Sleep最新文献

Sleep is critical for physical, cognitive, and mental health, but how sleep supports these domains likely fluctuates across the lifespan. While traditional observational and experimental study designs-often cross-sectional or limited (two-wave) longitudinal designs-have provided valuable insights, they fall short of capturing the dynamic nature of sleep and its effects over time. To fully understand these complex and evolving relationships, multimethod, multi-time point longitudinal designs are required. These approaches can illuminate the temporal dynamics of sleep and its outcomes, offering stronger and potentially causal conclusions. In this article, we aim to empower sleep scientists, clinicians, and trainees with research methods focused on studying change-methods that can be applied across both observational and experimental designs. To truly advance the field, it is critical to examine sleep throughout the lifespan, from infancy through older adulthood, with repeated and nuanced assessments of sleep and its related outcomes. We outline a variety of statistical analysis approaches and corresponding design considerations that support the rigorous study of change in sleep. Finally, we offer forward-looking recommendations for scientific training, research program evaluation and funding, and the development of research infrastructure and collaborations. Together, these strategies have the potential to propel the field of sleep research forward, generating richer insights and change-based conclusions. Statement of Significance As a field, we are driven by a fundamental question: does sleep temporally precede and cause changes to our physical, mental, and cognitive health? While many existing studies use cross-sectional or limited (two-wave) longitudinal designs, these approaches often fall short of capturing the full picture needed to understand the timing and impact of sleep. Encouragingly, we have the tools and methods needed to pursue this important work. In this article, we highlight statistical approaches and research designs that can help move the field forward. With thoughtful application of these methods, we can strengthen our conclusions, generate more impactful findings, and bring us closer to understanding the role of sleep across the lifespan.

Study objectives: Excessive daytime sleepiness (EDS), influenced by environmental and social-behavioral factors, is reported by a subset of patients with sleep apnea-a group that may be at elevated cardiovascular risk. However, it is unclear whether sleep apnea with and without EDS have distinct genetic underpinnings. In this study, we perform gene-by-EDS interaction analyses for apnea hypopnea index, a diagnostic marker of sleep apnea severity, to understand EDS's influence on its underlying genetic risk.

Methods: Discovery interaction analyses for common variants and gene-based rare variants were conducted respectively using multi-ethnic Trans-Omics for Precision Medicine (N = 11 619) data, followed by replication and subsequent meta-analysis in additional Trans-Omics for Precision Medicine-imputed data (N = 8904). The 1 degree-of-freedom (1df) G × E test and the 2df joint G,G × E tests were utilized. Sex-stratified analyses were additionally performed.

Results: Discovery analysis revealed two common intronic variants-rs13118183 (CCDC3) and rs281851 (MARCHF1)-and three rare variant gene sets mapped to SCUBE2, TMEM26, and CPS4FL-to exhibit interaction with EDS. Meta-analysis revealed EDS interaction with 11 rare variant gene sets mapped to UBLCP1, MED31, RAP1GAP, CPNE5, MYMX, YY1, ZNF773, YBEY, IQCB1, PI4K2B, and CORO1A.

Conclusion: Genetic loci reveal connections to cardiovascular risk, insulin resistance, thiamine deficiency, and resveratrol mechanism. Discovered genetic signals may offer insight into pertinent biological pathways for sleep apnea patients with an excessively sleepy subtype. Statement of Significance Sleep apnea is a complex sleep disorder. Exemplifying this is the disparately varying estimates of presence of excessive daytime sleepiness (EDS) in patients, and persistent EDS that lingers despite treatment. Some data indicate that the excessively sleepy subtype of sleep apnea carries heightened cardiovascular risk. Whether EDS influences genetic risk factors underlying sleep apnea has not yet been investigated. This study addresses this gap, as the first genome-wide gene × EDS interaction study for apnea hypopnea index, the standard sleep apnea severity metric. Genetic loci that have been previously unconsidered for sleep apnea are revealed. Discovered interaction signals highlight pathways in metabolism, genes associated with cardiometabolic traits, and therapeutic agents influencing obesity, blood pressure, oxidative stress, and apnea hypopnea index.

Study objectives: Prior research has suggested that disrupted and weakened rest-activity rhythms measured by accelerometry may be associated with risks of many diseases, including cardiometabolic diseases, cancer, and dementia, but the mechanisms underlying this are not fully understood. This study is the second of two studies aimed at using an untargeted approach to identify metabolomic markers associated with rest-activity rhythm characteristics and focuses on older women.

Methods: The analysis included 688 women in the Women's Health Initiative. Rest-activity rhythms were characterized by parametric and non-parametric algorithms applied to accelerometry data. Metabolomics data were measured from fasting serum samples with ultra high-performance liquid-phase chromatography and gas chromatography coupled with mass spectrometry and tandem mass spectrometry. Associations between rest-activity rhythms and metabolomics were determined by multiple linear regression models and Ingenuity Pathway Analysis.

Results: Of the 934 metabolites included, 280 showed an association (false discovery rate < 0.1) with one of the three primary rest-activity variables (pseudo F-statistic, intradaily variability, and interdaily stability). These metabolites represent a wide range of biochemical classes and metabolic pathways, including sulfur amino acids, fibrinopeptides, plasmalogens, amino sugar metabolites, and nucleotides. The PEX5 gene network was identified by the Ingenuity Pathway Analysis as the most significantly enriched genetic pathway in relation to rest-activity rhythms.

Conclusions: We found numerous metabolites and pathways that were associated with rest-activity rhythm variables in older women, suggesting a potentially wide-reaching role of diurnal behaviors in human metabolism and health. Statement of Significance In this metabolomics study in older women, we found a large number of metabolites that were associated with rest-activity rhythms. These metabolites represented a wide range of biochemical classes and metabolic pathways. This analysis also confirmed numerous metabolite associations we have recently found in a sample of older men in the Osteoporotic Fractures in Men study, lending further support to a wide-reaching role of circadian rhythms and diurnal behaviors in human health. To the best of our knowledge, our two studies were the first metabolomics investigations focusing on rest-activity rhythm characteristics. With further validation studies, we anticipate that findings from these studies will contribute to the broader endeavor to understand, diagnose, and treat circadian rhythm-related disorders, with potential benefits for human health.

Several dopaminergic compounds, including the clinically used pramipexole, are labeled as preferential dopamine D3 receptor (D3R) agonists based on their moderately higher affinity for the D3R versus other D2-like receptor subtypes. It is therefore generally believed that D3R is the main target for their initial therapeutic response in restless legs syndrome (RLS). Here, we review the results of recent comprehensive pharmacological studies that demonstrate that in addition to the binding affinities of D3R agonists, their functional responses at the different D2-like receptors depend on other pharmacodynamic factors, including intrinsic efficacy, biased agonism, functional efficacy, and receptor heteromerization, and pharmacokinetic factors, including brain penetrability. When considering all these factors, the short isoform of the D2 receptor (D2SR) localized in the dopaminergic neurons and D2SRs and D4Rs localized in corticostriatal glutamatergic terminals become preferential targets of low doses of these D2-like receptor agonists. On the other hand, higher doses are necessary to promote activation of postsynaptic striatal D3Rs forming heteromers with D1Rs, which could be associated with the phenomenon of augmentation, the worsening of RLS symptoms with their chronic use. The putative role of spinal D3Rs, especially with the periodic leg movements of sleep component of RLS, is also discussed. This analysis should provide therapeutic clues for better targeting of the dopamine receptor subtypes involved in the therapeutic and not in the secondary effects of D2-like receptor agonists in RLS. Statement of Significance We discuss recent pharmacological studies demonstrating that the targets of the therapeutic effects of dopamine receptor agonists in restless legs syndrome depend on more than just binding affinities. Several other pharmacodynamic and pharmacokinetic factors also need to be considered when evaluating the main dopamine receptor subtype involved. These studies suggest that striatal presynaptic D2 receptors (D2Rs) and D4Rs are preferentially involved in the therapeutic effects of dopamine receptor agonists, while striatal postsynaptic D1Rs and D3Rs are involved in the worsening of RLS symptoms with their chronic use. The putative role of spinal D3Rs, especially with the periodic leg movements of sleep component of RLS, is also discussed.

Study objectives: Rest-activity rhythm characteristics have been linked to a wide range of health conditions; however, the molecular mechanisms underlying these associations are not well understood. This study is the first of two studies aiming to use an untargeted approach to identify metabolomic markers associated with rest-activity rhythm characteristics and focuses on older men.

Methods: The study included 950 participants from the Osteoporotic Fractures in Men study. Multiple parametric and non-parametric variables of rest-activity rhythms were derived from actigraphy data. A total of 848 metabolites were measured from fasting blood samples using an untargeted approach. Multiple linear regression models and Ingenuity Pathway Analysis (IPA) were used to identify metabolomic profiles associated with rest-activity variables.

Results: We found 65 metabolites, mostly amino acids and lipids, that were significantly associated with at least one of the primary rest-activity variables (i.e. pseudo-F-statistic, intradaily variability, and interdaily stability). These metabolites were from various biochemical pathways, including diacylglycerol, plasmalogen, lysoplasmalogen, and amino sugar metabolism. The IPA suggested that these metabolites may be implicated in various diseases and functions, particularly immune and inflammatory diseases, and identified the PEX2-PEX5 network as a significantly enriched gene-regulation pathway.

Conclusions: Our findings expand the current knowledge about the relationship between diurnal behaviors and human metabolism, and provide new evidence regarding mechanistic pathways that may mediate the adverse health effects of impaired rest-activity rhythms in older men. Statement of Significance In this metabolomics study in older men, we found a large number of metabolites that were associated with rest-activity rhythms. Our findings expand the current knowledge about the relationship between circadian-regulated diurnal behaviors and human metabolism, reinforce the critical role of circadian function in health and diseases, and provide new evidence regarding mechanistic pathways that may mediate the adverse effects of circadian disruptions. Our findings also point to ample future directions for further research to further elucidate the relationships among rest-activity rhythms, metabolomic profiles, and disease risk, which may help identifying intermediate targets for developing disease therapies and developing models for disease risk prediction and management.

Study objectives: Native Americans (NAs) experience higher rates of chronic pain than other U.S. racial/ethnic groups. Sleep and pain share a bidirectional relationship, but sleep impacts pain more than the reverse. NAs experience high rates of sleep problems; thus, sleep may contribute to the NA pain disparity. To date, there have been no intensive longitudinal assessments of sleep and pain to assess whether sleep-pain temporal relationships differ across racial/ethnic groups, including NAs.

Methods: To address this research gap, a secondary analysis of a clinical trial of a mobile health intervention for anxiety and/or depression sample was conducted. NA (n = 199), White (n = 205), Black (n = 198), and Hispanic adults (n = 199) completed ecological momentary assessments of daily sleep quality, sleep duration, and morning and evening pain intensity for 6-months. Dynamic structural equation modeling was used to assess cross-lagged, temporal relationships between sleep and pain, while controlling potential confounds.

Results: As expected, there was a reciprocal sleep-pain relationship; lower sleep quality was associated with higher next-morning pain and higher pain was associated with lower next-day sleep quality. The sleep to pain path was stronger than the reverse. Evening pain was also associated with next-night sleep quality. Sleep duration was not temporally related to pain. There was a stronger sleep quality-pain association in NAs compared to Black participants, but no other racial/ethnic difference was significant.

Conclusions: This is the first study to show that sleep-pain relationships extend to NAs and other minoritized groups, but poor sleep may not fully account for NA pain disparities.

Clinical trial: Mobile Health and COVID-19, https://clinicaltrials.gov/study/NCT05074693, NCT05074693 Statement of Significance This is the first study to examine sleep-pain relationships in Native Americans (NAs), a group that experiences significant pain disparities. Sleep quality was related to morning pain and morning pain was related to sleep quality, but the effect of sleep quality on pain was stronger than the reverse. Similar relationships were found in other racial/ethnic groups (Black, Hispanic, White), except that the sleep-pain path was stronger in NAs than Black participants. Together, these findings suggest that poor sleep contributes to pain and that pain contributes to poor sleep in all groups and does not fully account for the NA pain disparity.