Journal of Sleep Research最新文献

Insomnia disorder (ID) frequently coexists with substantial psychiatric comorbidity, particularly anxiety and depression. The neurobiological mechanisms underlying the association between ID and emotional dysregulation remain incompletely understood. The locus coeruleus (LC), a pontine nucleus within the ascending reticular activating system, plays a crucial role in sleep-wake regulation and emotional processing. Here, we acquired simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) data from 37 patients with ID and 30 healthy controls (HCs) during their nocturnal sleep. Group-by-stage interactions in LC-based functional connectivity (FC) were assessed using a linear mixed-effects model. Associations were evaluated between FC patterns and the Pittsburgh sleep quality index (PSQI), the self-rating depression scale (SDS) and the self-rating anxiety scale (SAS). Significant group-by-stage interactions were observed in multiple brain regions, including the cingulate cortex, right insular cortex, left temporal cortex and left insular cortex. Post hoc analyses revealed that patients with ID exhibited significantly enhanced FC between the LC and cingulate cortex during N2 sleep compared to HCs (p = 0.023). In the pooled sample, N2-specific LC-cingulate cortex connectivity strength demonstrated significant positive correlations with both SDS scores (r = 0.337, p = 0.018) and PSQI scores (r = 0.401, p = 0.003). In conclusion, the observed alterations in LC-cingulate cortex FC during N2 sleep suggest a distinct neural circuit that may underlie the dysregulation of emotional processing in ID. These findings may provide insights into neurobiological mechanisms in ID.

Sleep disorders such as obstructive sleep apnea (OSA) may be influenced by environmental exposures, yet the contribution of indoor microbial communities is not well understood. In this study, we examined whether the composition and load of airborne bacteria in bedrooms were associated with the Multivariable Apnea Prediction (MAP) index, a validated indicator of OSA risk. Bedroom air was sampled using electrostatic dust fall collectors in five Nordic centres participating in ECRHS III. Dust was analysed for bacterial load, endotoxin levels, and microbial composition using qPCR, LAL assay, and 16S rRNA sequencing. Associations between microbial exposures and MAP index were assessed using linear regression and categorical MAP cutoffs (≥ 0.5 and ≥ 0.7) adjusting for environmental factors. Bacterial community composition differed significantly between MAP groups, and participants with MAP ≥ 0.7 showed higher bacterial loads. However, alpha diversity and endotoxin levels did not vary by MAP category. A total of 35 bacterial genera were associated with MAP scores; taxa enriched in individuals with higher MAP values were primarily anaerobic and human-associated, whereas negatively associated genera were mostly aerobic and environmental. These findings suggest that the bedroom microbiome may carry a distinct microbial signature related to elevated OSA risk, potentially reflecting or contributing to sleep-disordered breathing.

Risk stratification for patients with end-stage heart failure (HF) awaiting heart transplantation (HTX) is crucial. Sleep-disordered breathing (SDB) is a prevalent comorbidity, yet the impact of its resultant hypoxemic burden remains unclear in this population. We investigated the prognostic impact of nocturnal hypoxemic burden in patients with end-stage HF awaiting HTX. We prospectively enrolled 101 patients with end-stage HF listed for HTX at a single centre. Baseline polygraphy quantified nocturnal hypoxemic burden (time with SpO2 < 90%; t90). The primary endpoint was a 5-year composite of all-cause mortality or left ventricular assist device (LVAD) implantation. Multivariable Cox proportional hazards models were used for adjustment. During 5-year follow-up, 24 patients reached the primary endpoint. The primary finding was a significant, dose-response relationship between t90 (analysed as a continuous variable) and the primary endpoint (p < 0.001). In a multivariable Cox model adjusted for glomerular filtration rate (GFR) and left ventricular ejection fraction (LVEF), each 30-min increase in t90 was associated with a 29% increase in hazard (Adjusted HR: 1.29, 95% CI: 1.14-1.47, p < 0.001). A t90 of ≥ 180 min was identified as a clinical threshold of high risk, conferring a > 5-fold increase in hazard (Adjusted HR: 5.18, 95% CI: 1.69-15.81, p = 0.004). The cumulative duration of nocturnal hypoxemic burden is a powerful, independent predictor of death or LVAD implantation in patients with end-stage HF. Routine assessment of hypoxemic burden should be considered for risk stratification in patients awaiting heart transplantation. Trial Registration: ClinicalTrials.gov: NCT03026634.

In the literature exploring the associations between problematic social media use (SMU) and sleep, the majority of studies focus on problematic SMU as a predictor of poorer sleep outcomes. There is currently a scarcity of empirical investigation of the reverse causal direction. Therefore, the aim of this study was to investigate the impact of sleep (insomnia and sleep quality) on problematic social media use and the mediating role of motives for SMU. The eMediate study participants (young adult social media users from Bangladesh) who completed four surveys of SMU, sleep, and mental health at three-month intervals were included (n = 426, 49.8% female, mean age = 22.61 ± 1.83 years). Multilevel mediation analyses were conducted to examine the impact of sleep problems on problematic social media use through motives for SMU. Sleep problems significantly predicted SMU for coping, conforming, escapism, social support seeking, and decreasing negative emotions motives, as well as problematic social media use. Motives mediated 41% of the effect of insomnia symptoms and 71% of the effect of poor sleep quality on problematic social media use. SMU for coping and escapism motives mediated the associations between sleep problems and subsequent problematic social media use. SMU for coping with sleep problems and escaping from associated worries arising from sleep problems and real-life difficulties may reinforce use by providing short-term relief and leading to reliance on SMU.

Slow waves and sleep spindles characterise non-rapid eye movement (NREM) sleep and support cognitive and plasticity-related functions. While their stability across nights is well established, less is known about their consistency across daytime naps. Nineteen healthy young adults (20-27 years) underwent two 90-min afternoon naps, interleaved by 1 week, under polysomnographic recording. Slow waves and sleep spindles were detected using standardised algorithms, and their key features, as well as NREM spectral power, were extracted from N2 sleep and assessed for nap-to-nap reliability using intraclass correlation coefficients. Temporal coupling between spindles and slow wave events was also evaluated. Spectral power showed good consistency in the sigma band and moderate consistency in the delta band. Spindle frequency, density, and duration were highly reliable, particularly for fast spindles. Slow wave density and slope showed moderate stability, while amplitude and duration were less stable and not consistent, respectively. The phase of slow wave-spindle coupling did not show consistency between naps. Overall, some specific features of NREM sleep, particularly those related to spindles, appear relatively stable across naps and may reflect trait-like aspects of individual sleep physiology. In contrast, coupling dynamics appear more variable and influenced by state-related factors.

Sleep disturbance may be a modifiable risk factor for neurocognitive decline in critically ill children. Polysomnography, the gold standard for sleep analysis, is time and cost-intensive and not commonly available in the paediatric intensive care unit (PICU). Electroencephalography (EEG) also provides measurements of sleep and is more commonly used. We devised a novel EEG-based scoring system to categorise electrographic sleep and assessed its feasibility. In this retrospective observational cohort study across two PICUs, EEGs performed in patients aged 6 months to 18 years were analysed for sleep using a four-category system: category 1-invariable background, no state cycling or reactivity; category 2-reactivity and variability present, no discernable sleep architecture; category 3-discernable sleep architecture, abnormal pattern of sleep cycle; and category 4-normal sleep architecture and pattern. We evaluated 51 subjects. Seven patients (14%) were classified as category 1, 11 patients (22%) as category 2, 24 patients (47%) as category 3, and 9 patients (18%) as category 4. For those patients in whom sleep was detected (categories 3 and 4), N2 sleep was detected in 33 (100%) of patients, N3 sleep was detected in 24 (73%), and REM sleep was identified in 13 (39%). In this small cohort study across two centres, paediatric neurologists were able to qualify sleep in critically ill children using a novel EEG-based scoring system. If clinically validated, this scoring system could facilitate exploration of modifiable risk factors leading to sleep disruption in the PICU.

The ability to stay awake is crucial in life and can be compromised by insufficient sleep and medical conditions. Measuring alertness is important for evaluating driving ability and the Oxford Sleep Resistance (OSLER) test may provide an easy way for assessment. The study population included 40 professional truck drivers who participated in the Maintenance of Wakefulness Test (MWT) between 2000 and 2002. Half of these subjects had sleep latency less than 33 min in the MWT. All subjects completed a questionnaire, underwent interviews, participated in both the MWT and OSLER test on consecutive days and filled in the Karolinska Sleepiness Scale (KSS) before each MWT and OSLER test session. Altogether, 39 subjects successfully completed both the MWT and OSLER test in random order. The MWT took place after polysomnography. The mean sleep latency in the MWT was 38.7 min while the mean sleep latency in the OSLER test was 38.9 min. If the sleep latency in the OSLER test exceeded 33 min, it was highly likely that the sleep latency in the MWT would also be normal (> 33 min). The OSLER test appears to be a reliable objective measure for assessing the ability to stay awake in professional drivers and is easier to administer than the MWT, which still remains the gold standard.

Obstructive sleep apnea (OSA) has been linked to cortical atrophy and increased risk of neurodegeneration, a process potentially mediated by neurometabolic dysregulation. Recent work using high temporal-resolution metabolic MRI found greater changes in the cerebral metabolic rate of oxygen consumption (CMRO₂) during cued breath-hold stimuli simulating spontaneous apneas in OSA patients than in healthy people. Here, we conducted a secondary analysis on this work to assess whether the observed neurometabolic responses were associated with grey matter volume fraction. We examined previously collected data from OSA patients matched to non-OSA participants by age and sex to evaluate associations between MRI-based measures of neurometabolism and grey matter volume. Grey matter volume fraction (GMVF) was computed by segmenting T1-weighted structural images and regressing out age effects in OSA patients relative to the age-matched non-OSA participants. We then examined the relationship between GMVF, apnea-hypopnea index (AHI), and neurometabolic responses of cerebral blood flow (CBF), venous oxygen saturation (SvO₂), and CMRO₂ in response to breath-hold stimuli. OSA severity, expressed in terms of AHI, was negatively associated with GMVF in both OSA and non-OSA reference subjects after controlling for age. Incorporating the quantitative measures of brain oxygen metabolism showed breath-hold responses in CBF and SvO₂ to be positively associated with GMVF. However, changes in CMRO₂ were not significantly associated with age-normalized GMVF. The findings suggest that noninvasive global measures of brain oxygen metabolism may serve as quantitative markers of neural health. Further research is warranted to explore these measures and neurodegenerative risk in OSA.

Poor sleep and emotional wellbeing, which often decline during puberty, are associated with declines in metabolic health and are key determinants of childhood obesity. The aim of the study was to explore bidirectional associations between sleep, emotional wellbeing and obesity from ages 8 to 14 using the Growing Up in Scotland cohort. Secondary analyses were conducted on data from sweeps 7-10 (ages 8-14). Sleep duration was caregiver-reported at age 8 and self-reported at 14. Obesity was assessed using BMI percentiles (BMIp), derived from objective height and weight at ages 8, 10, 12 and 14. Emotional wellbeing was assessed using the Strengths and Difficulties Questionnaire caregiver-report at 10 and 12 years, and self-report at 14 years. Pearson correlations and adjusted regressions examined associations between sleep, BMIp and emotional wellbeing from ages 8 to 14. Analyses included 4157 participants (50.2% male). Shorter sleep at 8 years was associated with higher BMIp at 12 years (β = -0.172, CI (95%) = -0.335, -0.116, p < 0.001) and poorer emotional wellbeing at 10 (β = -0.120, CI (95%) = -0.179, -0.034, p < 0.001) and 12 years (β = -0.101, CI (95%) = -0.164, -0.026, p < 0.001). Poorer emotional wellbeing at 10 (β = -0.116, CI (95%) = -0.232, -0.093, p < 0.001) and 12 years (β = -0.194, CI (95%) = -0.328, -0.174, p < 0.001) predicted shorter sleep at 14 years. Higher BMIp at 8 years was associated with shorter sleep at 14 years (β = -0.182, CI (95%) = -0.359, -0.111, p < 0.001). Poorer emotional wellbeing at 10 years was associated with higher BMIp at 14 years (β = 0.142, CI (95%) = 0.074, 0.629, p = 0.13). Bidirectional associations emerged between short sleep and emotional wellbeing and higher BMIp. Poor emotional wellbeing was associated with subsequent obesity; but not bidirectionally. These interactions should inform the design of health interventions for 8-14-year-olds.

Sleep is essential for human functioning, but little attention has been paid to the interplay between sleep and maladaptive personality traits. We examined genetic and environmental associations between sleep and four maladaptive domains (MDs)-Negative Affectivity, Detachment, Disinhibition, and Psychoticism-within the framework of the DSM-5 Alternative Model of Personality Disorders (AMPD). We estimated phenotypic, genetic, and environmental variance and covariance using a twin study approach. Phenotypically, the four MDs showed small associations with sleep duration, medium associations with sleep efficiency, and large associations with sleep quality. A similar pattern was observed in genetic correlations, with Negative Affectivity and Detachment consistently showing the strongest associations. Multilevel Regression results based on the co-twin control design indicated that genetic factors only partially account for these relations. Whilst previous research has extensively focused on adaptive personality traits predicting sleep, our study highlights the importance of maladaptive traits as meaningful predictors of sleep health.