53 research outputs found
Alphaopics: Species and Photoreceptor-Specific Light Exposure Measurement in Mammals
No full textR package to calculate mammal species and photopigment specific light exposure
Alphaopics: Species and Photoreceptor-Specific Light Exposure Measurement in Mammals
No full textR package to calculate mammal species and photopigment specific light exposure
Seasonality and season of birth effect in the UK Biobank cohort
No full textObjectivesHumans live in environments that reduce the impact of seasonal cues. However, studies suggest that many aspects of human biology, such as birth, metabolism, health, and death are still annually rhythmic.MethodsUsing UK Biobank, a large (N = 502 536) population‐based resource, we investigated the influence of seasonality on birth rate, basal metabolic rate, health, reaction speed, and sleep. We also investigated the association between season of birth and regional brain volumes, basal metabolic rate, health, reaction speed, and sleep.ResultsOur results showed that annual birth rate peaks in April and May. Individuals had the highest basal metabolic rate in December and January. Poorer subjective general health and slower reaction time were observed in May. Susceptibility to insomnia showed an opposite trend that peaked in autumn and winter. People reported shorter periods of sleep, easier waking, earlier chronotype, more daytime dozing, and napping in summer compared with winter. Our results suggest that season of birth may influence later‐life characteristics. We also observed that the effect of season of birth is in the opposite direction of the seasonal rhythm for basal metabolic rate, reaction time, and insomnia. Moreover, our analysis showed that prevalence of allergy is higher among people born in spring compared to autumn.ConclusionsOverall, our findings indicate a significant effect of seasonality on a range of human traits and that early‐life seasons appear to have an effect on health and behaviors in adulthood
Narcolepsy genetic variants associated with sleep efficiency in a community dwelling older cohort
No full textAbstract Narcolepsy type I (NT1) is a life-long debilitating autoimmune neurological condition characterised by excessive daytime sleepiness (EDS); the only symptom universal to all patients. Issues regarding sleep efficiency is also prevalent in individuals with NT1, however it remains relatively understudied due to the difficulty in measuring the effect. Genetic traits have shown to predispose an individual to NT1 and while HLA-DQB1 * 06:02 remains the most impactful genetic risk factor additional genes that contribute to immune cell processing have also been identified. In this retrospective study we impute 13 non-MHC narcolepsy associated single nucleotide polymorphisms (SNPs) from 1,558 non-pathological elderly volunteers who have been followed for up to a 24-year period to determine the association with sleep efficiency. Utilising a healthy cohort allows us to independently assess the potential contribution of each SNP on the impact of the sleep cycle disruption. We observed significant associations between SNPs and various elements of the sleep process; however, the main findings were the associations with disturbed night sleep (DNS). We observed an association with rs10915020 and rs1551570 with an increased number of wake episodes during the night, conversely rs2859998 and rs2834168 showed a protective effect—reducing the frequency of nighttime disturbances. While the association with NT1 and DNS has long been established, this is the first investigation that attributes elements of DNS to the genetic profile of the patient. This suggests that the issues with sleep efficiency reported by patients may be due to genetic predispositions and supports the variation seen in the co-morbidities associated with the condition
Longitudinal Sleep Efficiency in the Elderly and Its Association with Health
No full textThe relationships between older age and sleep efficiency have traditionally been assessed using cross‐sectional studies that ignore changes within individuals as they age. This research examines the determinants of sleep efficiency, the heterogeneity in an individual's sleep efficiency trajectory across a period of up to 27 years in later life and its associations with health. The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age cohort (n = 6,375; age 42–94 years) was used in this study. Depression and health data were collected using self‐report validated instruments (Cornell Medical Index, Beck Depression Inventory and Geriatric Depression Scale). Longitudinal sleep and sociodemographic data were collected using a study‐specific self‐report questionnaire. A mixed‐effect model was performed for sleep efficiency with adjustments for time‐invariant and time‐variant predictors. Latent class analysis was used to demonstrate subgroups of sleep efficiency trajectories and associations between sleep efficiency clusters and health history of the participants were investigated. Older adults have decreased sleep efficiency over time, with 18.6% decline between 40 and 100 years of age. Three sleep efficiency trajectory clusters were identified: high (32%), medium (50%) and low sleep efficiency (18%). Belonging to the high sleep efficiency cluster was associated with having lower prevalence of hypertension, circulatory problems, general arthritis, breathing problems and recurrent episodes of depression compared to the low efficiency cluster. Overall, ageing decreases sleep efficiency. However, there are detectable subgroups of sleep efficiency that are related to prevalence of different diseases
Interactions between season of birth, chronological age and genetic polymorphisms in determining later-life chronotype
No full textHuman chronotype, the temporal pattern of daily behaviors, is influenced by postnatal seasonal programming and ageing. The aim of this study was to investigate genetic variants that are associated with season of birth programming and longitudinal chronotype change. Longitudinal sleep timing and genotype data from 1449 participants were collected for up to 27 years. Gene-environment interaction analysis was performed for 445 candidate single nucleotide polymorphisms that have previously been associated with chronotype. Associations were tested using linear mixed model. We identified 67 suggestively significant genomic loci that have genotype-ageing interaction and 25 genomic loci that may have genotype-season of birth interaction in determining chronotype. We attempted to replicate the results using longitudinal data of the UK Biobank from approximately 30,000 participants. Biological functions of these genes suggest that epigenetic regulation of gene expression and neural development may have roles in these processes. The strongest associated gene for sleep trajectories was ALKBH5, which has functions of DNA repair and epigenetic regulation. A potential candidate gene for postnatal seasonal programming was SIRT1, which has previously been implicated in postnatal programming, ageing and longevity. Genetic diversity may explain the heterogeneity in ageing-related change of sleep timing and postnatal environmental programming of later-life chronotype
Measuring light exposure in daily life:A review of wearable light loggers
No full textWearable light loggers are increasingly available for various applications, including consumer, research and clinical contexts. This study employed a survey design to systematically outline available wearable light loggers, focusing on their key characteristics and usability. Through expert meetings and iterative discussions, we developed a comprehensive survey instrument covering device properties, sensor characteristics, calibration methods, and applications. Data were collected from manufacturer-provided information and public sources for 53 wearable light loggers. Our findings highlight the diversity among wearable light loggers in terms of their device characteristics. A notable increase in the number and sophistication of wearable light loggers is visible over the past decade. However, the variability in the quality and completeness of reported device performance and validation methods emphasizes the importance of standardized practices and improved collaboration between researchers and manufacturers to enhance the reliability and usability of wearable light logging technologies in scientific research
Longitudinal change of sleep timing: association between chronotype and longevity in older adults
No full textEvening-oriented sleep timing preferences have been associated with risk of diabetes, cardiovascular diseases, obesity, psychiatric disorders, and increased mortality. This research aims to explore the relationship between diurnal preferences (chronotype), daily habits, metabolic health, and mortality, using longitudinal data from The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age (6375 participants at inception, recruited in the North of England) with a long follow-up period (up to 35.5 years). Mixed models were used to investigate the influence of aging, socio-demographic, and seasonal factors on sleep timing. Results show that sleep timing shifted towards earlier time with aging. Test seasons influence chronotype of older adults but working schedules challenge seasonality of sleep timing. Moreover, the season of birth may set chronotype in adulthood. Individual chronotype trajectories were clustered using latent class analysis and analyzed against metabolic health and mortality. We observed a higher risk of hypertension in the evening-type cluster compared to morning-type individuals (Odds ratio= 1.88, 95%CI = 1.02/3.47, p= .04). Evening-type cluster was also associated with traits related to lower health such as reduced sport participation, increased risk of depression and psychoticism personality, late eating, and increased smoking and alcohol usage. Finally, Cox regression of proportional hazards was used to study the effects of chronotype on longevity after adjusting for sleep duration, age, gender, smoking, alcohol usage, general health, and social class. The survival analysis (82.6% censored by death) revealed that evening-type chronotype increased the likelihood of mortality (Hazard ratio = 1.15, 95%CI = 1.04/1.26, p = .005). Taken together, chronotype is influenced by aging and seasonal effects. Evening-type preference may have detrimental outcomes for human well-being and longevity
Data: Associations between light exposure and sleep timing and sleepiness while awake in a sample of UK adults in everyday life
No full textRaw data of the research paper, 'Associations between light exposure and sleep timing and sleepiness while awake in a sample of UK adults in everyday life'. We incorporate an open-source wearable wrist-worn light logger (Spectrawear) and smart-phone based online data collection. We simultaneously record longitudinal light exposure (in equivalent daylight illuminance (EDI)), sleep timing, and subjective alertness over seven days, in a convenience sample of 59 UK adults without externally imposed circadian challenge (e.g. shift-work or jetlag). The monitor was set with a 30-second sampling interval. Participants were asked to wear the device during the day and to take it off just before their bedtimes by leaving it to a location in the same room (preferably near eye level). The repeated measure of sleepiness was collected by the Karolinska Sleepiness Scale (KSS) 10-item version (score 10: extremely sleepy). The sleep diary file includes wake time in the survey date and bedtime (zero=midnight), subjective sleep quality, sleep duration (hours), sleep latency (hours, how long it took to fall asleep after going to bed), napping, smoking, alcohol and caffeine usage yesterday. The baseline file includes age, sex, subjective health score, subjective chronotype, MCTQ MSFsc, PSQI total score, IPAQ activity category, general smoking, alcohol and caffeine usage behaviours.
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