Sleep inertia drives the association of evening chronotype with psychiatric disorders: epidemiological and genetic evidence.

Evening chronotypes (a.k.a. night-owls) are held to be at greater risk for psychiatric disorders. This is postulated to be due to delayed circadian timing increasing the likelihood of circadian misalignment in an early-oriented society. Circadian misalignment is known to heighten sleep inertia, the difficulty transitioning from sleep to wake characterized by low arousal and cognitive impairment, and evening chronotypes experience greater sleep inertia. Therefore, difficulty awakening may explain the relationship between evening chronotype and psychiatric disorders by acting as a biomarker of circadian misalignment. In analyzing the longitudinal incidence of psychiatric disorders in the UK Biobank (n = 496,820), we found that evening chronotype predicted increased incidence of major depressive disorder, schizophrenia, generalized anxiety disorder and bipolar disorder. Crucially, this effect was dependent on sleep inertia, which was a much stronger predictor of these disorders, such that evening types without sleep inertia were at no higher risk as compared to morning types. Longitudinal analyses of suicide and depressed mood (CES-D score) in the Older Finnish Twin Cohort (n = 23,854) replicated this pattern of results. Twin and genome-wide association analyses of difficulty awakening identified the trait to be heritable (Twin H2 = 0.40; SNP h2 = 0.08), enriched for circadian rhythms genes and have substantial shared genetic architecture with chronotype. Marginal and conditional Mendelian randomization analyses mirrored the epidemiological results, such that the causal effect of evening chronotype on psychiatric disorders was driven by shared genetic architecture with difficulty awakening. In contrast, difficult awakening was strongly causally associated with psychiatric disorders independently of chronotype. Psychiatric disorders were only weakly reverse causally linked to difficult awakening. Collectively, these results challenge the notion that evening chronotype is a risk factor for psychiatric disorders per se, suggesting instead that evening types are at greater risk for psychiatric disorders due to circadian misalignment, for which sleep inertia may be acting as a biomarker.

Personal light exposure patterns and incidence of type 2 diabetes: analysis of 13 million hours of light sensor data and 670,000 person-years of prospective observation.

Background: Light at night disrupts circadian rhythms, and circadian disruption is a risk factor for type 2 diabetes. Whether personal light exposure predicts diabetes risk has not been demonstrated in a large prospective cohort. We therefore assessed whether personal light exposure patterns predicted risk of incident type 2 diabetes in UK Biobank participants, using ∼13 million hours of light sensor data. Methods: Participants (N = 84,790, age (M ± SD) = 62.3 ± 7.9 years, 58% female) wore light sensors for one week, recording day and night light exposure. Circadian amplitude and phase were modeled from weekly light data. Incident type 2 diabetes was recorded (1997 cases; 7.9 ± 1.2 years follow-up; excluding diabetes cases prior to light-tracking). Risk of incident type 2 diabetes was assessed as a function of day and night light, circadian phase, and circadian amplitude, adjusting for age, sex, ethnicity, socioeconomic and lifestyle factors, and polygenic risk. Findings: Compared to people with dark nights (0-50th percentiles), diabetes risk was incrementally higher across brighter night light exposure percentiles (50-70th: multivariable-adjusted HR = 1.29 [1.14-1.46]; 70-90th: 1.39 [1.24-1.57]; and 90-100th: 1.53 [1.32-1.77]). Diabetes risk was higher in people with lower modeled circadian amplitude (aHR = 1.07 [1.03-1.10] per SD), and with early or late circadian phase (aHR range: 1.06-1.26). Night light and polygenic risk independently predicted higher diabetes risk. The difference in diabetes risk between people with bright and dark nights was similar to the difference between people with low and moderate genetic risk. Interpretation: Type 2 diabetes risk was higher in people exposed to brighter night light, and in people exposed to light patterns that may disrupt circadian rhythms. Avoidance of light at night could be a simple and cost-effective recommendation that mitigates risk of diabetes, even in those with high genetic risk. Funding: Australian Government Research Training Program.

Higher central circadian temperature amplitude is associated with greater metabolite rhythmicity in humans.

Robust circadian rhythms are essential for optimal health. The central circadian clock controls temperature rhythms, which are known to organize the timing of peripheral circadian rhythms in rodents. In humans, however, it is unknown whether temperature rhythms relate to the organization of circadian rhythms throughout the body. We assessed core body temperature amplitude and the rhythmicity of 929 blood plasma metabolites across a 40-h constant routine protocol, controlling for behavioral and environmental factors that mask endogenous temperature rhythms, in 23 healthy individuals (mean [± SD] age = 25.4 ± 5.7 years, 5 women). Valid core body temperature data were available in 17/23 (mean [± SD] age = 25.6 ± 6.3 years, 1 woman). Individuals with higher core body temperature amplitude had a greater number of metabolites exhibiting circadian rhythms (R2 = 0.37, p = .009). Higher core body temperature amplitude was also associated with less variability in the free-fitted periods of metabolite rhythms within an individual (R2 = 0.47, p = .002). These findings indicate that a more robust central circadian clock is associated with greater organization of circadian metabolite rhythms in humans. Metabolite rhythms may therefore provide a window into the strength of the central circadian clock.

Perfect Enough to Sleep? Perfectionism and Actigraphy-Determined Markers of Insomnia.

OBJECTIVES: Perfectionism is an important factor in insomnia development and maintenance. Previous studies exploring the relationship between perfectionism and insomnia have predominantly relied on self-reported sleep measures. Therefore, this study sought to assess whether actigraphy-measured sleep parameters were associated with perfectionism. METHODS: Sixty adults (85% females, mean age 30.18 ± 11.01 years) were sampled from the Australian general population. Actigraphy-derived objective sleep measures, subjective sleep diary measures, the Frost Multidimensional Perfectionism Scale (FMPS), Hewitt-Flett Multidimensional Perfectionism Scale (HFMPS) and Depression, Anxiety and Stress Scale 21 (DASS-21) were collected. RESULTS: High perfectionism levels were associated with poor sleep, but these relationships differed between objective and subjective measures. Perfectionism via FMPS total score and subscales of Concern over Mistakes, Doubts about Actions, Personal Standards and Self-oriented Perfectionism correlated with subjective sleep onset latency and sleep efficiency with moderate effects (r = .26 to .88). In contrast, perfectionism via HFMPS total score and subscales of Socially Prescribed Perfectionism and Parental Expectations predicted objective sleep onset latency and sleep efficiency. Additionally, stress mediated the relationships between objective sleep efficiency and Concern over Mistakes and Doubts about Actions. CONCLUSIONS: Perfectionism demonstrated stronger associations with subjective than objective sleep measures. Higher Parental Expectations and Socially Prescribed Perfectionism may increase one's vulnerability to objectively measured poor sleep. Therefore, perfectionism may be important in preventing and treating insomnia.

The interrelationships between sleep regularity, obstructive sleep apnea, and hypertension in a middle-aged community population.

STUDY OBJECTIVES: Little is known about the interrelationships between sleep regularity, obstructive sleep apnea (OSA) and important health markers. This study examined whether irregular sleep is associated with OSA and hypertension, and if this modifies the known association between OSA and hypertension. METHODS: Six hundred and two adults (age mean(SD) = 56.96(5.51) years, female = 60%) from the Raine Study who were not evening or night shift workers were assessed for OSA (in-laboratory polysomnography; apnea-hypopnea index ≥ 15 events/hour), hypertension (doctor diagnosed, or systolic blood pressure ≥140 mmHg and/or diastolic ≥90 mmHg) and sleep (wrist actigraphy for ≥5 days). A sleep regularity index (SRI) was determined from actigraphy. Participants were categorized by tertiles as severely irregular, mildly irregular, or regular sleepers. Logistic regression models examined the interrelationships between SRI, OSA and hypertension. Covariates included age, sex, body mass index, actigraphy sleep duration, insomnia, depression, activity, alcohol, smoking, and antihypertensive medication. RESULTS: Compared to regular sleepers, participants with mildly irregular (OR 1.97, 95% confidence intervals [CI] 1.20 to 3.27) and severely irregular (OR 2.06, 95% CI: 1.25 to 3.42) sleep had greater odds of OSA. Compared to those with no OSA and regular sleep, OSA and severely irregular sleep combined had the highest odds of hypertension (OR 2.34 95% CI: 1.07 to 5.12; p for interaction = 0.02) while those with OSA and regular/mildly irregular sleep were not at increased risk (p for interaction = 0.20). CONCLUSIONS: Sleep irregularity may be an important modifiable target for hypertension among those with OSA.

Sleep regularity is a stronger predictor of mortality risk than sleep duration: A prospective cohort study.

Abnormally short and long sleep are associated with premature mortality, and achieving optimal sleep duration has been the focus of sleep health guidelines. Emerging research demonstrates that sleep regularity, the day-to-day consistency of sleep-wake timing, can be a stronger predictor for some health outcomes than sleep duration. The role of sleep regularity in mortality, however, has not been investigated in a large cohort with objective data. We therefore aimed to compare how sleep regularity and duration predicted risk for all-cause and cause-specific mortality. We calculated Sleep Regularity Index (SRI) scores from > 10 million hours of accelerometer data in 60 977 UK Biobank participants (62.8 ±â€…7.8 years, 55.0% female, median[IQR] SRI: 81.0[73.8-86.3]). Mortality was reported up to 7.8 years after accelerometer recording in 1859 participants (4.84 deaths per 1000 person-years, mean (±SD) follow-up of 6.30 ±â€…0.83 years). Higher sleep regularity was associated with a 20%-48% lower risk of all-cause mortality (p < .001 to p = 0.004), a 16%-39% lower risk of cancer mortality (p < 0.001 to p = 0.017), and a 22%-57% lower risk of cardiometabolic mortality (p < 0.001 to p = 0.048), across the top four SRI quintiles compared to the least regular quintile. Results were adjusted for age, sex, ethnicity, and sociodemographic, lifestyle, and health factors. Sleep regularity was a stronger predictor of all-cause mortality than sleep duration, by comparing equivalent mortality models, and by comparing nested SRI-mortality models with and without sleep duration (p = 0.14-0.20). These findings indicate that sleep regularity is an important predictor of mortality risk and is a stronger predictor than sleep duration. Sleep regularity may be a simple, effective target for improving general health and survival.

Causal Association Between Subtypes of Excessive Daytime Sleepiness and Risk of Cardiovascular Diseases.

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 ß=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.

Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health.

Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.

Attitudes Towards Sleep as a Time Commitment are Associated with Sleep Regularity.

Objective: Irregular sleep-wake patterns are associated with poor health outcomes. However, factors that lead individuals to adopt more regular sleep-wake patterns are not well understood. This study aimed to (i) examine the relationship between sleep regularity and attitudes toward sleep in undergraduates; (ii) test an intervention to improve sleep regularity based on personalized feedback; and (iii) investigate whether changes in attitudes toward sleep associate with improved sleep regularity.Methods: Sleep-wake timing of 45 students (19.7 ± 1.8 years) was monitored daily over two weeks using an app-based diary. The least regular sleepers, calculated using the Sleep Regularity Index (SRI ≤ 81.4; N = 22), completed a four-week randomized control intervention (RCI) designed to improve sleep regularity. The Charlotte Attitudes Toward Sleep (CATS) scale was administered at baseline and post-RCI, with subscales measuring attitudes toward sleep as a time commitment (Time), and as a beneficial/enjoyable behavior (Benefits).Results: CATS Time was positively associated with SRI at baseline (r2 = 0.16, p =.006) and during the four-week RCI (r2 = 0.29, p =.01). CATS Benefits was not associated with SRI but was associated with sleep quality. There was no significant improvement in SRI during the intervention. The relationship between change in CATS Time and change in SRI (baseline vs. RCI) differed between intervention and control groups (r2 = 0.27, p =.03).Conclusions: Attitudes toward sleep as a time commitment are associated with sleep regularity and should be considered as a target in future interventions aiming to improve sleep regularity.