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Schmal C. The seasons within: a theoretical perspective on photoperiodic entrainment and encoding. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2024; 210:549-564. [PMID: 37659985 PMCID: PMC11226496 DOI: 10.1007/s00359-023-01669-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 08/11/2023] [Accepted: 08/16/2023] [Indexed: 09/04/2023]
Abstract
Circadian clocks are internal timing devices that have evolved as an adaption to the omnipresent natural 24 h rhythmicity of daylight intensity. Properties of the circadian system are photoperiod dependent. The phase of entrainment varies systematically with season. Plastic photoperiod-dependent re-arrangements in the mammalian circadian core pacemaker yield an internal representation of season. Output pathways of the circadian clock regulate photoperiodic responses such as flowering time in plants or hibernation in mammals. Here, we review the concepts of seasonal entrainment and photoperiodic encoding. We introduce conceptual phase oscillator models as their high level of abstraction, but, yet, intuitive interpretation of underlying parameters allows for a straightforward analysis of principles that determine entrainment characteristics. Results from this class of models are related and discussed in the context of more complex conceptual amplitude-phase oscillators as well as contextual molecular models that take into account organism, tissue, and cell-type-specific details.
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Affiliation(s)
- Christoph Schmal
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstr. 13, 10115, Berlin, Germany.
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2
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Wescott DL, Hasler BP, Franzen PL, Taylor ML, Klevens AM, Gamlin P, Siegle GJ, Roecklein KA. Circadian photoentrainment varies by season and depressed state: associations between light sensitivity and sleep and circadian timing. Sleep 2024; 47:zsae066. [PMID: 38530635 PMCID: PMC11168757 DOI: 10.1093/sleep/zsae066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 02/08/2024] [Indexed: 03/28/2024] Open
Abstract
STUDY OBJECTIVES Altered light sensitivity may be an underlying vulnerability for disrupted circadian photoentrainment. The photic information necessary for circadian photoentrainment is sent to the circadian clock from melanopsin-containing intrinsically photosensitive retinal ganglion cells (ipRGCs). The current study tested whether the responsivity of ipRGCs measured using the post-illumination pupil response (PIPR) was associated with circadian phase, sleep timing, and circadian alignment, and if these relationships varied by season or depression severity. METHODS Adult participants (N = 323, agem = 40.5, agesd = 13.5) with varying depression severity were recruited during the summer (n = 154) and winter (n = 169) months. Light sensitivity was measured using the PIPR. Circadian phase was assessed using Dim Light Melatonin Onset (DLMO) on Friday evenings. Midsleep was measured using actigraphy. Circadian alignment was calculated as the DLMO-midsleep phase angle. Multilevel regression models covaried for age, gender, and time since wake of PIPR assessment. RESULTS Greater light sensitivity was associated with later circadian phase in summer but not in winter (β = 0.23; p = 0.03). Greater light sensitivity was associated with shorter DLMO-midsleep phase angles (β = 0.20; p = 0.03) in minimal depression but not in moderate depression (SIGHSAD < 6.6; Johnson-Neyman region of significance). CONCLUSIONS Light sensitivity measured by the PIPR was associated with circadian phase during the summer but not in winter, suggesting ipRGC functioning in humans may affect circadian entrainment when external zeitgebers are robust. Light sensitivity was associated with circadian alignment only in participants with minimal depression, suggesting circadian photoentrainment, a possible driver of mood, may be decreased in depression year-round, similar to decreased photoentrainment in winter.
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Affiliation(s)
| | - Brant P Hasler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Peter L Franzen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Maddison L Taylor
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alison M Klevens
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Paul Gamlin
- Department of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Greg J Siegle
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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3
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Varma P, Postnova S, Knock S, Howard ME, Aidman E, Rajaratnam SWM, Sletten TL. SleepSync: Early Testing of a Personalised Sleep-Wake Management Smartphone Application for Improving Sleep and Cognitive Fitness in Defence Shift Workers. Clocks Sleep 2024; 6:267-280. [PMID: 38920420 PMCID: PMC11203003 DOI: 10.3390/clockssleep6020019] [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: 04/10/2024] [Revised: 05/27/2024] [Accepted: 05/27/2024] [Indexed: 06/27/2024] Open
Abstract
Shift work, long work hours, and operational tasks contribute to sleep and circadian disruption in defence personnel, with profound impacts on cognition. To address this, a digital technology, the SleepSync app, was designed for use in defence. A pre-post design study was undertaken to examine whether four weeks app use improved sleep and cognitive fitness (high performance neurocognition) in a cohort of shift workers from the Royal Australian Air Force. In total, 13 of approximately 20 shift-working personnel from one base volunteered for the study. Sleep outcomes were assessed using the Insomnia Severity Index (ISI), the Patient-Reported Outcomes Measurement Information System (PROMIS), Sleep Disturbance and Sleep-Related Impairment Scales, the Glasgow Sleep Effort Scale, the Sleep Hygiene Index, and mental health was assessed using the Depression, Anxiety, and Stress Scale-21. Sustained attention was measured using the 3-min Psychomotor Vigilance Task (PVT) and controlled response using the NBack. Results showed significant improvements in insomnia (ISI scores 10.31 at baseline and 7.50 after app use), sleep-related impairments (SRI T-scores 53.03 at baseline to 46.75 post-app use), and healthy sleep practices (SHI scores 21.61 at baseline to 18.83 post-app use; all p < 0.001). Trends for improvement were recorded for depression. NBack incorrect responses reduced significantly (9.36 at baseline; reduced by -3.87 at last week of app use, p < 0.001), but no other objective measures improved. These findings suggest that SleepSync may improve sleep and positively enhance cognitive fitness but warrants further investigation in large samples. Randomised control trials with other cohorts of defence personnel are needed to confirm the utility of this intervention in defence settings.
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Affiliation(s)
- Prerna Varma
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Clayton, VIC 3168, Australia
| | - Svetlana Postnova
- School of Physics, The University of Sydney, Camperdown, NSW 2050, Australia
| | - Stuart Knock
- School of Physics, The University of Sydney, Camperdown, NSW 2050, Australia
| | - Mark E. Howard
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Clayton, VIC 3168, Australia
- Institute for Breathing and Sleep, Austin Health, Heidelberg, VIC 3084, Australia
- Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC 3010, Australia
| | - Eugene Aidman
- Defence, Science and Technology Group, Department of Defence, Edinburgh, SA 5111, Australia;
- School of Biomedical Sciences & Pharmacy, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Shantha W. M. Rajaratnam
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Clayton, VIC 3168, Australia
- School of Biomedical Sciences & Pharmacy, University of Newcastle, Callaghan, NSW 2308, Australia
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Tracey L. Sletten
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Clayton, VIC 3168, Australia
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4
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Höhn C, Hahn MA, Gruber G, Pletzer B, Cajochen C, Hoedlmoser K. Effects of evening smartphone use on sleep and declarative memory consolidation in male adolescents and young adults. Brain Commun 2024; 6:fcae173. [PMID: 38846535 PMCID: PMC11154150 DOI: 10.1093/braincomms/fcae173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/08/2024] [Accepted: 05/16/2024] [Indexed: 06/09/2024] Open
Abstract
Exposure to short-wavelength light before bedtime is known to disrupt nocturnal melatonin secretion and can impair subsequent sleep. However, while it has been demonstrated that older adults are less affected by short-wavelength light, there is limited research exploring differences between adolescents and young adults. Furthermore, it remains unclear whether the effects of evening short-wavelength light on sleep architecture extend to sleep-related processes, such as declarative memory consolidation. Here, we recorded polysomnography from 33 male adolescents (15.42 ± 0.97 years) and 35 male young adults (21.51 ± 2.06 years) in a within-subject design during three different nights to investigate the impact of reading for 90 min either on a smartphone with or without a blue-light filter or from a printed book. We measured subjective sleepiness, melatonin secretion, sleep physiology and sleep-dependent memory consolidation. While subjective sleepiness remained unaffected, we observed a significant melatonin attenuation effect in both age groups immediately after reading on the smartphone without a blue-light filter. Interestingly, adolescents fully recovered from the melatonin attenuation in the following 50 min before bedtime, whereas adults still, at bedtime, exhibited significantly reduced melatonin levels. Sleep-dependent memory consolidation and the coupling between sleep spindles and slow oscillations were not affected by short-wavelength light in both age groups. Nevertheless, adults showed a reduction in N3 sleep during the first night quarter. In summary, avoiding smartphone use in the last hour before bedtime is advisable for adolescents and young adults to prevent sleep disturbances. Our research empirically supports general sleep hygiene advice and can inform future recommendations regarding the use of smartphones and other screen-based devices before bedtime.
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Affiliation(s)
- Christopher Höhn
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Paris Lodron University of Salzburg, 5020 Salzburg, Austria
- Centre for Cognitive Neuroscience Salzburg (CCNS), Paris Lodron University of Salzburg, 5020 Salzburg, Austria
| | - Michael A Hahn
- Hertie-Institute for Clinical Brain Research, University Medical Center Tübingen, 72076 Tübingen, Germany
| | - Georg Gruber
- The Siesta Group Schlafanalyse GmbH, 1210 Vienna, Austria
| | - Belinda Pletzer
- Centre for Cognitive Neuroscience Salzburg (CCNS), Paris Lodron University of Salzburg, 5020 Salzburg, Austria
| | - Christian Cajochen
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, 4002 Basel, Switzerland
- Research Cluster Molecular and Cognitive Neuroscience (MCN), University of Basel, 4055 Basel, Switzerland
| | - Kerstin Hoedlmoser
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Paris Lodron University of Salzburg, 5020 Salzburg, Austria
- Centre for Cognitive Neuroscience Salzburg (CCNS), Paris Lodron University of Salzburg, 5020 Salzburg, Austria
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5
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Della Monica C, Ravindran KKG, Atzori G, Lambert DJ, Rodriguez T, Mahvash-Mohammadi S, Bartsch U, Skeldon AC, Wells K, Hampshire A, Nilforooshan R, Hassanin H, The Uk Dementia Research Institute Care Research Amp Technology Research Group, Revell VL, Dijk DJ. A Protocol for Evaluating Digital Technology for Monitoring Sleep and Circadian Rhythms in Older People and People Living with Dementia in the Community. Clocks Sleep 2024; 6:129-155. [PMID: 38534798 DOI: 10.3390/clockssleep6010010] [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: 12/18/2023] [Revised: 02/12/2024] [Accepted: 02/20/2024] [Indexed: 03/28/2024] Open
Abstract
Sleep and circadian rhythm disturbance are predictors of poor physical and mental health, including dementia. Long-term digital technology-enabled monitoring of sleep and circadian rhythms in the community has great potential for early diagnosis, monitoring of disease progression, and assessing the effectiveness of interventions. Before novel digital technology-based monitoring can be implemented at scale, its performance and acceptability need to be evaluated and compared to gold-standard methodology in relevant populations. Here, we describe our protocol for the evaluation of novel sleep and circadian technology which we have applied in cognitively intact older adults and are currently using in people living with dementia (PLWD). In this protocol, we test a range of technologies simultaneously at home (7-14 days) and subsequently in a clinical research facility in which gold standard methodology for assessing sleep and circadian physiology is implemented. We emphasize the importance of assessing both nocturnal and diurnal sleep (naps), valid markers of circadian physiology, and that evaluation of technology is best achieved in protocols in which sleep is mildly disturbed and in populations that are relevant to the intended use-case. We provide details on the design, implementation, challenges, and advantages of this protocol, along with examples of datasets.
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Affiliation(s)
- Ciro Della Monica
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
| | - Kiran K G Ravindran
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
| | - Giuseppe Atzori
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
| | - Damion J Lambert
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
| | - Thalia Rodriguez
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
- School of Mathematics & Physics, University of Surrey, Guildford GU2 7XH, UK
| | - Sara Mahvash-Mohammadi
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
- Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK
| | - Ullrich Bartsch
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
| | - Anne C Skeldon
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
- School of Mathematics & Physics, University of Surrey, Guildford GU2 7XH, UK
| | - Kevin Wells
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
- Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK
| | - Adam Hampshire
- Department of Brain Sciences, Imperial College, London W12 0NN, UK
| | - Ramin Nilforooshan
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
- Surrey and Borders Partnership NHS Foundation Trust Surrey, Chertsey KT16 9AU, UK
| | - Hana Hassanin
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
- Surrey Clinical Research Facility, University of Surrey, Guildford GU2 7XP, UK
- NIHR Royal Surrey CRF, Royal Surrey Foundation Trust, Guildford GU2 7XX, UK
| | | | - Victoria L Revell
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, University of Surrey, Guildford GU2 7XP, UK
- UK Dementia Research Institute Care Research & Technology Centre (CR&T), Imperial College London and the University of Surrey, London W12 0NN, UK
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6
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Vicente-Martínez J, Bonmatí-Carrión MÁ, Madrid JA, Rol MA. Uncovering personal circadian responses to light through particle swarm optimization. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107933. [PMID: 38006683 DOI: 10.1016/j.cmpb.2023.107933] [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: 05/23/2023] [Revised: 10/02/2023] [Accepted: 11/17/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND AND OBJECTIVES Kronauer's oscillator model of the human central pacemaker is one of the most commonly used approaches to study the human circadian response to light. Two sources of error when applying it to a personal light exposure have been identified: (1) as a populational model, it does not consider inter-individual variability, and (2) the initial conditions needed to integrate the model are usually unknown, and thus subjectively estimated. In this work, we evaluate the ability of particle swarm optimization (PSO) algorithms to simultaneously uncover the optimal initial conditions and individual parameters of a pre-defined Kronauer's oscillator model. METHODS A Canonical PSO, a Dynamic Multi-Swarm PSO and a novel modification of the latter, namely Hierarchical Dynamic Multi-Swarm PSO, are evaluated. Two different target models (under a regular and an irregular schedule) are defined, and the same realistic light profile is fed to them. Based on their output, a fitness function is proposed, which is minimized by the algorithms to find the optimum set of parameters and initial conditions of the model. RESULTS We demonstrate that Dynamic Multi-Swarm and Hierarchical Dynamic Multi-Swarm algorithms can accurately uncover personal circadian parameters under both regular and irregular schedules, but as expected, optimization is easier under a regular schedule. Circadian parameters play the most important role in the optimization process and should be prioritized over initial conditions, although assessment of the impact of misestimating the latter is recommended. The log-log linear relationship between mean absolute error and computational cost shows that the number of particles to use is at the discretion of the user. CONCLUSIONS The robustness and low errors achieved by the algorithms support their further testing, validation and systematic application to empirical data under a regular or irregular schedule. Uncovering personal circadian parameters can improve the assessment of the circadian status of a person and the applicability of personalized light therapies, as well as help to discover other factors that may lie behind the interindividual variability in the circadian response to light.
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Affiliation(s)
- Jesús Vicente-Martínez
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - María Ángeles Bonmatí-Carrión
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain.
| | - Juan Antonio Madrid
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - Maria Angeles Rol
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain
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7
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Skeldon AC, Rodriguez Garcia T, Cleator SF, della Monica C, Ravindran KKG, Revell VL, Dijk DJ. Method to determine whether sleep phenotypes are driven by endogenous circadian rhythms or environmental light by combining longitudinal data and personalised mathematical models. PLoS Comput Biol 2023; 19:e1011743. [PMID: 38134229 PMCID: PMC10817199 DOI: 10.1371/journal.pcbi.1011743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 01/26/2024] [Accepted: 12/06/2023] [Indexed: 12/24/2023] Open
Abstract
Sleep timing varies between individuals and can be altered in mental and physical health conditions. Sleep and circadian sleep phenotypes, including circadian rhythm sleep-wake disorders, may be driven by endogenous physiological processes, exogeneous environmental light exposure along with social constraints and behavioural factors. Identifying the relative contributions of these driving factors to different phenotypes is essential for the design of personalised interventions. The timing of the human sleep-wake cycle has been modelled as an interaction of a relaxation oscillator (the sleep homeostat), a stable limit cycle oscillator with a near 24-hour period (the circadian process), man-made light exposure and the natural light-dark cycle generated by the Earth's rotation. However, these models have rarely been used to quantitatively describe sleep at the individual level. Here, we present a new Homeostatic-Circadian-Light model (HCL) which is simpler, more transparent and more computationally efficient than other available models and is designed to run using longitudinal sleep and light exposure data from wearable sensors. We carry out a systematic sensitivity analysis for all model parameters and discuss parameter identifiability. We demonstrate that individual sleep phenotypes in each of 34 older participants (65-83y) can be described by feeding individual participant light exposure patterns into the model and fitting two parameters that capture individual average sleep duration and timing. The fitted parameters describe endogenous drivers of sleep phenotypes. We then quantify exogenous drivers using a novel metric which encodes the circadian phase dependence of the response to light. Combining endogenous and exogeneous drivers better explains individual mean mid-sleep (adjusted R-squared 0.64) than either driver on its own (adjusted R-squared 0.08 and 0.17 respectively). Critically, our model and analysis highlights that different people exhibiting the same sleep phenotype may have different driving factors and opens the door to personalised interventions to regularize sleep-wake timing that are readily implementable with current digital health technology.
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Affiliation(s)
- Anne C. Skeldon
- School of Mathematics & Physics, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
| | - Thalia Rodriguez Garcia
- School of Mathematics & Physics, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Sean F. Cleator
- School of Mathematics & Physics, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Ciro della Monica
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Kiran K. G. Ravindran
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Victoria L. Revell
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Derk-Jan Dijk
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
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Abbott SM, Phillips AJ, Reid KJ, Cain SW, Zee PC. What's in a name? delayed by any other name is still a circadian disorder: a call for improved nomenclature for delayed sleep-wake phase disorder subtypes. Sleep 2023; 46:zsad222. [PMID: 37651094 DOI: 10.1093/sleep/zsad222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023] Open
Affiliation(s)
- Sabra M Abbott
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, ILUSA
| | - Andrew J Phillips
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Kathryn J Reid
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, ILUSA
| | - Sean W Cain
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Phyllis C Zee
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, ILUSA
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9
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Ohashi M, Eto T, Takasu T, Motomura Y, Higuchi S. Relationship between Circadian Phase Delay without Morning Light and Phase Advance by Bright Light Exposure the Following Morning. Clocks Sleep 2023; 5:615-626. [PMID: 37873842 PMCID: PMC10594521 DOI: 10.3390/clockssleep5040041] [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: 07/31/2023] [Revised: 10/17/2023] [Accepted: 10/20/2023] [Indexed: 10/25/2023] Open
Abstract
Humans have a circadian rhythm for which the period varies among individuals. In the present study, we investigated the amount of natural phase delay of circadian rhythms after spending a day under dim light (Day 1 to Day 2) and the amount of phase advance due to light exposure (8000 lx, 4100 K) the following morning (Day 2 to Day 3). The relationships of the phase shifts with the circadian phase, chronotype and sleep habits were also investigated. Dim light melatonin onset (DLMO) was investigated as a circadian phase marker on each day. In the 27 individuals used for the analysis, DLMO was delayed significantly (-0.24 ± 0.33 h, p < 0.01) from Day 1 to Day 2 and DLMO was advanced significantly (0.18 ± 0.36 h, p < 0.05) from Day 2 to Day 3. There was a significant correlation between phase shifts, with subjects who had a greater phase delay in the dim environment having a greater phase advance by light exposure (r = -0.43, p < 0.05). However, no significant correlations with circadian phase, chronotype or sleep habits were found. These phase shifts may reflect the stability of the phase, but do not account for an individual's chronotype-related indicators.
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Affiliation(s)
- Michihiro Ohashi
- Graduate School of Integrated Frontier Sciences, Kyushu University, Fukuoka 815-8540, Japan; (M.O.)
- Research Fellow of the Japan Society for the Promotion of Science, Fukuoka 815-8540, Japan
| | - Taisuke Eto
- Research Fellow of the Japan Society for the Promotion of Science, Fukuoka 815-8540, Japan
- Department of Human Life Design and Science, Faculty of Design, Kyushu University, Fukuoka 815-8540, Japan
- Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan
| | - Toaki Takasu
- Graduate School of Integrated Frontier Sciences, Kyushu University, Fukuoka 815-8540, Japan; (M.O.)
| | - Yuki Motomura
- Department of Human Life Design and Science, Faculty of Design, Kyushu University, Fukuoka 815-8540, Japan
| | - Shigekazu Higuchi
- Department of Human Life Design and Science, Faculty of Design, Kyushu University, Fukuoka 815-8540, Japan
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10
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Skapetze L, Owino S, Lo EH, Arai K, Merrow M, Harrington M. Rhythms in barriers and fluids: Circadian clock regulation in the aging neurovascular unit. Neurobiol Dis 2023; 181:106120. [PMID: 37044366 DOI: 10.1016/j.nbd.2023.106120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/27/2023] [Accepted: 04/07/2023] [Indexed: 04/14/2023] Open
Abstract
The neurovascular unit is where two very distinct physiological systems meet: The central nervous system (CNS) and the blood. The permeability of the barriers separating these systems is regulated by time, including both the 24 h circadian clock and the longer processes of aging. An endogenous circadian rhythm regulates the transport of molecules across the blood-brain barrier and the circulation of the cerebrospinal fluid and the glymphatic system. These fluid dynamics change with time of day, and with age, and especially in the context of neurodegeneration. Factors may differ depending on brain region, as can be highlighted by consideration of circadian regulation of the neurovascular niche in white matter. As an example of a potential target for clinical applications, we highlight chaperone-mediated autophagy as one mechanism at the intersection of circadian dysregulation, aging and neurodegenerative disease. In this review we emphasize key areas for future research.
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Affiliation(s)
- Lea Skapetze
- Institute of Medical Psychology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Sharon Owino
- Neuroscience Program, Smith College, Northampton, MA 01060, United States of America
| | - Eng H Lo
- Neuroprotection Research Laboratories, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Arai
- Neuroprotection Research Laboratories, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Martha Merrow
- Institute of Medical Psychology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Mary Harrington
- Neuroscience Program, Smith College, Northampton, MA 01060, United States of America.
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11
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Burns AC, Phillips AJK, Rutter MK, Saxena R, Cain SW, Lane JM. Genome-wide gene by environment study of time spent in daylight and chronotype identifies emerging genetic architecture underlying light sensitivity. Sleep 2023; 46:zsac287. [PMID: 36519390 PMCID: PMC9995784 DOI: 10.1093/sleep/zsac287] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/14/2022] [Indexed: 12/23/2022] Open
Abstract
STUDY OBJECTIVES Light is the primary stimulus for synchronizing the circadian clock in humans. There are very large interindividual differences in the sensitivity of the circadian clock to light. Little is currently known about the genetic basis for these interindividual differences. METHODS We performed a genome-wide gene-by-environment interaction study (GWIS) in 280 897 individuals from the UK Biobank cohort to identify genetic variants that moderate the effect of daytime light exposure on chronotype (individual time of day preference), acting as "light sensitivity" variants for the impact of daylight on the circadian system. RESULTS We identified a genome-wide significant SNP mapped to the ARL14EP gene (rs3847634; p < 5 × 10-8), where additional minor alleles were found to enhance the morningness effect of daytime light exposure (βGxE = -.03, SE = 0.005) and were associated with increased gene ARL14EP expression in brain and retinal tissues. Gene-property analysis showed light sensitivity loci were enriched for genes in the G protein-coupled glutamate receptor signaling pathway and genes expressed in Per2+ hypothalamic neurons. Linkage disequilibrium score regression identified Bonferroni significant genetic correlations of greater light sensitivity GWIS with later chronotype and shorter sleep duration. Greater light sensitivity was nominally genetically correlated with insomnia symptoms and risk for post-traumatic stress disorder (PTSD). CONCLUSIONS This study is the first to assess light as an important exposure in the genomics of chronotype and is a critical first step in uncovering the genetic architecture of human circadian light sensitivity and its links to sleep and mental health.
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Affiliation(s)
- Angus C Burns
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute, Cambridge, MA, USA
| | - Andrew J K Phillips
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Martin K Rutter
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute, Cambridge, MA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Sean W Cain
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Jacqueline M Lane
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute, Cambridge, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, 02115, USA
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12
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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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13
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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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14
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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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15
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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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16
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Lipsanen J, Kuula L, Elovainio M, Partonen T, Pesonen AK. Data-driven modelling approach to circadian temperature rhythm profiles in free-living conditions. Sci Rep 2021; 11:15029. [PMID: 34294824 PMCID: PMC8298484 DOI: 10.1038/s41598-021-94522-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 07/01/2021] [Indexed: 01/13/2023] Open
Abstract
The individual variation in the circadian rhythms at the physiological level is not well understood. Albeit self-reported circadian preference profiles have been consolidated, their premises are grounded on human experience, not on physiology. We used data-driven, unsupervised time series modelling to characterize distinct profiles of the circadian rhythm measured from skin surface temperature in free-living conditions. We demonstrate the existence of three distinct clusters of individuals which differed in their circadian temperature profiles. The cluster with the highest temperature amplitude and the lowest midline estimating statistic of rhythm, or rhythm-adjusted mean, had the most regular and early-timed sleep–wake rhythm, and was the least probable for those with a concurrent delayed sleep phase, or eveningness chronotype. While the clusters associated with the observed sleep and circadian preference patterns, the entirely unsupervised modelling of physiological data provides a novel basis for modelling and understanding the human circadian functions in free-living conditions.
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Affiliation(s)
- Jari Lipsanen
- Sleepwell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Liisa Kuula
- Sleepwell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Marko Elovainio
- Sleepwell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Timo Partonen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Anu-Katriina Pesonen
- Sleepwell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
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17
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Murray JM, Magee M, Sletten TL, Gordon C, Lovato N, Ambani K, Bartlett DJ, Kennaway DJ, Lack LC, Grunstein RR, Lockley SW, Rajaratnam SMW, Phillips AJK. Light-based methods for predicting circadian phase in delayed sleep-wake phase disorder. Sci Rep 2021; 11:10878. [PMID: 34035333 PMCID: PMC8149449 DOI: 10.1038/s41598-021-89924-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 04/13/2021] [Indexed: 02/04/2023] Open
Abstract
Methods for predicting circadian phase have been developed for healthy individuals. It is unknown whether these methods generalize to clinical populations, such as delayed sleep-wake phase disorder (DSWPD), where circadian timing is associated with functional outcomes. This study evaluated two methods for predicting dim light melatonin onset (DLMO) in 154 DSWPD patients using ~ 7 days of sleep-wake and light data: a dynamic model and a statistical model. The dynamic model has been validated in healthy individuals under both laboratory and field conditions. The statistical model was developed for this dataset and used a multiple linear regression of light exposure during phase delay/advance portions of the phase response curve, as well as sleep timing and demographic variables. Both models performed comparably well in predicting DLMO. The dynamic model predicted DLMO with root mean square error of 68 min, with predictions accurate to within ± 1 h in 58% of participants and ± 2 h in 95%. The statistical model predicted DLMO with root mean square error of 57 min, with predictions accurate to within ± 1 h in 75% of participants and ± 2 h in 96%. We conclude that circadian phase prediction from light data is a viable technique for improving screening, diagnosis, and treatment of DSWPD.
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Affiliation(s)
- Jade M. Murray
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia ,Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia
| | - Michelle Magee
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia ,Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia ,grid.1008.90000 0001 2179 088XCentre for Neuroscience of Speech, Department of Audiology and Speech Pathology, University of Melbourne, Melbourne, VIC Australia
| | - Tracey L. Sletten
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia ,Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia
| | - Christopher Gordon
- Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia ,grid.417229.b0000 0000 8945 8472Woolcock Institute of Medical Research and Sydney Local Health District, Sydney, NSW Australia ,grid.1013.30000 0004 1936 834XUniversity of Sydney Susan Wakil School of Nursing, Camperdown, NSW Australia
| | - Nicole Lovato
- Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,grid.1014.40000 0004 0367 2697Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA Australia
| | - Krutika Ambani
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia
| | - Delwyn J. Bartlett
- Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia ,grid.417229.b0000 0000 8945 8472Woolcock Institute of Medical Research and Sydney Local Health District, Sydney, NSW Australia
| | - David J. Kennaway
- grid.1010.00000 0004 1936 7304Robinson Research Institute and School of Medicine, University of Adelaide, Adelaide, SA Australia
| | - Leon C. Lack
- Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,grid.1014.40000 0004 0367 2697Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA Australia
| | - Ronald R. Grunstein
- Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia ,grid.417229.b0000 0000 8945 8472Woolcock Institute of Medical Research and Sydney Local Health District, Sydney, NSW Australia
| | - Steven W. Lockley
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia ,Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia ,grid.62560.370000 0004 0378 8294Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDivision of Sleep Medicine, Harvard Medical School, Boston, MA USA
| | - Shantha M. W. Rajaratnam
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia ,Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia ,NHMRC Centre for Sleep and Circadian Neurobiology, Sydney, NSW Australia ,grid.62560.370000 0004 0378 8294Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDivision of Sleep Medicine, Harvard Medical School, Boston, MA USA
| | - Andrew J. K. Phillips
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC 3800 Australia ,Cooperative Research Centre for Alertness, Safety and Productivity, Clayton, VIC Australia
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18
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Cain SW, McGlashan EM, Vidafar P, Mustafovska J, Curran SPN, Wang X, Mohamed A, Kalavally V, Phillips AJK. Evening home lighting adversely impacts the circadian system and sleep. Sci Rep 2020; 10:19110. [PMID: 33154450 PMCID: PMC7644684 DOI: 10.1038/s41598-020-75622-4] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 10/14/2020] [Indexed: 01/08/2023] Open
Abstract
The regular rise and fall of the sun resulted in the development of 24-h rhythms in virtually all organisms. In an evolutionary heartbeat, humans have taken control of their light environment with electric light. Humans are highly sensitive to light, yet most people now use light until bedtime. We evaluated the impact of modern home lighting environments in relation to sleep and individual-level light sensitivity using a new wearable spectrophotometer. We found that nearly half of homes had bright enough light to suppress melatonin by 50%, but with a wide range of individual responses (0–87% suppression for the average home). Greater evening light relative to an individual’s average was associated with increased wakefulness after bedtime. Homes with energy-efficient lights had nearly double the melanopic illuminance of homes with incandescent lighting. These findings demonstrate that home lighting significantly affects sleep and the circadian system, but the impact of lighting for a specific individual in their home is highly unpredictable.
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Affiliation(s)
- Sean W Cain
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
| | - Elise M McGlashan
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Parisa Vidafar
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Jona Mustafovska
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Simon P N Curran
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Xirun Wang
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Anas Mohamed
- Department of Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Malaysia
| | - Vineetha Kalavally
- Department of Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Malaysia
| | - Andrew J K Phillips
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
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