed: 05/18/2023] Open
Abstract
Objective To assess the performance of a wearable multi-sensor system (SensEcho) in comparison to polysomnography (PSG) in measuring sleep stages and searching for obstructive sleep apnea (OSA). Methods Participants underwent overnight simultaneous monitoring using SensEcho and PSG in a sleep laboratory. SensEcho analyzed the recordings spontaneously, and PSG was assessed as per standard guidelines. The degree of snoring was evaluated according to the guidelines for the diagnosis and treatment of OSA hypopnea syndrome (2011 revision). The Epworth Sleepiness Scale (ESS) was used to assess general daytime sleepiness. Results This study included 103 Han Chinese, 91 of whom (age 39.02 ± 13.84 years, body mass index 27.28 ± 5.12 kg/m2, 61.54% male) completed the assessments. The measures of total sleep time (P = 0.198); total wake time (P = 0.182); shallow sleep (P = 0.297), deep sleep (P = 0.422), rapid eye movement sleep (P = 0.570), and awake (P = 0.336) proportions were similar between SensEcho and PSG. Using an apnea-hypopnea index (AHI) cutoff of ≥ 5 events/h, the SensEcho had 82.69% sensitivity and 89.74% specificity. Almost the same results were obtained at an AHI threshold of ≥ 15 events/h. Although the specificity increased to 94.67%, it decreased to 43.75% at an AHI cutoff of ≥ 30 events/h. Conclusion This study demonstrated that SensEcho can be used to evaluate sleep status and screen for OSA. Nevertheless, improving the accuracy of its assessment of severe OSA and further testing its effectiveness in community and home environments is necessary.
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Affiliation(s)
- Shuang-Jiang Zhou
- Sleep Medicine Center, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, People’s Republic of China
| | - Rui Yang
- Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Lei-Lei Wang
- Sleep Medicine Center, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, People’s Republic of China
| | - Meng Qi
- Sleep Medicine Center, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, People’s Republic of China
| | - Xiao-Fei Yuan
- Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Ting-Ting Wang
- School of Mental Health, Bengbu Medical College, Bengbu, People’s Republic of China
| | - Tian-He Song
- Department of Psychology, Chengde Medical University, Chengde, People’s Republic of China
| | - Yun-Yue Zhuang
- Department of Psychology, Chengde Medical University, Chengde, People’s Republic of China
| | - Hong-Juan Li
- Sleep Medicine Center, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, People’s Republic of China
| | - Yun-Long Tan
- Sleep Medicine Center, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, People’s Republic of China
| | - Xue Wang
- Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Correspondence: Xue Wang, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People’s Republic of China, Tel +86-10-58303034, Email
| | - Jing-Xu Chen
- Sleep Medicine Center, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, People’s Republic of China
- Jing-Xu Chen, Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, People’s Republic of China, Tel +86-10-83024278, Email
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13
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Chinoy ED, Cuellar JA, Jameson JT, Markwald RR. Daytime Sleep-Tracking Performance of Four Commercial Wearable Devices During Unrestricted Home Sleep. Nat Sci Sleep 2023; 15:151-164. [PMID: 37032817 PMCID: PMC10075216 DOI: 10.2147/nss.s395732] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/20/2023] [Indexed: 04/11/2023] Open
Abstract
Purpose Previous studies have found that many commercial wearable devices can accurately track sleep-wake patterns in laboratory or home settings. However, nearly all previous studies tested devices under conditions with fixed time in bed (TIB) and during nighttime sleep episodes only. Despite its relevance to shift workers and others with irregular sleep schedules, it is largely unknown how devices track daytime sleep. Therefore, we tested the sleep-tracking performance of four commercial wearable devices during unrestricted home daytime sleep. Participants and Methods Participants were 16 healthy young adults (6 men, 10 women; 26.6 ± 4.6 years, mean ± SD) with habitual daytime sleep schedules. Participants slept at home for 1 week under unrestricted conditions (ie, self-selecting TIB) using a set of four commercial wearable devices and completed reference sleep logs. Wearables included the Fatigue Science ReadiBand, Fitbit Inspire HR, Oura Ring, and Polar Vantage V Titan. Daytime sleep episode TIB biases and frequencies of missed and false-positive daytime sleep episodes were examined. Results TIB bias was low in general for all devices on most daytime sleep episodes, but some exhibited large biases (eg, >1 h). Total missed daytime sleep episodes were as follows: Fatigue Science: 3.6%; Fitbit: 4.8%; Oura: 6.0%; Polar: 37.3%. Missed episodes occurred most often when TIB was short (eg, naps <4 h). Conclusion When daytime sleep episodes were recorded, the devices generally exhibited similar performance for tracking TIB (ie, most episodes had low bias). However, the devices failed to detect some daytime episodes, which occurred most often when TIB was short, but varied across devices (especially Polar, which missed over one-third of episodes). Findings suggest that accurate daytime sleep tracking is largely achievable with commercial wearable devices. However, performance differences for missed recordings suggest that some devices vary in reliability (especially for naps), but improvements could likely be made with changes to algorithm sensitivities.
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Affiliation(s)
- Evan D Chinoy
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Joseph A Cuellar
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Jason T Jameson
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Rachel R Markwald
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
- Correspondence: Rachel R Markwald, Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, 140 Sylvester Road, San Diego, CA, 92106, USA, Tel +1 619 767 4494, Email
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14
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Ike CO, Wen JT, Oishi MM, Brown LK, Agung Julius A. Fast tuning of observer-based circadian phase estimator using biometric data. Heliyon 2022; 8:e12500. [PMID: 36636209 PMCID: PMC9830155 DOI: 10.1016/j.heliyon.2022.e12500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 09/26/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
Circadian rhythms play a vital role in maintaining an individual's well-being, and they have been shown to be the product of the master oscillator in the suprachiasmatic nuclei (SCN) located in the brain. The SCN however, is inaccessible for assessment, so existing standards for circadian phase estimation often focus on the use of indirect measurements as proxies for the circadian state. These methods often suffer from severe delays due to invasive methods of sample collection, making online estimation impossible. In this paper, we propose a linear state observer as an elegant solution for continuous phase estimation. This observer-based filter is used in isolating the frequency components of input biometric signals, which are then taken to be the circadian state. We start the design process by fixing the observer's oscillatory frequency at 24 hours, and then we tune its gains using an evolutionary optimization algorithm to extract the target components from individuals' data. The resulting filter was able to provide phase estimates with an average absolute error within 1.5 hours on all test subjects, given their minute-to-minute actigraphy data collected in ambulatory conditions.
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Affiliation(s)
- Chukwuemeka O. Ike
- Lighting Enabled Systems and Applications (LESA) Engineering Research Center, Troy, NY, United States,Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States,Corresponding author at: Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States.
| | - John T. Wen
- Lighting Enabled Systems and Applications (LESA) Engineering Research Center, Troy, NY, United States,Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States
| | - Meeko M.K. Oishi
- Department of Internal Medicine and School of Engineering, University of New Mexico, Albuquerque, NM, United States
| | - Lee K. Brown
- Department of Internal Medicine and School of Engineering, University of New Mexico, Albuquerque, NM, United States
| | - A. Agung Julius
- Lighting Enabled Systems and Applications (LESA) Engineering Research Center, Troy, NY, United States,Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States
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15
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Porosnicu Rodriguez KA, Salas RME, Schneider L. Insomnia. Neurol Clin 2022; 41:1-19. [DOI: 10.1016/j.ncl.2022.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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16
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Meyer N, Harvey AG, Lockley SW, Dijk DJ. Circadian rhythms and disorders of the timing of sleep. Lancet 2022; 400:1061-1078. [PMID: 36115370 DOI: 10.1016/s0140-6736(22)00877-7] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 03/20/2022] [Accepted: 05/05/2022] [Indexed: 02/06/2023]
Abstract
The daily alternation between sleep and wakefulness is one of the most dominant features of our lives and is a manifestation of the intrinsic 24 h rhythmicity underlying almost every aspect of our physiology. Circadian rhythms are generated by networks of molecular oscillators in the brain and peripheral tissues that interact with environmental and behavioural cycles to promote the occurrence of sleep during the environmental night. This alignment is often disturbed, however, by contemporary changes to our living environments, work or social schedules, patterns of light exposure, and biological factors, with consequences not only for sleep timing but also for our physical and mental health. Characterised by undesirable or irregular timing of sleep and wakefulness, in this Series paper we critically examine the existing categories of circadian rhythm sleep-wake disorders and the role of the circadian system in their development. We emphasise how not all disruption to daily rhythms is driven solely by an underlying circadian disturbance, and take a broader, dimensional approach to explore how circadian rhythms and sleep homoeostasis interact with behavioural and environmental factors. Very few high-quality epidemiological and intervention studies exist, and wider recognition and treatment of sleep timing disorders are currently hindered by a scarcity of accessible and objective tools for quantifying sleep and circadian physiology and environmental variables. We therefore assess emerging wearable technology, transcriptomics, and mathematical modelling approaches that promise to accelerate the integration of our knowledge in sleep and circadian science into improved human health.
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Affiliation(s)
- Nicholas Meyer
- Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, London, UK; Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, UK
| | - Allison G Harvey
- Department of Psychology, University of California, Berkeley, CA, USA
| | - Steven W Lockley
- Division of Sleep and Circadian Disorders, Department of Medicine and Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA; Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, UK.
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17
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Moreno JP, Hannay KM, Walch O, Dadabhoy H, Christian J, Puyau M, El-Mubasher A, Bacha F, Grant SR, Park RJ, Cheng P. Estimating circadian phase in elementary school children: leveraging advances in physiologically informed models of circadian entrainment and wearable devices. Sleep 2022; 45:6547079. [PMID: 35275213 PMCID: PMC9189953 DOI: 10.1093/sleep/zsac061] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 03/02/2022] [Indexed: 11/12/2022] Open
Abstract
STUDY OBJECTIVES Examine the ability of a physiologically based mathematical model of human circadian rhythms to predict circadian phase, as measured by salivary dim light melatonin onset (DLMO), in children compared to other proxy measurements of circadian phase (bedtime, sleep midpoint, and wake time). METHODS As part of an ongoing clinical trial, a sample of 29 elementary school children (mean age: 7.4 ± .97 years) completed 7 days of wrist actigraphy before a lab visit to assess DLMO. Hourly salivary melatonin samples were collected under dim light conditions (<5 lx). Data from actigraphy were used to generate predictions of circadian phase using both a physiologically based circadian limit cycle oscillator mathematical model (Hannay model), and published regression equations that utilize average sleep onset, midpoint, and offset to predict DLMO. Agreement of proxy predictions with measured DLMO were assessed and compared. RESULTS DLMO predictions using the Hannay model outperformed DLMO predictions based on children's sleep/wake parameters with a Lin's Concordance Correlation Coefficient (LinCCC) of 0.79 compared to 0.41-0.59 for sleep/wake parameters. The mean absolute error was 31 min for the Hannay model compared to 35-38 min for the sleep/wake variables. CONCLUSION Our findings suggest that sleep/wake behaviors were weak proxies of DLMO phase in children, but mathematical models using data collected from wearable data can be used to improve the accuracy of those predictions. Additional research is needed to better adapt these adult models for use in children. CLINICAL TRIAL The i Heart Rhythm Project: Healthy Sleep and Behavioral Rhythms for Obesity Prevention https://clinicaltrials.gov/ct2/show/NCT04445740.
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Affiliation(s)
- Jennette P Moreno
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Kevin M Hannay
- Department of Mathematics, University of Michigan, Ann Arbor, MI, USA.,Arcascope Inc., Chantilly, VA, USA
| | - Olivia Walch
- Arcascope Inc., Chantilly, VA, USA.,Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Hafza Dadabhoy
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Jessica Christian
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Maurice Puyau
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Abeer El-Mubasher
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Fida Bacha
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Sarah R Grant
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Rebekah Julie Park
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Philip Cheng
- Thomas Roth Sleep Disorders and Research Center, Henry Ford Health System, Detroit, MI, USA
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18
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Beyond the limits of circadian entrainment: Non-24-hour sleep-wake disorder, shift work, and social jet lag. J Theor Biol 2022; 545:111148. [PMID: 35513166 DOI: 10.1016/j.jtbi.2022.111148] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 04/11/2022] [Accepted: 04/21/2022] [Indexed: 01/07/2023]
Abstract
While the vast majority of humans are able to entrain their circadian rhythm to the 24-hour light-dark cycle, there are numerous individuals who are not able to do so due to disease or societal reasons. We use computational and mathematical methods to analyze a well-established model of human circadian rhythms to address cases where individuals do not entrain to the 24-hour light-dark cycle, leading to misalignment of their circadian phase. For each case, we provide a mathematically justified strategy for how to minimize circadian misalignment. In the case of non-24-hour sleep-wake disorder, we show why appropriately timed bright light therapy induces entrainment. With regard to shift work, we explain why reentrainment times following transitions between day and night shifts are asymmetric, and how higher light intensity enables unusually rapid reentrainment after certain transitions. Finally, with regard to teenagers who engage in compensatory catch-up sleep on weekends, we propose a rule of thumb for sleep and wake onset times that minimizes circadian misalignment due to this type of social jet lag. In all cases, the primary mathematical approach involves understanding the dynamics of entrainment maps that measure the phase of the entrained rhythm with respect to the daily onset of lights.
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19
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Cheng WJ, Hang LW, Kubo T, Vanttola P, Huang SC. Impact of sleep timing on attention, sleepiness, and sleep quality among real-life night shift workers with shift work disorder: a cross-over clinical trial. Sleep 2022; 45:6527235. [PMID: 35148396 DOI: 10.1093/sleep/zsac034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 12/10/2021] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVES To examine the effect of sleep timing intervention on sleep quality, attention, and sleepiness at work among night shift workers with shift work disorder. METHODS We recruited 60 real-life night shift workers through advertisements to participate this cross-over clinical trial. Shift work disorder was confirmed with interview and sleep log. Participants were designated to follow evening sleep (15:00-23:00) and morning sleep (09:00-17:00) schedules in a randomized order. Chronotype was confirmed by the Munich Chronotype Questionnaire. Sleep behaviors and light exposure were recorded using actigraphy. Outcome measures were sleepiness evaluated by the Karolinska Sleepiness Scale, sleep quality evaluated by the Pittsburgh Sleep Quality Index, and attention performance assessed with psychomotor vigilance test. Differences in outcome between the morning and evening sleep schedules were compared using repeated measures ANOVA. RESULTS The participants slept for longer durations during evening sleep schedules compared with morning sleep schedules. Lower sleepiness scores, higher sleep quality, and shorter reaction times and less lapse numbers in the psychomotor vigilance test were observed for participants during evening sleep schedules than morning sleep schedules after adjustment for light exposure and sleep duration. Significant interaction effects were observed for reaction time and lapse number between chronotype and sleep schedule, where the differences between sleep schedules were most prominent among those with late chronotypes. CONCLUSIONS It is recommended that night shift workers with shift work disorder arrange to sleep in the evening instead of the morning for better sleep and attention performance, especially those with late chronotypes. TRIAL REGISTRATION Sleep Schedule Intervention Study Among Night Shift Workers, https://clinicaltrials.gov/ct2/show/NCT04160572, ClinicalTrials.gov Identifier: NTC04160572.
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Affiliation(s)
- Wan-Ju Cheng
- Department of Psychiatry, China Medical University Hospital, Taichung, Taiwan.,Department of Public Health, China Medical University, Taichung, Taiwan.,Center for Durg Abuse and Addiction, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Liang-Wen Hang
- Department of Pulmonary and Critical Care Medicine, Sleep Medicine Center, China Medical University Hospital, Taichung, Taiwan.,Department of Respiratory Therapy, College of Health Care, China Medical University, Taichung, Taiwan
| | - Tomohide Kubo
- National Institute of Occupational Safety and Health, Kawasaki, Japan
| | - Päivi Vanttola
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Sheng-Che Huang
- Department of Public Health, China Medical University, Taichung, Taiwan
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20
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Parveen N, Parganiha A. Consequences and factors associated with OSA: a brief review. BIOL RHYTHM RES 2022. [DOI: 10.1080/09291016.2022.2054558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Affiliation(s)
- Noorshama Parveen
- School of Studies in Life Science, Pandit Ravishankar Shukla University, Raipur, India
| | - Arti Parganiha
- School of Studies in Life Science, Pandit Ravishankar Shukla University, Raipur, India
- Center for Translational Chronobiology, Pandit Ravishankar Shukla University, Raipur, India
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21
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St. Hilaire MA. Modeling (circadian). PROGRESS IN BRAIN RESEARCH 2022; 273:181-198. [DOI: 10.1016/bs.pbr.2022.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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22
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Basner M, Smith MG, McCauley P, Van Dongen HPA. Seasonal night-work with extended hours and transmeridian travel: An analysis of global fatigue-related sleigh crash risk. Sleep Health 2021; 8:3-6. [PMID: 34920975 DOI: 10.1016/j.sleh.2021.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Mathias Basner
- Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
| | - Michael G Smith
- Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Peter McCauley
- Sleep and Performance Research Center, Washington State University, Spokane, Washington, USA
| | - Hans P A Van Dongen
- Sleep and Performance Research Center, Washington State University, Spokane, Washington, USA; Elson S. Floyd College of Medicine, Washington State University, Spokane, Washington, USA
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23
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Lujan MR, Perez-Pozuelo I, Grandner MA. Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms. Front Digit Health 2021; 3:721919. [PMID: 34713186 PMCID: PMC8521807 DOI: 10.3389/fdgth.2021.721919] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 07/20/2021] [Indexed: 12/23/2022] Open
Abstract
Movement-based sleep-wake detection devices (i.e., actigraphy devices) were first developed in the early 1970s and have repeatedly been validated against polysomnography, which is considered the “gold-standard” of sleep measurement. Indeed, they have become important tools for objectively inferring sleep in free-living conditions. Standard actigraphy devices are rooted in accelerometry to measure movement and make predictions, via scoring algorithms, as to whether the wearer is in a state of wakefulness or sleep. Two important developments have become incorporated in newer devices. First, additional sensors, including measures of heart rate and heart rate variability and higher resolution movement sensing through triaxial accelerometers, have been introduced to improve upon traditional, movement-based scoring algorithms. Second, these devices have transcended scientific utility and are now being manufactured and distributed to the general public. This review will provide an overview of: (1) the history of actigraphic sleep measurement, (2) the physiological underpinnings of heart rate and heart rate variability measurement in wearables, (3) the refinement and validation of both standard actigraphy and newer, multisensory devices for real-world sleep-wake detection, (4) the practical applications of actigraphy, (5) important limitations of actigraphic measurement, and lastly (6) future directions within the field.
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Affiliation(s)
- Matthew R Lujan
- Sleep and Health Research Program, Department of Psychiatry, University of Arizona College of Medicine, Tucson, AZ, United States
| | - Ignacio Perez-Pozuelo
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.,Department of Medicine, The Alan Turing Institute, London, United Kingdom
| | - Michael A Grandner
- Sleep and Health Research Program, Department of Psychiatry, University of Arizona College of Medicine, Tucson, AZ, United States
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Abstract
Wearable technology has a history in sleep research dating back to the 1970s. Because modern wearable technology is relatively cheap and widely used by the general population, this represents an opportunity to leverage wearable devices to advance sleep medicine and research. However, there is a lack of published validation studies designed to quantify device performance against accepted gold standards, especially across different populations. Recommendations for conducting performance assessments and using wearable devices are now published with the goal of standardizing wearable device implementation and advancing the field.
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25
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Lechat B, Scott H, Naik G, Hansen K, Nguyen DP, Vakulin A, Catcheside P, Eckert DJ. New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences. Front Neurosci 2021; 15:751730. [PMID: 34690688 PMCID: PMC8530106 DOI: 10.3389/fnins.2021.751730] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 09/16/2021] [Indexed: 01/07/2023] Open
Abstract
Current approaches to quantify and diagnose sleep disorders and circadian rhythm disruption are imprecise, laborious, and often do not relate well to key clinical and health outcomes. Newer emerging approaches that aim to overcome the practical and technical constraints of current sleep metrics have considerable potential to better explain sleep disorder pathophysiology and thus to more precisely align diagnostic, treatment and management approaches to underlying pathology. These include more fine-grained and continuous EEG signal feature detection and novel oxygenation metrics to better encapsulate hypoxia duration, frequency, and magnitude readily possible via more advanced data acquisition and scoring algorithm approaches. Recent technological advances may also soon facilitate simple assessment of circadian rhythm physiology at home to enable sleep disorder diagnostics even for “non-circadian rhythm” sleep disorders, such as chronic insomnia and sleep apnea, which in many cases also include a circadian disruption component. Bringing these novel approaches into the clinic and the home settings should be a priority for the field. Modern sleep tracking technology can also further facilitate the transition of sleep diagnostics from the laboratory to the home, where environmental factors such as noise and light could usefully inform clinical decision-making. The “endpoint” of these new and emerging assessments will be better targeted therapies that directly address underlying sleep disorder pathophysiology via an individualized, precision medicine approach. This review outlines the current state-of-the-art in sleep and circadian monitoring and diagnostics and covers several new and emerging approaches to better define sleep disruption and its consequences.
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Affiliation(s)
- Bastien Lechat
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Hannah Scott
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Ganesh Naik
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Kristy Hansen
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Duc Phuc Nguyen
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Andrew Vakulin
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Peter Catcheside
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
| | - Danny J Eckert
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, SA, Australia
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26
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Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness. iScience 2021; 24:103129. [PMID: 34622173 PMCID: PMC8479255 DOI: 10.1016/j.isci.2021.103129] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 08/09/2021] [Accepted: 09/10/2021] [Indexed: 11/29/2022] Open
Abstract
Shift workers and many other groups experience irregular sleep-wake patterns. This can induce excessive daytime sleepiness that decreases productivity and elevates the risk of accidents. However, the degree of daytime sleepiness is not correlated with standard sleep parameters like total sleep time, suggesting other factors are involved. Here, we analyze real-world sleep-wake patterns of shift workers measured with wearables by developing a computational package that simulates homeostatic sleep pressure – physiological need for sleep – and the circadian rhythm. This reveals that shift workers who align sleep-wake patterns with their circadian rhythm have lower daytime sleepiness, even if they sleep less. The alignment, quantified by the sleep parameter, circadian sleep sufficiency, can be increased by dynamically adjusting daily sleep durations according to varying bedtimes. Our computational package provides flexible and personalized real-time sleep-wake patterns for individuals to reduce their daytime sleepiness and could be used with wearables to develop smart alarms. Sleep-wake patterns measured by wearables are analyzed with a mathematical model A new sleep parameter CSS measures the circadian alignment of sleep-wake patterns Sleep-wake patterns more aligned with circadian rhythm decrease daytime sleepiness Our computational package calculates the CSS to provide personalized sleep schedules
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27
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Soreca I. The role of circadian rhythms in Obstructive Sleep Apnea symptoms and novel targets for treatment. Chronobiol Int 2021; 38:1274-1282. [PMID: 34027758 DOI: 10.1080/07420528.2021.1929281] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 04/09/2021] [Accepted: 05/09/2021] [Indexed: 10/21/2022]
Abstract
Obstructive Sleep Apnea (OSA) is a common disorder that is associated with disability, premature mortality and lost quality of life. Excessive daytime sleepiness and depressive symptoms confer a great portion of the disability and lost quality of life associated with the disorder. While showing robust rates of response and symptoms resolutions, current treatments aimed at correcting the respiratory disturbances are not universally successful and a non-negligible proportion of patients who are correctly using available therapies do not experience symptomatic relief, suggesting that mechanisms beyond the respiratory disturbances may be involved in the pathogenesis of symptoms. A growing body of literature concerning animal and human models suggests that the sleep and respiratory disturbances commonly seen in OSA, namely sleep fragmentation, partial sleep deprivation, intermittent hypoxia, can promote shifts in circadian rhythms ultimately leading to misalignment between sleep-wake rhythms and the internal clock, as well as desynchrony amongst peripheral clocks and peripheral and central clock. This manuscript reviews the current evidence in support of a circadian disturbance underlying OSA symptomatology and proposes new applications for existing chronotherapeutic interventions with the potential for improving symptoms and quality of life for those patients that do not find symptomatic relief with currently available treatments.
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Affiliation(s)
- Isabella Soreca
- Department of Sleep Medicine, Mental Illness Research, Clinical, Education Centers of Excellence (MIRECC), VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
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28
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Cogswell D, Bisesi P, Markwald RR, Cruickshank-Quinn C, Quinn K, McHill A, Melanson EL, Reisdorph N, Wright KP, Depner CM. Identification of a Preliminary Plasma Metabolome-based Biomarker for Circadian Phase in Humans. J Biol Rhythms 2021; 36:369-383. [PMID: 34182829 PMCID: PMC9134127 DOI: 10.1177/07487304211025402] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Measuring individual circadian phase is important to diagnose and treat circadian rhythm sleep-wake disorders and circadian misalignment, inform chronotherapy, and advance circadian science. Initial findings using blood transcriptomics to predict the circadian phase marker dim-light melatonin onset (DLMO) show promise. Alternatively, there are limited attempts using metabolomics to predict DLMO and no known omics-based biomarkers predict dim-light melatonin offset (DLMOff). We analyzed the human plasma metabolome during adequate and insufficient sleep to predict DLMO and DLMOff using one blood sample. Sixteen (8 male/8 female) healthy participants aged 22.4 ± 4.8 years (mean ± SD) completed an in-laboratory study with 3 baseline days (9 h sleep opportunity/night), followed by a randomized cross-over protocol with 9-h adequate sleep and 5-h insufficient sleep conditions, each lasting 5 days. Blood was collected hourly during the final 24 h of each condition to independently determine DLMO and DLMOff. Blood samples collected every 4 h were analyzed by untargeted metabolomics and were randomly split into training (68%) and test (32%) sets for biomarker analyses. DLMO and DLMOff biomarker models were developed using partial least squares regression in the training set followed by performance assessments using the test set. At baseline, the DLMOff model showed the highest performance (0.91 R2 and 1.1 ± 1.1 h median absolute error ± interquartile range [MdAE ± IQR]), with significantly (p < 0.01) lower prediction error versus the DLMO model. When all conditions (baseline, 9 h, and 5 h) were included in performance analyses, the DLMO (0.60 R2; 2.2 ± 2.8 h MdAE; 44% of the samples with an error under 2 h) and DLMOff (0.62 R2; 1.8 ± 2.6 h MdAE; 51% of the samples with an error under 2 h) models were not statistically different. These findings show promise for metabolomics-based biomarkers of circadian phase and highlight the need to test biomarkers that predict multiple circadian phase markers under different physiological conditions.
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Affiliation(s)
- D Cogswell
- Sleep and Chronobiology Laboratory, University of Colorado, Boulder, Boulder, Colorado
| | - P Bisesi
- Sleep and Chronobiology Laboratory, University of Colorado, Boulder, Boulder, Colorado
| | - R R Markwald
- Sleep and Chronobiology Laboratory, University of Colorado, Boulder, Boulder, Colorado
| | - C Cruickshank-Quinn
- Department of Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - K Quinn
- Department of Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - A McHill
- Sleep and Chronobiology Laboratory, University of Colorado, Boulder, Boulder, Colorado
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon
| | - E L Melanson
- Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- Division of Geriatric Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- Eastern Colorado Veterans Affairs Geriatric Research, Education, and Clinical Center, Denver, Colorado
| | - N Reisdorph
- Department of Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - K P Wright
- Sleep and Chronobiology Laboratory, University of Colorado, Boulder, Boulder, Colorado
- Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - C M Depner
- Sleep and Chronobiology Laboratory, University of Colorado, Boulder, Boulder, Colorado
- Department of Health and Kinesiology, The University of Utah, Salt Lake City, Utah
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29
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Duffy JF, Abbott SM, Burgess HJ, Crowley SJ, Emens JS, Epstein LJ, Gamble KL, Hasler BP, Kristo DA, Malkani RG, Rahman SA, Thomas SJ, Wyatt JK, Zee PC, Klerman EB. Workshop report. Circadian rhythm sleep-wake disorders: gaps and opportunities. Sleep 2021; 44:zsaa281. [PMID: 33582815 PMCID: PMC8120340 DOI: 10.1093/sleep/zsaa281] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 10/02/2020] [Indexed: 01/09/2023] Open
Abstract
This White Paper presents the results from a workshop cosponsored by the Sleep Research Society (SRS) and the Society for Research on Biological Rhythms (SRBR) whose goals were to bring together sleep clinicians and sleep and circadian rhythm researchers to identify existing gaps in diagnosis and treatment and areas of high-priority research in circadian rhythm sleep-wake disorders (CRSWD). CRSWD are a distinct class of sleep disorders caused by alterations of the circadian time-keeping system, its entrainment mechanisms, or a misalignment of the endogenous circadian rhythm and the external environment. In these disorders, the timing of the primary sleep episode is either earlier or later than desired, irregular from day-to-day, and/or sleep occurs at the wrong circadian time. While there are incomplete and insufficient prevalence data, CRSWD likely affect at least 800,000 and perhaps as many as 3 million individuals in the United States, and if Shift Work Disorder and Jet Lag are included, then many millions more are impacted. The SRS Advocacy Taskforce has identified CRSWD as a class of sleep disorders for which additional high-quality research could have a significant impact to improve patient care. Participants were selected for their expertise and were assigned to one of three working groups: Phase Disorders, Entrainment Disorders, and Other. Each working group presented a summary of the current state of the science for their specific CRSWD area, followed by discussion from all participants. The outcome of those presentations and discussions are presented here.
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Affiliation(s)
- Jeanne F Duffy
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Sabra M Abbott
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Helen J Burgess
- Department of Psychiatry, University of Michigan, Ann Arbor, MI
| | - Stephanie J Crowley
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL
| | - Jonathan S Emens
- Department of Psychiatry, Oregon Health & Science University, Portland, OR
| | - Lawrence J Epstein
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Karen L Gamble
- Department of Psychiatry University of Alabama at Birmingham, Birmingham, AL
| | - Brant P Hasler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - David A Kristo
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Roneil G Malkani
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Shadab A Rahman
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - S Justin Thomas
- Department of Psychiatry University of Alabama at Birmingham, Birmingham, AL
| | - James K Wyatt
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL
| | - Phyllis C Zee
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Elizabeth B Klerman
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
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30
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Swanson GR, Kochman N, Amin J, Chouhan V, Yim W, Engen PA, Shaikh M, Naqib A, Tran L, Voigt RM, Forsyth CB, Green SJ, Keshavarzian A. Disrupted Circadian Rest-Activity Cycles in Inflammatory Bowel Disease Are Associated With Aggressive Disease Phenotype, Subclinical Inflammation, and Dysbiosis. Front Med (Lausanne) 2021; 8:770491. [PMID: 35265631 PMCID: PMC8900134 DOI: 10.3389/fmed.2021.770491] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/08/2021] [Indexed: 12/11/2022] Open
Abstract
Patients with inflammatory bowel disease (IBD)-Crohn's disease (CD), and ulcerative colitis (UC), have poor sleep quality. Sleep and multiple immunologic and gastrointestinal processes in the body are orchestrated by the circadian clock, and we recently reported that a later category or chronotype of the circadian clock was associated with worse IBD specific outcomes. The goal of this study was to determine if circadian misalignment by rest-activity cycles is associated with markers of aggressive disease, subclinical inflammation, and dysbiosis in IBD. A total of 42 patients with inactive but biopsy-proven CD or UC and 10 healthy controls participated in this prospective cohort study. Subjects were defined as having an aggressive IBD disease history (steroid dependence, use of biologic or immunomodulator, and/or surgery) or non-aggressive history. All participants did two weeks of wrist actigraphy, followed by measurement of intestinal permeability and stool microbiota. Wrist actigraphy was used to calculate circadian markers of rest-activity- interdaily stability (IS), intradaily variability (IV), and relative amplitude (RA). Aggressive IBD history was associated with decrease rest-activity stability (IS) and increased fragmentation compared to non-aggressive IBD and health controls at 0.39 ±.15 vs. 0.51 ± 0.10 vs. 0.55 ± 0.09 (P < 0.05) and 0.83 ± 0.20 vs. 0.72 ± 0.14 (P < 0.05) but not HC at 0.72 ± 0.14 (P = 0.08); respectively. There was not a significant difference in RA by IBD disease history. Increased intestinal permeability and increased TNF-α levels correlated with an increased rest activity fragmentation (IV) at R = 0.35, P < 0.05 and R = 0.37, P < 0.05, respectively; and decreased rest-activity amplitude (RA) was associated with increased stool calprotectin at R = 0.40, P < 0.05. Analysis of intestinal microbiota showed a significant decrease in commensal butyrate producing taxa and increased pro-inflammatory bacteria with disrupted rest-activity cycles. In this study, different components of circadian misalignment by rest-activity cycles were associated with a more aggressive IBD disease history, increased intestinal permeability, stool calprotectin, increased pro-inflammatory cytokines, and dysbiosis. Wrist activity allows for an easy non-invasive assessment of circadian activity which may be an important biomarker of inflammation in IB.
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Affiliation(s)
- Garth R. Swanson
- Division of Digestive Diseases and Nutrition, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
- *Correspondence: Garth R. Swanson
| | - Nicole Kochman
- Division of Digestive Diseases and Nutrition, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
| | - Jaimin Amin
- Division of Digestive Diseases and Nutrition, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
| | - Vijit Chouhan
- Division of Digestive Diseases and Nutrition, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
| | - Wesley Yim
- Division of Digestive Diseases and Nutrition, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
| | - Phillip A. Engen
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
| | - Maliha Shaikh
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
| | - Ankur Naqib
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
| | - Laura Tran
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
| | - Robin M. Voigt
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
| | - Christopher B. Forsyth
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
| | - Stefan J. Green
- Genomics and Microbiome Core Facility, Rush University, Chicago, IL, United States
| | - Ali Keshavarzian
- Division of Digestive Diseases and Nutrition, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
- Rush Medical College, Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, IL, United States
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31
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Hühne A, Hoch E, Landgraf D. DAILY-A Personalized Circadian Zeitgeber Therapy as an Adjunctive Treatment for Alcohol Use Disorder Patients: Study Protocol for a Randomized Controlled Trial. Front Psychiatry 2020; 11:569864. [PMID: 33519541 PMCID: PMC7840704 DOI: 10.3389/fpsyt.2020.569864] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 12/09/2020] [Indexed: 01/23/2023] Open
Abstract
Background: Hallmarks of alcohol use disorder (AUD) are disturbances of circadian rhythms and everyday structures. While circadian rhythms dictate the timing of daily recurring activities such as sleep, activity, and meals, conversely, these activities represent time cues, so called Zeitgebers, that the circadian system uses to synchronize with the environment. Here we present a study protocol for our newly developed therapy approach for AUD patients, in which we take advantage of this mutual influence and stabilize and strengthen their circadian system by creating strict daily schedules for daily Zeitgeber activities. Since every person has a circadian system with its own characteristics and is subject to social obligations, the daily plans are personalized for each test person. Our hypothesis is that a regular exposure to Zeitgebers stabilizes behavioral and physiological circadian rhythms and thereby reduces the risk of alcohol relapses and depressive symptoms and facilitates physical recovery in AUD patients during the 1st weeks of their addiction therapy. Methods/design: The study is a 6-weeks single site trial with a controlled, randomized, single-blinded, parallel-group design including patients with a diagnosis of AUD. The study runs parallel to the standard addiction therapy of the clinic. Patients are randomly assigned to either an intervention group (DAILY) or a sham control group (placebo treatment). Questionnaires and physiological assessments of both groups are conducted before and immediately after the intervention or control treatment. According to our hypothesis, the primary outcomes of this study are improvements of regularity, alcohol consumption, and relapse rate in AUD patients compared to AUD patients receiving control treatment. Secondary outcomes are reduced depressive symptoms and increased physical recovery. Discussion: This study is a randomized controlled trial to investigate the efficacy of a personalized circadian Zeitgeber therapy as an adjunctive treatment for alcohol use disorder patients. The overall goal of this and more extended future studies is the development of an adjunctive therapy for AUD patients that is uncomplicated in its use and easy to implement in the clinical and everyday routine. Trial registration: This study is registered at the German Clinical Trial Register with the trial number DRKS00019093 on November 28, 2019.
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Affiliation(s)
- Anisja Hühne
- Circadian Biology Group, Department of Molecular Neurobiology, Clinic of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University, Munich, Germany.,Munich Medical Research School, Ludwig Maximilian University, Munich, Germany
| | - Eva Hoch
- Cannabinoid Research and Treatment Group, Division of Clinical Psychology and Psychological Treatment, Department of Psychology, Clinic of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University, Munich, Germany
| | - Dominic Landgraf
- Circadian Biology Group, Department of Molecular Neurobiology, Clinic of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University, Munich, Germany
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