Sleep最新文献

The locus coeruleus (LC) plays important roles in sleep/wake regulation and cognitive functions. LC neurons may be particularly sensitive to neural injury and serve as an early site of accumulation pathological tau in Alzheimer's disease. Obstructive sleep apnea (OSA) creates both chronic intermittent hypoxia and sleep fragmentation as potential insults to differentially sensitive neural populations including the locus coeruleus (LC). Using high field 7T imaging in cognitively normal older adults, we demonstrate that time spent with an oxygen saturation below 90% (T90), a measure of OSA's hypoxic burden, inversely correlates with LC structural integrity and explains significant variance in LC structural integrity after controlling for age, sex, and BMI. In contrast, other sleep variables such as the apnea-hypopnea index (AHI), total sleep time, and sleep efficiency did not contribute significant variance in LC structural integrity in this model. Thus, in the diagnosis of OSA, attention to hypoxic burden variables may be important in risk stratification for LC neural injury. This observation may inform future work determining whether mitigation of the hypoxemic burden from OSA can slow deterioration in LC integrity.

Study objectives: Excessive daytime sleepiness (EDS) has been associated with significant cardiovascular morbidity. Objective sleepiness, as measured by short sleep onset latencies (SOL), has been associated with poor cognitive performance in otherwise healthy individuals who do not complain of EDS, but its association with cardiovascular morbidity has not been explored. Thus, we investigated the association of objective sleepiness without a complaint of EDS with hypertension risk in a large random general population sample.

Methods: From 1741 adults of the Penn State Cohort, 1590 individuals without a complaint of EDS were included in the cross-sectional analysis. From those, 659 subjects without hypertension were followed-up for an average of 7.5 years and were included in the longitudinal analysis. Objective sleepiness was defined as SOL≤7 minutes during overnight 8-hour polysomnography. Prevalent hypertension was defined as either high blood pressure (BP) or medication use, whereas incident hypertension was determined by self-report of receiving treatment for high BP. Binary logistic regression was performed while controlling for multiple potential covariates.

Results: The prevalence and incidence of hypertension was significantly lower in individuals with objective sleepiness than control group (22.1% vs. 32.3% and 8.8% vs. 17.3%, respectively). Objective sleepiness was less likely to be associated with prevalent (OR=0.44; 95%CI=0.23-0.81; p=0.010) or incident (OR=0.31; 95%CI=0.10-0.96; p=0.043) hypertension respectively compared to control group. The combination of objective sleepiness with subjective EDS eliminated the protective effect on hypertension risk.

Conclusions: Our novel and unexpected findings suggest that objective sleepiness without EDS has a protected effect against hypertension risk, a useful finding for practicing clinicians in assessing hypertension risk in their patients.

Study objectives: Conventional sleep staging relies on 30-second epochs, potentially concealing transient sleep stage intrusion and reducing precision. Building on our previous study of mini-epochs, we investigated whether U-Sleep, an existing automatic deep learning-based sleep staging model with high performance in epochs, could be optimized to similar performance level in 5-second mini-epoch scoring, thereby enabling more detailed sleep characterization.

Methods: We created a dataset of 48,000 human-scored 5-second mini-epochs from 100 PSGs. We compared mini-epochs to human-scored epochs before U-Sleep was optimized using transfer learning and evaluated on a test set. Model performance was assessed using F1-scores, confusion matrices, stage distributions and transition rates comparing scorings of the original U-Sleep before, and the optimized U-Sleep after transfer learning to human-scored mini-epochs.

Results: Compared to human-scored epochs, human-scored mini-epochs captured significantly more transitions (1.70/minute vs. 0.21/minute, p<0.001), and significantly more wake (8.4% versus 5.4%), N1 (7.2% versus 5.4%), and N2 (51.8% versus 40.9%), less N3 (15.4% versus 25.2%) and REM sleep (16.7% versus 23.0%) (all p<0.001). Optimizing U-Sleep improved its performance significantly from F1=0.74 to F1=0.81 (p<0.05) and gave increased transition rates in the test set (original U-Sleep: 1.06/minute, optimized U-Sleep: 1.34/minute, human-scored mini-epochs: 1.70/minute). Stage distributions did not differ between optimized U-Sleep's scorings and human-scored mini-epochs.

Conclusion: After optimization, U-Sleep performance in mini-epochs matched the high performance levels previously reported in both human and automated 30-second epoch scoring. This demonstrates the feasibility of precise, automated high resolution sleep staging. Future work should include external validation and application to full-night recordings.

Although partial sleep deprivation affects brain function and results in emotional and subjective sleepiness abnormalities, the changes in the brain functional configurations after partial sleep deprivation and their interaction effects with age remain unclear. We employed Network-Based Statistic-Predict approach to separately assess the behavioral-related brain functional reorganizations patterns in healthy young adults (N = 36, 19 females, 23.53 ± 2.36 years) and healthy older adults (N = 33, 18 females, 68.81 ± 2.41 years) after partial sleep deprivation. And further investigated the changes of segregation, integration, and balance in resting-state brain functional organization from a hierarchical modular perspective using a nested-spectral partition method. Based on edge weights and node strengths, we found that the behavior-related organization patterns recruited more connections within and between canonical resting-state functional networks in younger participants after partial sleep deprivation, shifting the whole brain into a more integrated and less segregated state, especially in the sensorimotor and visual networks. This increase in the number of functional networks was accompanied by a reversed node contribution hierarchy. In contrast, the older participants tend to exhibit nonspecific connectivity patterns after partial sleep deprivation, with reduced integration in almost all typical networks except for the sensorimotor network. These results suggest that partial sleep deprivation leads to the reorganization of widespread functional brain networks and that this effect is age-related. Statement of Significance The patterns of whole-brain functional reorganization induced by partial sleep deprivation across different age groups remain unclear. By combining Network-Based Statistics-Predict analysis and the nested-spectral partition method, we found that partial sleep deprivation leads to a significantly increased number of behavior-related functional networks and deviated toward more integrated in young adults. More importantly, the reversal of node contribution hierarchy in the young group elucidated the network reorganization process, offering direction for identifying biomarkers to predict behavior after partial sleep deprivation. In contrast, older adults exhibit functional specificity degradation and reduced whole-brain network integration after partial sleep deprivation, promoting a more segregated brain state. These findings may provide insights into the neural basis underlying behavioral changes induced by partial sleep deprivation.

Study objectives: Cerebrospinal fluid (CSF) hypocretin-1/orexin-A quantification via radioimmunoassay (RIA) is used for diagnosing narcolepsy type 1(NT1), but its limitations require alternative methods. Using liquid chromatography-mass spectrometry (LC-MS), this study aimed to 1) fully characterize CSF orexin-A fragments detected by the gold standard RIA method, and 2) assess diagnostic relevance of measuring the most prevalent fragment, a 16-mer, in patients with NT1, narcolepsy type 2 (NT2), idiopathic hypersomnia (IH), and nonspecified hypersomnolence (NSH).

Methods: CSF samples were analyzed using RIA and LC-MS in patients with hypersomnolence disorders evaluated at the French Narcolepsy National Reference Center. Fractionation techniques isolated orexin-A and its fragments, which were identified via targeted MS. Statistical analysis compared LC-MS performance against RIA.

Results: CSF samples from 115 patients (54.8% females, mean age 30.4 ± 15.8 years) including 52 with NT1, 6 NT2, 13 IH, and 44 NSH were analyzed by RIA and LC-MS. A 16-mer orexin-A fragment was identified and quantified by LC-MS, with lower levels in NT1. This fragment correlated strongly with RIA-measured orexin-A (r = 0.83, p < .0001) and demonstrated high sensitivity (98.1%) and specificity (85.7%) for diagnosis of NT1. Receiver operating characteristics analyses confirmed the high performance with an area under the curve of 0.975 and an optimal diagnostic cutoff of 10.67 pg/mL for LC-MS.

Conclusions: The 16-mer orexin-A peptide represents a promising biomarker that could in the future help in the diagnosis of central hypersomnolence disorders. The transition from RIA to LC-MS methods for the quantification of 16-mer orexin-A represents a critical advance toward improving diagnostic accuracy and understanding orexinergic dysfunction in sleep disorders.