Sleep最新文献

Current treatments for narcolepsy type 1 (NT1) have little impact on psychiatric, cognitive, and metabolic comorbidities. Here, we evaluated the feasibility, safety, and efficacy of a prospective exercise training (ET) program on sleep-related symptoms and comorbidities in NT1. Sedentary adult with NT1 participated in a 6-week supervised ET program followed by a 18-week self-directed program. Outcomes included the Narcolepsy Severity Scale (NSS), Hospital Anxiety and Depression Scale, Insomnia Severity Index (ISI), cardiometabolic parameters (body mass index [BMI], glycemia, insulin, C-reactive protein, lipid panel with insulin resistance [IR] [TG/HDL-C] and cardiovascular risk [Total-C/HDL-C] markers), cardiorespiratory fitness, and attention (Bron/Lyon Attention Stability Test). Wilcoxon tests compared baseline, 6-week, and 6-month data. Among 30 participants (73.3% women, 39.8 ± 13.9 years, BMI = 31.0 ± 5.1 kg/m2), 25 completed the 6-month program. Of the 379 supervised sessions (84.2% attendance), only seven partial cataplexies occurred. At 6 weeks, significant improvements were observed in median[IQR] NSS (-2.0[-4.0;0], p=.046), ISI (-1.0[-3.0;1.0], p=.050), triglycerides (-0.21[-0.46;-0.09]g/L, p=.015), IR (-0.19[-0.46;-0.04], p=.003), cardiorespiratory fitness (+15.0[5.0;20.0]watts, p<.001), and in most attention scores (stability, intensity, reaction time: p<.05). At 6 months, NSS and ISI changes were no longer significant but anxiety (-1.0[-3.0;1.0], p=.041) and depression (-2.0[-4.0;0.0], p=.004) decreased. Improvements in IR (-0.27[-0.44;-0.11], p=.002), triglycerides (-0.2[-0.4;0.0]g/L, p=.033), cardiovascular risk (-0.16[-0.41;-0.02], p=.019), and attention scores (intensity, reaction time, number of errors p<.05) were sustained. VO2max and BMI showed no significant changes. Physical activity is feasible and safe in NT1, enabling improvements in narcolepsy symptoms, anxiety/depression, cognition, and cardiometabolic markers. Larger randomized controlled trials are needed to confirm these findings. Clinical Trial: NARCOSPORT NCT05460052.

Study objectives: Night shifts are commonly used as proxy for circadian disruption (CD) in epidemiological studies. However, other shift types can also cause CD if they interfere with a worker's biological night. We quantified and compared cumulative CD to night shift exposure and assessed their associations with health-related outcomes.

Methods: Shift work exposure was derived from questionnaire data for 42 119 nurses for the period 2012-2017. Cumulative CD was estimated as the total overlap (h) between shift work and preferred sleep-wake times. Pearson's correlation (r) assessed relationships between cumulative CD and night shift exposure. Associations with sleep disturbances, medication use, and overweight were analyzed using Poisson regression.

Results: The median cumulative CD among shift workers was 1674 h over 6 years (interquartile range = 432-3153 h). High CD (≥2809 h) was associated with increased prevalence of sleep problems (incidence rate ratio [IRR] = 1.10, 95% confidence interval [CI] 1.07-1.13), melatonin use (IRR = 1.86; 95% CI 1.70-2.04), sleep medication use (IRR = 1.15; 95% CI 1.01-1.32), and overweight (IRR = 1.04; 95% CI 1.02-1.07). The number of performed night shifts strongly correlated with cumulative CD (r = 0.93), and using night shifts as proxy for CD gave similar results. However, among shift workers who did not perform night shifts, high CD was still associated with increased sleep problems and melatonin use.

Conclusion: Cumulative CD is associated with sleep and health disturbances, even among shift workers who do not perform night shifts, underlining its potential role in disease development. While night shifts remain a practical proxy in large-scale studies, our study highlights the importance of using more nuanced, individualized measures of CD.

Study objectives: Knowledge about how day-to-day variations in sleep affect cognitive performance in real-world contexts is currently limited. This study investigated how daily fluctuations in sleep duration, efficiency, and quality affect next-day processing speed, and tested whether these associations differ between young and older adults.

Methods: A total of 158 young (18-30 years) and 168 older adults (55-75 years) participated in a 21-day intensive longitudinal design. Sleep duration and efficiency were measured using actigraphy, while sleep quality was assessed via sleep diaries. Processing speed was measured using a 60 s smartphone-based Digit Symbol Substitution Task, administered up to eight times per day. Multilevel mixed models tested the within- and between-person effects of sleep duration, sleep efficiency and sleep quality, as well as the effect of age group on processing speed.

Results: Within-person, a sleep duration shorter than their own average (p < .001), and a sleep quality poorer than their own average (p < .05) predicted poorer next-day performance. Between-person differences in sleep duration, sleep efficiency and sleep quality were not significantly associated with processing speed. Older adults showed worse performance than young adults (p < .001), but the effect of daily sleep fluctuations on performance did not significantly vary between age groups.

Conclusions: Daily fluctuations in sleep duration and sleep quality are linked to processing speed in young and older adults in real-world contexts. Results suggest that within-person, day-to-day variations in sleep may be more important than between-person differences. Maintaining an adequate sleep duration each day may help prevent cognitive impairments in daily functioning across age groups.

Study objectives: This cross-sectional study aimed to develop a tool to predict sleep bruxism (SB) and estimate the impacts of risk factors found for SB in a personalized manner for each apneic patient.

Methods: A total of 321 individuals with apnea underwent full-night type 1 polysomnography. SB was assessed using electrodes applied to the masseter and chin muscles. Data collected included the apnea and hypopnea index, sleep arousal index, total sleep time, sex, and commonly used medications. SB was defined as experiencing more than two rhythmic masticatory muscle activity events per hour of sleep. Statistical analysis identified variables associated with SB, leading to the creation of a nomogram.

Results: Risk factors for SB in this population included the non-use of thyroid medications, the use of antidepressants, male sex, sleep arousals, total sleep time, and the apnea-hypopnea index. The nomogram enables prediction of SB and assessment of individualized impacts of SB risk factors for each patient.

Conclusions: When SB treatment is required in apneic individuals, fill in the nomogram allows for the assessment of important SB risk factors impacts and the targeting of personalized intervention strategies. SB interventions should involve a multidisciplinary team due to potential connections with systemic disorders. Future studies with longitudinal designs or RCT are essential to validate the nomogram. Statement of Significance When addressing the treatment of sleep bruxism in individuals with apnea, approaches should consider the impacts of some important related risk factors, identified through the individualized use of the nomogram-a novel tool developed by this research group. Additionally, when sleep bruxism is present, it's crucial to screen for associated conditions such as untreated thyroid disorders, obstructive sleep apnea, issues leading to the use of antidepressant medication, and frequent sleep disturbances. Dentists play an essential role in diagnosing potential systemic issues, contributing significantly by identifying signs and symptoms that manifest in the orofacial region.

Study objectives: Insomnia and psychiatric disorders are frequently comorbid and heritable, yet their shared genetic architecture and neurobiological mechanisms remain poorly understood. We investigated the genetic overlap, biological pathways, and brain cell types linking insomnia with 12 psychiatric disorders.

Methods: We analyzed genome-wide association study data from insomnia (Neff = 314,149) and 12 psychiatric disorders (Neff = 12,783-449,855). Genetic architecture was assessed using bivariate MiXeR. Shared loci were identified through conjunctional false discovery rate (conjFDR) and Association analysis based on SubSETs (ASSET). Gene-set enrichment was performed with MAGMA, and cell-type specificity was determined using SEISMIC analysis of single-cell RNA sequencing data from 36 brain cell types.

Results: Significant genetic correlations emerged between insomnia and seven psychiatric disorders: attention-deficit/hyperactivity disorder (ADHD), anorexia nervosa (AN), anxiety disorders (ANX), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). Cross-trait analyses identified 70 shared genomic loci containing 97 candidate single nucleotide polymorphisms (SNPs), including novel associations: 7 with ADHD, 6 with AN, 3 with ANX, 3 with ASD, 5 with BD, 15 with MDD, and 19 with SCZ. Pathway enrichment analysis revealed GABAergic synapse signaling as a central mechanism. Cell-type analysis implicated eight cortical neuron subtypes-four GABAergic interneurons and four glutamatergic neurons. Of 71 genes mapped to shared loci, 33 showed significant expression in these neuronal populations.

Conclusions: Our findings reveal extensive shared genetic architecture between insomnia and psychiatric disorders, converging on cortical GABA-glutamate circuitry dysfunction. These results identify potential therapeutic targets for comorbid conditions and demonstrate how integrating genetic epidemiology with cellular neuroscience can elucidate transdiagnostic mechanisms underlying neuropsychiatric comorbidity, informing precision medicine approaches.