Sleep最新文献

We aimed to test the association between sleep-related polygenic scores (PGSs) and accelerometer-based sleep metrics among Brazilian adolescents and to evaluate potential mechanisms underlying the association through the enrichment of obesity, and cortisol pathway-specific polygenic scores (PRSet). Utilizing data from The 2004 Pelotas (Brazil) Birth Cohort, sleep time window and sleep efficiency were measured at the 11-year-old follow-up using ActiGraph accelerometers. Three sleep PGSs were developed based on the most recent genome-wide association study of accelerometer-based sleep measures. PRSet, calculated using variants linked to body mass index (BMI) and plasmatic cortisol concentration, aimed to assess pleiotropic effects. Linear regression models, adjusted for sex and the first 10 principal components of ancestry, were employed to explore the impact of sleep PGS and specific-PRSet on sleep phenotypes. The number of nocturnal sleep episodes-PGS was positively associated with sleep time window (β = 2.306, SE: 0.92, p = .011). Nocturnal sleep episodes were also associated with sleep time window when restricted to BMI-PRSet (β = 2.682, SE: 0.912, competitive p = .003). Both the number of sleep episodes and sleep time window cortisol-PRSets were associated (β = .002, SE: 0.001, p = .013; β = .003, SE: 0.001, p = .003, respectively) and exhibited enrichment in molecular pathways (competitive p = .011; competitive p = .003, respectively) with sleep efficiency. Sleep polygenetic components observed in European adults may partially explain the accelerometer-based sleep time window in Brazilian adolescents. Specific BMI molecular pathways strengthened the association between sleep PGS and sleep time window, while the cortisol concentration pathway had a significant impact on the genetic liability for sleep efficiency. Our results suggest genetic overlap as a potential etiological pathway for sleep-related comorbidities, emphasizing common genetic mechanisms.

The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful. Such a capability would allow for longitudinal data collection in patients' homes, informing our understanding of sleep and its interaction with various diseases and their therapeutic responses, both in clinical trials and routine care. In this article, we develop an advanced machine-learning algorithm for passively monitoring sleep and nocturnal breathing from radio waves reflected off people while asleep. Validation results in comparison with the gold standard (i.e. polysomnography; n = 880) demonstrate that the model captures the sleep hypnogram (with an accuracy of 80.5% for 30-second epochs categorized into wake, light sleep, deep sleep, or REM), detects sleep apnea (AUROC = 0.89), and measures the patient's Apnea-Hypopnea Index (ICC = 0.90; 95% CI = [0.88, 0.91]). Notably, the model exhibits equitable performance across race, sex, and age. Moreover, the model uncovers informative interactions between sleep stages and a range of diseases including neurological, psychiatric, cardiovascular, and immunological disorders. These findings not only hold promise for clinical practice and interventional trials but also underscore the significance of sleep as a fundamental component in understanding and managing various diseases.

Study objectives: The effectiveness of advanced emergency braking systems (AEBS) in preventing drowsy driving-related truck collisions remains unclear. We aimed to evaluate the damage-mitigation effect of AEBS on drowsy driving-related collisions involving large trucks using collision rate and damage amount.

Methods: Data collected by a Japanese transportation company from 1699 collisions involving 31 107 large trucks over 7 years were analyzed post hoc. The collision rate (number of trucks with collisions/total number of trucks) and damage amount (total amount of property damage and personal injury) were compared based on whether the collisions were caused by drowsy or nondrowsy driving and whether the trucks were equipped with AEBS or not.

Results: For all and nondrowsy driving-related collisions, the collision rate for the 12 887 trucks with AEBS (1.62 and 1.20 collisions/truck/7 years, respectively) was significantly lower than that for the 18 220 trucks without AEBS (1.94 and 1.56 collisions/truck/7 years, respectively; p = .04 and p = .008, respectively). However, for drowsy driving-related collisions, the collision rate did not significantly differ between trucks with and without AEBS. The damage amount in neither type of collision (drowsy vs. nondrowsy) significantly differed between trucks with and without AEBS.

Conclusions: Regarding the collision rate of large trucks, AEBS was effective in nondrowsy driving-related collisions, but not in collisions involving drowsy driving. The damage amount was not mitigated for trucks with and without AEBS regardless of the collision type. The limited effect of AEBS for damage mitigation suggests the need for combined use with other safety-support systems that intervene in driving operations.

Study objectives: Sleep disorders and psychiatric disorders frequently coexist and interact, yet the shared genetic basis linking these two domains remains poorly understood.

Methods: We investigated the genetic correlation and overlap between seven sleep/circadian traits and three psychiatric disorders at the level of genome-wide association studies (GWAS), utilizing LDSC, HDL, and GPA. To identify potential polygenic single nucleotide variations (SNVs) within each trait pair, we used PLACO, while gene-level analyses were performed using MAGMA and POPS. Furthermore, the functions and biological mechanisms, enriched phenotypes, tissues, cellular features, and pathways were thoroughly investigated using FUMA, deTS, and enrichment analyses at the biological pathway level.

Results: Our study revealed extensive genetic associations and overlaps in all 21 trait pairs. We identified 18 494 SNVs and 543 independent genomic risk loci, with 113 confirmed as causative through colocalization analysis. These loci collectively spanned 196 unique chromosomal regions. We pinpointed 43 distinct pleiotropic genes exhibiting significant enrichment in behavioral/physiological phenotypes, nervous system phenotypes, and brain tissue. Aberrations in synaptic structure and function, neurogenesis and development, as well as immune responses, particularly involving the MAPK pathway, emerged as potential underpinnings of the biology of sleep/circadian traits and psychiatric disorders.

Conclusions: We identified shared loci and specific sets of genes between sleep/circadian traits and psychiatric disorders, shedding light on the genetic etiology. These discoveries hold promise as potential targets for novel drug interventions, providing valuable insights for the development of therapeutic strategies for these disorders.

Study objectives: The Psychomotor Vigilance Task (PVT) is widely recognized as the gold standard for measuring vigilance, providing a rapid and objective measure of this state. While driving simulations are also used, they typically require longer administration times. This study examines the sensitivity of driving simulation variables to sleep deprivation throughout the task. The aim is to determine the shorter duration at which performance declines can be observed. A secondary goal is to compare driving simulation and PVT variables' sensitivity in detecting sleep deprivation.

Methods: 43 participants (22 males; aged 46.7 ± 17.8 years) completed a 90-minute driving simulation and a 10-minute PVT under two conditions (normal sleep and partial sleep deprivation of 3.5 hours). Signed-rank Wilcoxon tests and effect sizes were computed for variables from both tasks. Effect sizes were calculated for each 10-minute interval to assess sensitivity over time.

Results: All the variables showed sensitivity to sleep deprivation. The largest effect sizes were observed in the driving simulation and specifically for the standard deviation of lateral position (SDLP) (r=0.73) and the standard deviation of steering wheel movement (SDSW) (r=0.73). A large effect size for the SDLP (r=0.71) was observed after only 20 minutes of driving. For the 10-minute PVT, the highest effect size was observed for the number of lapses (r=0.52).

Conclusion: Driving-related variables are highly sensitive to sleep deprivation while providing continuous performance measurements. The SDLP is a particularly sensitive variable even with a reduced driving time of 20 minutes, suggesting that driving simulation tasks can be effectively shortened to 20 minutes.

Study objectives: To determine the association between adherence to positive airway pressure and healthcare costs among a national sample of older adults with comorbid OSA and common chronic conditions.

Methods: Our data source was a random sample of Medicare administrative claims for years 2016-2019. Inclusion criteria included age >65 years and new diagnosis of OSA. Exclusion criteria included evidence of prior OSA treatment during the 12 months prior to the index date, active cancer, or end-stage renal disease. OSA was defined using physician-assigned diagnostic codes. Common chronic conditions included chronic obstructive pulmonary disease, congestive heart failure, depression, hypertension, type 2 diabetes mellitus, obesity, and stroke. Based on Medicare policy, individuals were classified as adherers, non-adherers, or non-initiators. Risk adjustment was based on the CMS-HCC approach developed by the Centers for Medicaid and Medicare Service specifically to estimate anticipated costs. To examine the impact of PAP adherence on costs, we employed a weighted DID regression framework to account for baseline variations in health status and other confounding factors.

Results: Participants included 28,220 Medicare beneficiaries with comorbid OSA. Of these, 45% were adherent to PAP, 10% were non-adherent, and 44% did not initiate PAP. Relative to non-initiators, beneficiaries who initiated PAP displayed $195 reduced per-member per-month costs over 24 months. This finding remained consistent across all seven medical and psychiatric subgroups, as well as among individuals with multimorbidity.

Conclusions: In this national analysis of Medicare beneficiaries with common chronic conditions, PAP adherence was associated with reduced costs over 24 months.

Study objectives: The majority of patients with insomnia exhibit abnormal sleep in objective testing (e.g. decreased sleep duration, decreased slow wave sleep [SWS]). Previous studies have suggested that some of these objective measures of poor sleep, such as decreased sleep duration, are associated with a higher risk of hypertension in insomnia. We examined the relationship between SWS and morning and evening blood pressure (BP) levels in patients with clinically diagnosed insomnia.

Methods: A total of 229 normal sleepers and 1378 insomnia patients were included in this study. Insomnia was defined based on standard diagnostic criteria with symptoms lasting ≥6 months. All participants underwent in-laboratory polysomnography. Patients were classified into quartiles of percent SWS. Evening and morning hypertension were defined using BP measurements taken in the evening before and in the morning after polysomnography, respectively. Multivariable logistic regression models were used to assess the relationship between insomnia, SWS, and hypertension.

Results: Insomniacs with <3.5% SWS (OR 3.27, 95% confidence intervals [CI]: 1.31 to 7.66) and those with 3.5%-10.2% SWS (OR 2.38, 95% CI: 1.28 to 5.91) had significantly greater odds of morning hypertension compared to normal sleepers. No associations were seen in insomnia with 10.2%-15.8% SWS and with >15.8% SWS. Significant effect modifications by sex (p = .043) were found, as decreased SWS was associated with morning hypertension only in men. Odds of evening hypertension were not significantly associated with SWS.

Conclusions: Decreased SWS is associated with morning hypertension in a dose-dependent manner in insomnia, especially in men.

Study objectives: Obstructive sleep apnea (OSA) is more prevalent in men and older adults. Few studies have explored variations in pathological endotypic traits by age and sex using a large patient sample, offering insights into the development of the disease. Our study aims to examine how endotype characteristics of OSA vary across ages in different sex.

Methods: A cross-sectional study was conducted, enrolling 2296 adult patients referred for in-laboratory diagnostic polysomnography at a single sleep center in Taiwan. Among them, 1374 had an apnea-hypopnea index ≥5. Using the "Phenotyping Using Polysomnography" method, we estimated four endotypic traits-arousal threshold, upper airway collapsibility, loop gain, and upper airway muscle compensation. Demographic and polysomnographic characteristics were compared between sexes and age groups. Generalized linear regression and generalized additive models were employed to explore the associations of sex and age with endotypic traits.

Results: Men with OSA exhibited higher collapsibility and lower compensation than women (difference: 4.32 %eupnea and 4.49 %eupnea, respectively). Younger patients with OSA had a higher prevalence of obesity, more snoring symptoms, and lower loop gain compared to older patients. For men, age was correlated with increased collapsibility, increased loop gain, and decreased arousal threshold after 37 years old. Whereas in women, endotypic traits were not associated with age, except for an increase in loop gain with advancing age.

Conclusions: Personalized treatment options for OSA should take into consideration age and sex. Reducing loop gain could be a treatment objective for older patients with OSA.