Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes

Association of sleep traits with risk of hypertensive disorders of pregnancy: a mendelian randomization study

BACKGROUND

Unhealthy sleep patterns are common during pregnancy and have been associated with an increased risk of developing hypertensive disorders of pregnancy (HDPs) in observational studies. However, the causality underlying these associations remains uncertain. This study aimed to evaluate the potential causal association between seven sleep traits and the risk of HDPs using a two-sample Mendelian randomization study.

METHODS

Genome-wide association study (GWAS) summary statistics were obtained from the FinnGen consortium, UK Biobank, and other prominent consortia, with a focus on individuals of European ancestry. The primary analysis utilized an inverse-variance-weighted MR approach supplemented by sensitivity analyses to mitigate potential biases introduced by pleiotropy. Furthermore, a two-step MR framework was employed for mediation analyses.

RESULTS

The data analyzed included 200 000-500 000 individuals for each sleep trait, along with approximately 15 000 cases of HDPs. Genetically predicted excessive daytime sleepiness (EDS) exhibited a significant association with an increased risk of HDPs [odds ratio (OR) 2.96, 95% confidence interval (95% CI) 1.40-6.26], and the specific subtype of preeclampsia/eclampsia (OR 2.97, 95% CI 1.06-8.3). Similarly, genetically predicted obstructive sleep apnea (OSA) was associated with a higher risk of HDPs (OR 1.27, 95% CI 1.09-1.47). Sensitivity analysis validated the robustness of these associations. Mediation analysis showed that BMI mediated approximately 25% of the association between EDS and HDPs, while mediating up to approximately 60% of the association between OSA and the outcomes. No statistically significant associations were observed between other genetically predicted sleep traits, such as chronotype, daytime napping, sleep duration, insomnia, snoring, and the risk of HDPs.

CONCLUSION

Our findings suggest a causal association between two sleep disorders, EDS and OSA, and the risk of HDPs, with BMI acting as a crucial mediator. EDS and OSA demonstrate promise as potentially preventable risk factors for HDPs, and targeting BMI may represent an alternative treatment strategy to mitigate the adverse impact of sleep disorders.

Genetic evidence for the causal effects of C-reactive protein on self-reported habitual sleep duration

Inflammatory responses to acute stimuli are proposed to regulate sleep, but the relationship between chronic inflammation and habitual sleep duration is elusive. Here, we study this relation using genetically predicted level of chronic inflammation, indexed by CRP and IL6 signaling, and self-reported sleep duration. By Mendelian randomization analysis, we show that elevated CRP level within <10 mg/L has a homeostatic effect that facilitates maintaining 7-8 h sleep duration per day - making short-sleepers sleep longer (p = 2.42 × 10-2) and long-sleepers sleep shorter (1.87 × 10-7); but it is not associated with the overall sleep duration (p = 0.17). This homeostatic effect replicated in an independent CRP dataset. We observed causal effects of the soluble interleukin 6 receptor and gp130 on overall sleep duration (p = 1.62 × 10-8, p = 2.61 × 10-58, respectively), but these effects disappeared when CRP effects were accounted for in the model. Using polygenic score analysis, we found that the homeostatic effect of CRP on sleep duration stems primarily from the genetic variants within the CRP gene region: when genetic variants outside of this region were used to predict CRP levels, the opposite direction of effect was observed. In conclusion, we show that elevated CRP level may causally facilitate maintaining an optimal sleep duration that is beneficial to health, thus updating our current knowledge of immune regulation on sleep.

No bidirectional relationship between sleep phenotypes and risk of proliferative diabetic retinopathy: a two-sample Mendelian randomization study

This study aimed to investigate the probable existence of a causal relationship between sleep phenotypes and proliferative diabetic retinopathy (PDR). Single nucleotide polymorphisms associated with sleep phenotypes were selected as instrumental variables at the genome-wide significance threshold (P < 5 × 10-8). Inverse-variance weighted was applied as the primary Mendelian randomization (MR) analysis method, and MR Egger regression, weighted median, simple mode, and weighted mode methods were used as complementary analysis methods to estimate the causal association between sleep phenotypes and PDR. Results indicated that genetically predicted sleep phenotypes had no causal effects on PDR risk after Bonferroni correction (P = 0.05/10) [Chronotype: P = 0.143; Daytime napping: P = 0.691; Daytime sleepiness: P = 0.473; Insomnia: P = 0.181; Long sleep duration: P = 0.671; Morning person:P = 0.113; Short sleep duration: P = 0.517; Obstructive sleep apnea: P = 0.091; Sleep duration: P = 0.216; and snoring: P = 0.014]. Meanwhile, there are no reverse causality for genetically predicted PDR on sleep phenotypes [Chronotype: P = 0.100; Daytime napping: P = 0.146; Daytime sleepiness: P = 0.469; Insomnia: P = 0.571; Long sleep duration: P = 0.779; Morning person: P = 0.040; Short sleep duration: P = 0.875; Obstructive sleep apnea: P = 0.628; Sleep duration: P = 0.896; and snoring: P = 0.047]. This study's findings did not support the causal effect of between sleep phenotypes and PDR. Whereas, longitudinal studies can further verify results validation.

Mendelian randomization study supports positive bidirectional causal relationships between genetically predicted insomnia symptom and liability to benign prostatic hyperplasia

BACKGROUND

Sleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study.

METHODS

Genome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran's Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability.

RESULTS

Forward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003-1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096-2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results.

CONCLUSION

This study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

The causal relationship between sleep disturbances and the risk of frailty: a two-sample Mendelian randomization study

OBJECTIVE

Adequate sleep is closely related to people's health. However, with increasing age, the quality of sleep worsens. At the same time, among elderly individuals, frailty is also a disturbing factor, which makes elderly individuals more vulnerable to negative factors. To explore the relationship between the two, we conducted this study.

METHODS

In this paper, independent genetic variations related to insomnia, sleep duration and daytime sleepiness were selected as IVs, and related genetic tools were used to search published genome-wide association studies for a two-sample Mendelian randomization (TSMR) analysis. The inverse-variance weighted (IVW) method was used as the main Mendelian randomization analysis method. Cochran's Q test was used to test heterogeneity, MR‒Egger was used to test horizontal pleiotropy, and the MR-PRESSO test was used to remove outliers.

RESULTS

According to our research, insomnia (OR = 1.10, 95% CI 1.03-1.17, P = 2.59e-97), long sleep duration (OR = 0.66, 95% CI 0.37-1.17, P = 0.02), short sleep duration (OR = 1.30, 95% CI 1.22-1.38, P = 2.23e-17) and daytime sleepiness (OR = 1.49, 95% CI 1.25-1.77, P = 0.96e-4) had a bidirectional causal relationship with frailty.

CONCLUSIONS

Our research showed that there is a causal relationship between sleep disturbances and frailty. This result was obtained by a TSMR analysis, which involves the use of genetic variation as an IV to determine causal relationships between exposure and outcome. Future TSMR studies should include a larger sample for analysis.

The relationship between autoimmune thyroid disease, thyroid nodules and sleep traits: a Mendelian randomization study

Background

Previous studies have suggested a potential association between Autoimmune thyroid disease Thyroid nodules and Sleep Traits, but the evidence is limited and controversial, and the exact causal relationship remains uncertain.

Objective

Therefore, we employed a MR analysis to investigate the causal relationship between Autoimmune thyroid disease, Thyroid nodules and Sleep Traits.

Methods

To explore the interplay between Autoimmune thyroid disease Thyroid nodules and Sleep Traits, we employed MR studies utilizing summary statistics derived from GWAS in individuals of European ancestry. To ensure robustness, multiple techniques were employed to assess the stability of the causal effect, including random-effect inverse variance weighted, weighted median, MR-Egger regression, and MR-PRESSO. Heterogeneity was evaluated using Cochran's Q value. Additionally, we investigated the presence of horizontal pleiotropy through MR-Egger regression and MR-PRESSO.

Results

The IVW method indicates a significant causal relationship between "Getting up" and autoimmune hypothyroidism, as revealed by the IVW method (OR: 0.59, 95% CI: 0.45 to 0.78, P-value = 1.99e-4). Additionally, there might be a potential correlation between sleep duration and autoimmune hypothyroidism (OR: 0.76, 95% CI: 0.60 to 0.79, P-value = 0.024). Moreover, the observed potential positive link between daytime nap and thyroid nodules (OR: 1.66, 95% CI: 1.07 to 2.58, P-value = 0.023) is subject to caution, as subsequent MR PRESSO testing reveals the presence of horizontal pleiotropy, raising concerns about the reliability of the findings. The findings suggested a potential inverse association between Autoimmune hypothyroidism and Getting up (OR: 0.99, 95% CI: 0.98 to 1.00, P-value = 6.66e-3).As the results of MR-Egger method(OR: 1.00, 95% CI: 0.98 to 1.02, P-value = 0.742) exhibited an opposing trend to that observed with the IVW method and the results did not reach significance after P-value correction.

Conclusion

The results of our study reveal a notable cause-and-effect relationship between Getting up and Autoimmune hypothyroidism, indicating its potential role as a protective factor against this condition. However, no causal connection was observed between sleep traits and Graves' disease or Thyroid nodules.

Sleep Characteristics and Risk of Stroke and Dementia: An Observational and Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Sleep disturbances are implicated as risk factors of both stroke and dementia. However, whether these associations are causal and whether treatment of sleep disorders could reduce stroke and dementia risk remain uncertain. We aimed to evaluate associations and ascertain causal relationships between sleep characteristics and stroke/dementia risk and MRI markers of small vessel disease (SVD).

METHODS

We used data sets from a multicenter population-based study and summary statistics from genome-wide association studies (GWASs) of sleep characteristics and outcomes. We analyzed 502,383 UK Biobank participants with self-reported sleep measurements, including sleep duration, insomnia, chronotype, napping, daytime dozing, and snoring. In observational analyses, the primary outcomes were incident stroke, dementia, and their subtypes, alongside SVD markers. Hazard ratios (HRs) and odds ratios (ORs) were adjusted for age, sex, and ethnicity, and additional vascular risk factors. In Mendelian randomization (MR) analyses, ORs or risk ratios are reported for the association of each genetic score with clinical or MRI end points.

RESULTS

Among 502,383 participants (mean [SD] age, 56.5 [8.1] years; 54.4% female), there were 7,668 cases of all-cause dementia and 10,334 strokes. In longitudinal analyses, after controlling for cardiovascular risk factors, participants with insomnia, daytime napping, and dozing were associated with increased risk of any stroke (HR 1.05, 95% CI 1.01-1.11, p = 8.53 × 10-3; HR 1.09, 95% CI 1.05-1.14, p = 3.20 × 10-5; HR 1.19, 95% CI 1.08-1.32, p = 4.89 × 10-4, respectively). Almost all sleep measures were associated with dementia risk (all p < 0.001, except insomnia). Cross-sectional analyses identified associations between napping, snoring, and MRI markers of SVD (all p < 0.001). MR analyses supported a causal link between genetically predicted insomnia and increased stroke risk (OR 1.31, 95% CI 1.13-1.51, p = 0.00072), but not with dementia or SVD markers.

DISCUSSION

We found that multiple sleep measures predicted future risk of stroke and dementia, but these associations were attenuated after controlling for cardiovascular risk factors and were absent in MR analyses for Alzheimer disease. This suggests possible confounding or reverse causation, implying caution before proposing sleep disorder modifications for dementia treatment.

Exome sequencing identifies genes associated with sleep-related traits

Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.

Impact of Sleep Disorders and Disturbed Sleep on Brain Health: A Scientific Statement From the American Heart Association

Accumulating evidence supports a link between sleep disorders, disturbed sleep, and adverse brain health, ranging from stroke to subclinical cerebrovascular disease to cognitive outcomes, including the development of Alzheimer disease and Alzheimer disease-related dementias. Sleep disorders such as sleep-disordered breathing (eg, obstructive sleep apnea), and other sleep disturbances, as well, some of which are also considered sleep disorders (eg, insomnia, sleep fragmentation, circadian rhythm disorders, and extreme sleep duration), have been associated with adverse brain health. Understanding the causal role of sleep disorders and disturbances in the development of adverse brain health is complicated by the common development of sleep disorders among individuals with neurodegenerative disease. In addition to the role of sleep disorders in stroke and cerebrovascular injury, mechanistic hypotheses linking sleep with brain health and biomarker data (blood-based, cerebrospinal fluid-based, and imaging) suggest direct links to Alzheimer disease-specific pathology. These potential mechanisms and the increasing understanding of the "glymphatic system," and the recognition of the importance of sleep in poststroke recovery, as well, support a biological basis for the indirect (through the worsening of vascular disease) and direct (through specific effects on neuropathology) connections between sleep disorders and brain health. Given promising evidence for the benefits of treatment and prevention, sleep disorders and disturbances represent potential targets for early treatment that may improve brain health more broadly. In this scientific statement, we discuss the evidence supporting an association between sleep disorders and disturbances and poor brain health ranging from stroke to dementia and opportunities for prevention and early treatment.

Genetics of sleep medication purchases suggests causality from sleep problems to psychiatric traits

STUDY OBJECTIVES

Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems.

METHODS

We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation.

RESULTS

In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12).

CONCLUSIONS

These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

Multivariate genome-wide association study of sleep health demonstrates unity and diversity

There has been a recent push to focus sleep research less on disordered sleep and more on the dimensional sleep health. Sleep health incorporates several dimensions of sleep: chronotype, efficiency, daytime alertness, duration, regularity, and satisfaction with sleep. A previous study demonstrated sleep health domains correlate only moderately with each other at the genomic level (|rGs| = 0.11-0.51) and show unique relationships with psychiatric domains (controlling for shared variances, duration, alertness, and non-insomnia independently related to a factor for internalizing psychopathology). Of the domains assessed, circadian preference was the least genetically correlated with all other facets of sleep health. This pattern is important because it suggests sleep health should be considered a multifaceted construct rather than a unitary construct. Prior genome-wide association studies (GWASs) have vastly increased our knowledge of the biological underpinnings of specific sleep traits but have only focused on univariate analyses. We present the first multivariate GWAS of sleep and circadian health (multivariate circadian preference, efficiency, and alertness factors, and three single-indicator factors of insomnia, duration, and regularity) using genomic structural equation modeling. We replicated loci found in prior sleep GWASs, but also discovered "novel" loci for each factor and found little evidence for genomic heterogeneity. While we saw overlapping genomic enrichment in subcortical brain regions and shared associations with external traits, much of the genetic architecture (loci, mapped genes, and enriched pathways) was diverse among sleep domains. These results confirm sleep health as a family of correlated but genetically distinct domains, which has important health implications.

Genome-wide association analysis of composite sleep health scores in 413,904 individuals

Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, and together may provide a more complete picture of sleep health, while also illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches. GWASs of these six SHSs identify 28 significant novel loci adjusting for multiple testing on six traits (p<8.3e-9), along with 341 previously reported loci (p<5e-08). The heritability of the first three SHS-PCs equals or exceeds that of SHS-ADD (SNP-h2=0.094), while revealing sleep-domain-specific genetic discoveries. Significant loci enrich in multiple brain tissues and in metabolic and neuronal pathways. Post GWAS analyses uncover novel genetic mechanisms underlying sleep health and reveal connections to behavioral, psychological, and cardiometabolic traits.

DAYWAKE implicates novel roles for circulating lipid-binding proteins as extracerebral regulators of daytime wake-sleep behavior

Sleep during the midday, commonly referred to as siesta, is a common trait of animals that mainly sleep during the night. Work using Drosophila led to the identification of the daywake (dyw) gene, found to have anti-siesta activity. Herein, we show that the DYW protein undergoes signal peptide-dependent secretion, is present in the circulatory system, and accumulates in multiple organs, but, surprisingly, it is not detected in the brain where wake-sleep centers are located. The abundance of DYW in adult flies is regulated by age, sex, temperature, and the splicing efficiency of a nearby thermosensitive intron. We suggest that DYW regulates daytime wake-sleep balance in an indirect, extracerebral manner, via a multi-organ network that interfaces with the circulatory system.

Association between alcohol consumption and sleep traits: observational and mendelian randomization studies in the UK biobank

Previous studies have shown that excessive alcohol consumption is associated with poor sleep. However, the health risks of light-to-moderate alcohol consumption in relation to sleep traits (e.g., insomnia, snoring, sleep duration and chronotype) remain undefined, and their causality is still unclear in the general population. To identify the association between alcohol consumption and multiple sleep traits using an observational and Mendelian randomization (MR) design. Observational analyses and one-sample MR (linear and nonlinear) were performed using clinical and individual-level genetic data from the UK Biobank (UKB). Two-sample MR was assessed using summary data from genome-wide association studies from the UKB and other external consortia. Phenotype analyses were externally validated using data from the National Health and Nutrition Examination Survey (2017-2018). Data analysis was conducted from January 2022 to October 2022. The association between alcohol consumption and six self-reported sleep traits (short sleep duration, long sleep duration, chronotype, snoring, waking up in the morning, and insomnia) were analysed. This study included 383,357 UKB participants (mean [SD] age, 57.0 [8.0] years; 46% male) who consumed a mean (SD) of 9.0 (10.0) standard drinks (one standard drink equivalent to 14 g of alcohol) per week. In the observational analyses, alcohol consumption was significantly associated with all sleep traits. Light-moderate-heavy alcohol consumption was linearly linked to snoring and the evening chronotype but nonlinearly associated with insomnia, sleep duration, and napping. In linear MR analyses, a 1-SD (14 g) increase in genetically predicted alcohol consumption was associated with a 1.14-fold (95% CI, 1.07-1.22) higher risk of snoring (P < 0.001), a 1.28-fold (95% CI, 1.20-1.37) higher risk of evening chronotype (P < 0.001) and a 1.24-fold (95% CI, 1.13-1.36) higher risk of difficulty waking up in the morning (P < 0.001). Nonlinear MR analyses did not reveal significant results after Bonferroni adjustment. The results of the two-sample MR analyses were consistent with those of the one-sample MR analyses, but with a slightly attenuated overall estimate. Our findings suggest that even low levels of alcohol consumption may affect sleep health, particularly by increasing the risk of snoring and evening chronotypes. The negative effects of alcohol consumption on sleep should be made clear to the public in order to promote public health.

Causal Association Between Subtypes of Excessive Daytime Sleepiness and Risk of Cardiovascular Diseases

BACKGROUND

Excessive daytime sleepiness (EDS), experienced in 10% to 20% of the population, has been associated with cardiovascular disease and death. However, the condition is heterogeneous and is prevalent in individuals having short and long sleep duration. We sought to clarify the relationship between sleep duration subtypes of EDS with cardiovascular outcomes, accounting for these subtypes.

METHODS AND RESULTS

We defined 3 sleep duration subtypes of excessive daytime sleepiness: normal (6-9 hours), short (<6 hours), and long (>9 hours), and compared these with a nonsleepy, normal-sleep-duration reference group. We analyzed their associations with incident myocardial infarction (MI) and stroke using medical records of 355 901 UK Biobank participants and performed 2-sample Mendelian randomization for each outcome. Compared with healthy sleep, long-sleep EDS was associated with an 83% increased rate of MI (hazard ratio, 1.83 [95% CI, 1.21-2.77]) during 8.2-year median follow-up, adjusting for multiple health and sociodemographic factors. Mendelian randomization analysis provided supporting evidence of a causal role for a genetic long-sleep EDS subtype in MI (inverse-variance weighted β=1.995, P=0.001). In contrast, we did not find evidence that other subtypes of EDS were associated with incident MI or any associations with stroke (P>0.05).

CONCLUSIONS

Our study suggests the previous evidence linking EDS with increased cardiovascular disease risk may be primarily driven by the effect of its long-sleep subtype on higher risk of MI. Underlying mechanisms remain to be investigated but may involve sleep irregularity and circadian disruption, suggesting a need for novel interventions in this population.

Causal relationship between sleep traits and cognitive impairment: A Mendelian randomization study

OBJECTIVE

Observational studies had demonstrated a link between sleep disturbances and cognitive decline. Here, we aimed to investigate the causal association between genetically predicted sleep traits and cognitive impairment using Mendelian randomization (MR).

METHODS

Using strict criteria, we selected genetic variants from European ancestry Genome-wide association studies (GWAS) from the Sleep Disorders Knowledge Portal and UK Biobank as instrumental variables for several sleep traits, including insomnia, sleep duration, daytime sleepiness, daytime napping, and chronotype. Summary statistics related to cognitive impairment were derived from five different GWAS, including the Social Science Genetic Association Consortium. The role of self-reported sleep trait phenotypes in the etiology of cognitive impairment was explored using inverse-variance weighted (IVW) tests, MR-Egger tests, and weighted medians, and sensitivity analyses were conducted to ensure robustness.

RESULTS

In the main IVW analysis, sleep duration (reaction time: β = -0.05, 95% CI -0.07 to -0.04, p = 1.93×10-12 ), daytime sleepiness (average cortical thickness: β = -0.12, 95% CI -0.22 to -0.02, p = 0.023), and daytime napping (fluid intelligence: β = -0.47, 95% CI -0.87 to -0.07, p = 0.021; hippocampal volume in Alzheimer's disease: β = -0.99, 95% CI -1.64 to -0.35, p = 0.002) were significantly negatively correlated with cognitive performance. However, any effects of insomnia and chronotype on cognitive impairment were not determined.

CONCLUSIONS

Our findings highlighted that focusing on sleep behaviors or distinct sleep patterns-particularly sleep duration, daytime sleepiness, and daytime napping, was a promising approach for preventing cognitive impairment. This study also shed light on risk factors for and potential early markers of cognitive impairment risk factors.

Selection of genetic instruments in Mendelian randomisation studies of sleep traits

This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.

Unraveling the associations and causalities between glucose metabolism and multiple sleep traits

Purpose

The aim of our study is to estimate the associations and causalities of glucose metabolism traits of fasting blood glucose (FBG), fasting insulin (FINS), glycosylated hemoglobin (HbA1c), and 2-h glucose post-challenge (2hGlu) with sleep traits consisting of excessive daytime sleepiness (EDS), insomnia, and sleep duration.

Methods

We employed standard quantitative analysis procedures to assess the associations between sleep traits and glucose metabolism. Moreover, we acquired published genome-wide association studies (GWAS) summary statistics for these traits and conducted Mendelian randomization (MR) analyses to estimate their causal directions and effects. Inverse variance weighting (IVW) was employed as the primary approach, followed by sensitivity analyses.

Results

A total of 116 studies with over 840,000 participants were included in the quantitative analysis. Our results revealed that participants with abnormal glucose metabolism had higher risks for EDS (OR [95% CI] = 1.37 [1.10,1.69]), insomnia (OR [95% CI] = 1.65 [1.24,2.20]), and both short and long sleep duration (OR [95% CI] = 1.35 [1.12,1.63]; OR [95% CI] = 1.38 [1.13,1.67] respectively). In addition, individuals with these sleep traits exhibited alterations in several glycemic traits compared with non-affected controls. In MR analysis, the primary analysis demonstrated causal effects of 2hGlu on risks of EDS (OR [95% CI] = 1.022 [1.002,1.042]) and insomnia (OR [95% CI] = 1.020[1.001,1.039]). Furthermore, FINS was associated with short sleep duration (OR [95% CI] = 1.043 [1.018,1.068]), which reversely presented a causal influence on HbA1c (β [95% CI] = 0.131 [0.022,0.239]). These results were confirmed by sensitivity analysis.

Conclusion

Our results suggested mutual risk and causal associations between the sleep traits and glycemic traits, shedding new light on clinical strategies for preventing sleep disorders and regulating glucose metabolism. Future studies targeting these associations may hold a promising prospect for public health.

Genetic analysis of probable sleep bruxism and its associations with clinical and behavioral traits

STUDY OBJECTIVES

Sleep bruxism (SB) can cause damage on teeth, headache and severe pain affecting both sleep and daily functioning. Yet despite the growing interest into bruxism, the underlying clinically relevant biological mechanisms remain unresolved. The aim of our study was to understand biological mechanisms and clinical correlates of SB including previously reported disease associations.

METHODS

We used data from the FinnGen release R9 (N = 377 277 individuals) that are linked with Finnish hospital and primary care registries. We identified 12 297 (3.26%) individuals with International Classification of Diseases (ICD)-10 codes used for SB. In addition, we used logistic regression to examine the association between probable SB and its clinically diagnosed risk factors and comorbidities using ICD-10 codes. Furthermore, we examined medication purchases using prescription registry. Finally, we performed the first genome-wide association analysis for probable SB and computed genetic correlations using questionnaire, lifestyle, and clinical traits.

RESULTS

The genome-wide association analysis revealed one significant association: rs10193179 intronic to Myosin IIIB (MYO3B) gene. In addition, we observed phenotypic associations and high genetic correlations with pain diagnoses, sleep apnea, reflux disease, upper respiratory diseases, psychiatric traits, and also their related medications such as antidepressants and sleep medication (p < 1e-4 for each trait).

CONCLUSIONS

Our study provides a large-scale genetic framework to understand risk factors for SB and suggests potential biological mechanisms. Furthermore, our work strengthens the important earlier work that highlights SB as a trait that is associated with multiple axes of health. As part of this study, we provide genome-wide summary statistics that we hope will be useful for the scientific community studying SB.

The causal associations of altered inflammatory proteins with sleep duration, insomnia and daytime sleepiness

STUDY OBJECTIVES

Growing evidence linked inflammation with sleep. This study aimed to evaluate the associations and causal effects of sleep traits including insomnia, excessive daytime sleepiness (EDS), and sleep duration (short: <7 h; normal: 7-9 h; long: ≥9 h), with levels of C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), and interleukins.

METHODS

Standard procedures of quantitative analysis were applied to estimate the expression differences for each protein in compared groups. Then, a two-sample Mendelian randomization (MR) analysis was performed to explore their causal relationships with published genome-wide association study summary statistics. The inverse-variance weighted was used as the primary method, followed by several complementary approaches as sensitivity analyses.

RESULTS

A total of 44 publications with 51 879 participants were included in the quantitative analysis. Our results showed that the levels of CRP, interleukin-1β (IL-1β), IL-6, and TNF-α were higher from 0.36 to 0.58 (after standardization) in insomnia compared with controls, while there was no significant difference between participants with EDS and controls. Besides, there was a U/J-shaped expression of CRP and IL-6 with sleep durations. In MR analysis, the primary results demonstrated the causal effects of CRP on sleep duration (estimate: 0.017; 95% confidence intervals [CI], [0.003, 0.031]) and short sleep duration (estimate: -0.006; 95% CI, [-0.011, -0.001]). Also, IL-6 was found to be associated with long sleep duration (estimate: 0.006; 95% CI, [0.000, 0.013]). These results were consistent in sensitivity analyses.

CONCLUSIONS

There are high inflammatory profiles in insomnia and extremes of sleep duration. Meanwhile, elevated CRP and IL-6 have causal effects on longer sleep duration. Further studies can focus on related upstream and downstream mechanisms.

Mendelian randomization and colocalization analyses reveal an association between short sleep duration or morning chronotype and altered leukocyte telomere length

Observational studies suggest certain sleep traits are associated with telomere length, but the causal nature of these associations is unclear. The study aimed to determine the causal associations between 11 sleep-related traits and leukocyte telomere length (LTL) through two-sample Mendelian randomization and colocalization analyses using the summary statistics from large-scale genome-wide association studies. Univariable Mendelian randomization indicates that genetically determined short sleep is associated with decreased LTL, while morning chronotype is associated with increased LTL. Multivariable Mendelian randomization further supports the findings and colocalization analysis identifies shared common genetic variants for these two associations. No genetic evidence is observed for associations between other sleep-related traits and LTL. Sensitivity MR methods, reverse MR and re-running MR after removing potential pleiotropic genetic variants enhance the robustness of the results. These findings indicate that prioritizing morning chronotype and avoiding short sleep is beneficial for attenuating telomere attrition. Consequently, addressing sleep duration and chronotype could serve as practical intervention strategies.

Causal associations between sleep traits and brain structure: a bidirectional Mendelian randomization study

BACKGROUND

Emerging evidence suggests bidirectional causal relationships between sleep disturbance and psychiatric disorders, but the underlying mechanisms remain unclear. Understanding the bidirectional causality between sleep traits and brain imaging-derived phenotypes (IDPs) will help elucidate the mechanisms. Although previous studies have identified a range of structural differences in the brains of individuals with sleep disorders, it is still uncertain whether grey matter (GM) volume alterations precede or rather follow from the development of sleep disorders.

RESULTS

After Bonferroni correction, the forward MR analysis showed that insomnia complaint remained positively associated with the surface area (SA) of medial orbitofrontal cortex (β, 0.26; 95% CI, 0.15-0.37; P = 5.27 × 10-6). In the inverse MR analysis, higher global cortical SA predisposed individuals less prone to suffering insomnia complaint (OR, 0.89; 95%CI, 0.85-0.94; P = 1.51 × 10-5) and short sleep (≤ 6 h; OR, 0.98; 95%CI, 0.97-0.99; P = 1.51 × 10-5), while higher SA in posterior cingulate cortex resulted in a vulnerability to shorter sleep durations (β, - 0.09; 95%CI, - 0.13 to - 0.05; P = 1.21 × 10-5).

CONCLUSIONS

Sleep habits not only result from but also contribute to alterations in brain structure, which may shed light on the possible mechanisms linking sleep behaviours with neuropsychiatric disorders, and offer new strategies for prevention and intervention in psychiatric disorders and sleep disturbance.

Sleep disorders causally affect the brain cortical structure: A Mendelian randomization study

BACKGROUND

s: Previous studies have reported that patients with sleep disorders have altered brain cortical structures. However, the causality has not been determined. We performed a two-sample Mendelian randomization (MR) to reveal the causal effect of sleep disorders on brain cortical structure.

METHODS

We included as exposures 11 phenotypes of sleep disorders including subjective and objective sleep duration, insomnia symptom and poor sleep efficiency, daytime sleepiness (narcolepsy)/napping, morning/evening preference, and four sleep breathing related traits from nine European-descent genome-wide association studies (GWASs). Further, outcome variables were provided by ENIGMA Consortium GWAS for full brain and 34 region-specific cortical thickness (TH) and surface area (SA) of grey matter. Inverse-variance weighted (IVW) was used as the primary estimate whereas alternative MR methods were implemented as sensitivity analysis approaches to ensure results robustness.

RESULTS

At the global level, both self-reported or accelerometer-measured shorter sleep duration decreases the thickness of full brain both derived from self-reported data (βIVW = 0.03 mm, standard error (SE) = 0.02, P = 0.038; βIVW = 0.02 mm, SE = 0.01, P = 0.010). At the functional level, there were 66 associations of suggestive evidence of causality. Notably, one robust evidence after multiple testing correction (1518 tests) suggests the without global weighted SA of superior parietal lobule was influenced significantly by sleep efficiency (βIVW = -285.28 mm2, SE = 68.59, P = 3.2 × 10-5).

CONCLUSIONS

We found significant evidence that shorter sleep duration, as estimated by self-reported interview and accelerometer measurements, was causally associated with atrophy in the entire human brain.

The Park Sleep subtype in Parkinson's disease: from concept to clinic

INTRODUCTION

The heterogeneity of Parkinson's disease (PD) is evident from descriptions of non-motor (NMS) subtypes and Park Sleep, originally identified by Sauerbier et al. 2016, is one such clinical subtype associated with the predominant clinical presentation of sleep dysfunctions including excessive daytime sleepiness (EDS), along with insomnia.

AREAS COVERED

A literature search was conducted using the PubMed, Medline, Embase, and Web of Science databases, accessed between 1 February 2023 and 28 March 2023. In this review, we describe the clinical subtype of Park Sleep and related 'tests' ranging from polysomnography to investigational neuromelanin MRI brain scans and some tissue-based biological markers.

EXPERT OPINION

Cholinergic, noradrenergic, and serotonergic systems are dominantly affected in PD. Park Sleep subtype is hypothesized to be associated primarily with serotonergic deficit, clinically manifesting as somnolence and narcoleptic events (sleep attacks), with or without rapid eye movement behavior disorder (RBD). In clinic, Park Sleep recognition may drive lifestyle changes (e.g. driving) along with therapy adjustments as Park Sleep patients may be sensitive to dopamine D3 active agonists, such as ropinirole and pramipexole. Specific dashboard scores based personalized management options need to be implemented and include pharmacological, non-pharmacological, and lifestyle linked advice.

Adherence to a healthy sleep pattern is associated with lower risks of incident falls and fractures during aging

Background

Autoimmune diseases are more common among people with unhealthy sleep behaviors, and these conditions have been linked to aging-related bone health. However, there have been few studies that examined the correlation between recently developed sleep patterns based on sleep duration, sleepiness, chronotype, snoring, insomnia, and the incidence of falls and fractures.

Methods

We used a newly developed sleep pattern with components of sleep 7 to 8 h per day, absence of frequent excessive daytime sleepiness, early chronotype, no snoring, and no frequent insomnia as healthy factors to study their relationship with the incidence of falls and fractures. The analysis was conducted among 289,000 participants from the UK Biobank.

Results

The mean follow-up period was 12.3 years (3.5 million person-years of follow-up), and 12,967 cases of falls and 16,121 cases of all fractures were documented. Compared to participants exhibiting an unfavorable sleep pattern, those adhering to a healthy sleep pattern experienced a 17% and 28% reduction in the risks of incident falls (hazard ratio [HR], 0.83; 95% CI, 0.74-0.93) and all fractures (HR, 0.72; 95% CI, 0.66-0.79) during follow-up. In addition, participants exhibiting a healthy sleep pattern, together with a high genetically determined bone mineral density (BMD), showed the lowest risks of falls and fractures.

Conclusion

A healthy sleep pattern was significantly linked to decreased risks of incident falls and fractures. The protective association was not modified by genetically determined BMD.

Sleep Behaviors, Genetic Predispositions, and Risk of Esophageal Cancer

BACKGROUND

Risk factors contributing to more than 10-fold increase in esophageal cancer in the last 50 years remain underexplored. We aim to examine the associations of sleep behaviors with esophageal adenocarcinoma (EAC) and squamous cell carcinoma (ESCC).

METHODS

We prospectively assessed the associations between sleep behaviors (chronotype, duration, daytime napping, daytime sleepiness, snoring, and insomnia) and EAC and ESCC risk in 393,114 participants in the UK Biobank (2006-2016). Participants with 0, 1, and ≥2 unhealthy behaviors, including sleep <6 or >9 h/d, daytime napping, and usual daytime sleepiness were classified as having a good, intermediate, and poor sleep. For EAC, we also examined interactions with polygenic risk score (PRS). Cox models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI).

RESULTS

We documented 294 incident EAC and 95 ESCC. Sleep >9 h/d (HR, 2.05; 95% CI, 1.18-3.57) and sometimes daytime napping (HR, 1.36; 95% CI, 1.06-1.75) were individually associated with increased EAC risk. Compared with individuals with good sleep, those with intermediate sleep had a 47% (HR, 1.47; 95% CI, 1.13-1.91) increased EAC risk, and those with poor sleep showed an 87% (HR, 1.87; 95% CI, 1.24-2.82) higher risk (Ptrend < 0.001). The elevated risks for EAC were similar within strata of PRS (Pinteraction = 0.884). Evening chronotype was associated with elevated risk of ESCC diagnosed after 2 years of enrollment (HR, 2.79; 95% CI, 1.32-5.88).

CONCLUSIONS

Unhealthy sleep behaviors were associated with an increased risk of EAC, independent of genetic risk.

IMPACT

Sleep behaviors may serve as modifiable factors for the prevention of EAC.

Is Short Sleep Bad for the Brain? Brain Structure and Cognitive Function in Short Sleepers

Many sleep less than recommended without experiencing daytime sleepiness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this using a cross-sectional and longitudinal sample of 47,029 participants of both sexes (20-89 years) from the Lifebrain consortium, Human Connectome project (HCP) and UK Biobank (UKB), with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. A total of 740 participants who reported to sleep <6 h did not experience daytime sleepiness or sleep problems/disturbances interfering with falling or staying asleep. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime sleepiness and sleep problems (n = 1742) and participants sleeping the recommended 7-8 h (n = 3886). However, both groups of short sleepers showed slightly lower general cognitive function (GCA), 0.16 and 0.19 SDs, respectively. Analyses using accelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income, and education. The results suggest that some people can cope with less sleep without obvious negative associations with brain morphometry and that sleepiness and sleep problems may be more related to brain structural differences than duration. However, the slightly lower performance on tests of general cognitive abilities warrants closer examination in natural settings.SIGNIFICANCE STATEMENT Short habitual sleep is prevalent, with unknown consequences for brain health and cognitive performance. Here, we show that daytime sleepiness and sleep problems are more strongly related to regional brain volumes than sleep duration. However, participants sleeping ≤6 h had slightly lower scores on tests of general cognitive function (GCA). This indicates that sleep need is individual and that sleep duration per se is very weakly if at all related brain health, while daytime sleepiness and sleep problems may show somewhat stronger associations. The association between habitual short sleep and lower scores on tests of general cognitive abilities must be further scrutinized in natural settings.

Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships With Psychopathology

Background

Poor sleep is associated with many negative health outcomes, including multiple dimensions of psychopathology. In the past decade, sleep researchers have advocated for focusing on the concept of sleep health as a modifiable health behavior to mitigate or prevent these outcomes. Sleep health dimensions often include sleep efficiency, duration, satisfaction, regularity, timing, and daytime alertness. However, there is no consensus on how to best operationalize sleep health at the phenotypic and genetic levels. In some studies, specific sleep health domains were examined individually, while in others, sleep health domains were examined together (e.g., with an aggregate sleep health score).

Methods

Here, we compared alternative sleep health factor models using genomic structural equation modeling on summary statistics from previously published genome-wide association studies of self-reported and actigraphic sleep measures with effective sample sizes up to 452,633.

Results

Our best-fitting sleep health model had 6 correlated genetic factors pertaining to 6 sleep health domains: circadian preference, efficiency, alertness, duration, noninsomnia, and regularity. All sleep health factors were significantly correlated (|rgs| = 0.11-0.51), except for the circadian preference factor with duration and noninsomnia. Better sleep health was generally significantly associated with lower genetic liability for psychopathology (|rgs| = 0.05-0.48), yet the 6 sleep health factors showed divergent patterns of associations with different psychopathology factors, especially when controlling for covariance among the sleep health factors.

Conclusions

These results provide evidence for genetic separability of sleep health constructs and their differentiation with respect to associations with mental health.

Cardiovascular Outcomes in Adults with Coronary Artery Disease and Obstructive Sleep Apnea with versus without Excessive Daytime Sleepiness in the RICCADSA Cinical Trial

Rationale: Recent randomized controlled trials did not show cardiovascular benefits of continuous positive airway pressure (CPAP) in adults with coronary artery disease (CAD) and obstructive sleep apnea (OSA) in intention-to-treat analyses. It has been argued that exclusion of patients with OSA with excessive daytime sleepiness (EDS), who may be most likely to benefit from CPAP treatment, may be a reason for the null results. Objectives: We addressed 1) the effect of concomitant EDS on adverse outcomes in patients with CAD and OSA; and 2) whether the cardiovascular benefit of CPAP adherence differs between individuals with versus without EDS. Methods: This was a secondary analysis of the RICCADSA (Randomized Intervention with CPAP in CAD and Obstructive Sleep Apnea) trial, conducted in Sweden between 2005 and 2013. Data were analyzed from 155 patients with CAD with OSA (apnea-hypopnea index ⩾ 15/h) and EDS (Epworth Sleepiness Scale score ⩾ 10), who were allocated to CPAP and 244 patients without EDS (ESS < 10), who were randomized to CPAP or no CPAP. Patients who were allocated to no CPAP or were nonadherent (CPAP usage < 4 h/night) were compared with adherent patients (CPAP usage ⩾ 4 h/night) at 1-year follow-up. Inverse probability of treatment weighting was applied to mimic randomization of EDS. The primary endpoint was the first event of repeat revascularization, myocardial infarction, stroke, or cardiovascular mortality. Results: The median follow-up was 52.2 months. The incidence of the primary endpoint did not differ significantly between the EDS versus no-EDS groups in the entire cohort. Within the adherent group, patients without EDS had a significantly decreased risk compared with patients with EDS (adjusted hazard ratio, 0.41; 95% confidence interval, 0.20-0.85; P = 0.02). Conclusions: Adverse cardiovascular outcomes did not differ by degrees of EDS for patients with CAD with OSA who were untreated or nonadherent to treatment. CPAP use, at least 4 h/night, was associated with reduced adverse outcomes in participants without EDS. Clinical trial registered with www.clinicaltrials.gov (NCT00519597).

Does EGFR Signaling Mediate Orexin System Activity in Sleep Initiation?

Sleep-wake cycle disorders are an important symptom of many neurological diseases, including Parkinson's disease, Alzheimer's disease, and multiple sclerosis. Circadian rhythms and sleep-wake cycles play a key role in maintaining the health of organisms. To date, these processes are still poorly understood and, therefore, need more detailed elucidation. The sleep process has been extensively studied in vertebrates, such as mammals and, to a lesser extent, in invertebrates. A complex, multi-step interaction of homeostatic processes and neurotransmitters provides the sleep-wake cycle. Many other regulatory molecules are also involved in the cycle regulation, but their functions remain largely unclear. One of these signaling systems is epidermal growth factor receptor (EGFR), which regulates the activity of neurons in the modulation of the sleep-wake cycle in vertebrates. We have evaluated the possible role of the EGFR signaling pathway in the molecular regulation of sleep. Understanding the molecular mechanisms that underlie sleep-wake regulation will provide critical insight into the fundamental regulatory functions of the brain. New findings of sleep-regulatory pathways may provide new drug targets and approaches for the treatment of sleep-related diseases.

Bipolar Chronobiology in Men and Mice: A Narrative Review

In patients with bipolar disorder, we do not only see a cycling of mood episodes, but also a shift in circadian rhythm. In the present overview, the circadian rhythm, the "internal clock", and their disruptions are briefly described. In addition, influences on circadian rhythms such as sleep, genetics, and environment are discussed. This description is conducted with a translational focus covering human patients as well as animal models. Concluding the current knowledge on chronobiology and bipolar disorder, implications for specificity and the course of bipolar disorder and treatment options are given at the end of this article. Taken together, circadian rhythm disruption and bipolar disorder are strongly correlated; the exact causation, however, is still unclear.

Utilizing EEG and fNIRS for the detection of sleep-deprivation-induced fatigue and its inhibition using colored light stimulation

Drowsy driving is a common, but underestimated phenomenon in terms of associated risks as it often results in crashes causing fatalities and serious injuries. It is a challenging task to alert or reduce the driver's drowsy state using non-invasive techniques. In this study, a drowsiness reduction strategy has been developed and analyzed using exposure to different light colors and recording the corresponding electrical and biological brain activities. 31 subjects were examined by dividing them into 2 classes, a control group, and a healthy group. Fourteen EEG and 42 fNIRS channels were used to gather neurological data from two brain regions (prefrontal and visual cortices). Experiments shining 3 different colored lights have been carried out on them at certain times when there is a high probability to get drowsy. The results of this study show that there is a significant increase in HbO of a sleep-deprived participant when he is exposed to blue light. Similarly, the beta band of EEG also showed an increased response. However, the study found that there is no considerable increase in HbO and beta band power in the case of red and green light exposures. In addition to that, values of other physiological signals acquired such as heart rate, eye blinking, and self-reported Karolinska Sleepiness Scale scores validated the findings predicted by the electrical and biological signals. The statistical significance of the signals achieved has been tested using repeated measures ANOVA and t-tests. Correlation scores were also calculated to find the association between the changes in the data signals with the corresponding changes in the alertness level.

Sleep behaviors and Parkinson's disease: A bidirectional Mendelian randomization analysis

OBJECTIVE

Whether the quantity and quality of sleep are the risk factors for the development of Parkinson's disease remains unclear though it has now been confirmed that the quality of sleep among patients with Parkinson's disease is affected at the prodromal and clinical stages. Accordingly, this study aimed to examine the bidirectional causal relationships of multiple sleep-related phenotypes with Parkinson's disease using a two-sample Mendelian randomization (MR) method.

METHODS

The summary-level data collected from the published genome-wide association studies was used for analysis. Besides, the genetic relationships between different sleep-related phenotypes, including self-reported and accelerometer measured traits, were estimated for the risk and age at the onset of Parkinson's disease. To conduct MR analysis, inverse variance weighted, weight median, MR-Egger, and MR-PRESSO method were mainly used. Moreover, sensitivity analyses were carried out to examine the pleiotropic effect.

RESULTS

In general, there was insufficient evidence to support the causal effect of sleep-related phenotypes on risk (N cases/controls = 33,674/449,056) and age at the onset (N cases = 28,568) of Parkinson's disease. However, the results of this study indicated that the later onset age of Parkinson's disease was related to the frequent occurrence of insomnia (OR [95% CI] 1.007 [1.003, 1.011], P < 0.001) after the adjustment for multiple testing.

CONCLUSIONS

The results of this study suggest that insomnia-associated single nucleotide polymorphisms are more frequent in later onset Parkinson's disease patients compared to earlier onset patients. However, given the limitations of statistical power and potential bias, further validation should be still conducted through larger population research.

SREBP modulates the NADP+/NADPH cycle to control night sleep in Drosophila

Sleep behavior is conserved throughout evolution, and sleep disturbances are a frequent comorbidity of neuropsychiatric disorders. However, the molecular basis underlying sleep dysfunctions in neurological diseases remains elusive. Using a model for neurodevelopmental disorders (NDDs), the Drosophila Cytoplasmic FMR1 interacting protein haploinsufficiency (Cyfip^85.1/+), we identify a mechanism modulating sleep homeostasis. We show that increased activity of the sterol regulatory element-binding protein (SREBP) in Cyfip^85.1/+ flies induces an increase in the transcription of wakefulness-associated genes, such as the malic enzyme (Men), causing a disturbance in the daily NADP⁺/NADPH ratio oscillations and reducing sleep pressure at the night-time onset. Reduction in SREBP or Men activity in Cyfip^85.1/+ flies enhances the NADP⁺/NADPH ratio and rescues the sleep deficits, indicating that SREBP and Men are causative for the sleep deficits in Cyfip heterozygous flies. This work suggests modulation of the SREBP metabolic axis as a new avenue worth exploring for its therapeutic potential in sleep disorders.

Integration of genome-scale data identifies candidate sleep regulators

STUDY OBJECTIVES

Genetics impacts sleep, yet, the molecular mechanisms underlying sleep regulation remain elusive. In this study, we built machine learning models to predict sleep genes based on their similarity to genes that are known to regulate sleep.

METHODS

We trained a prediction model on thousands of published datasets, representing circadian, immune, sleep deprivation, and many other processes, using a manually curated list of 109 sleep genes.

RESULTS

Our predictions fit with prior knowledge of sleep regulation and identified key genes and pathways to pursue in follow-up studies. As an example, we focused on the NF-κB pathway and showed that chronic activation of NF-κB in a genetic mouse model impacted the sleep-wake patterns.

CONCLUSION

Our study highlights the power of machine learning in integrating prior knowledge and genome-wide data to study genetic regulation of complex behaviors such as sleep.

Sleepiness in adults: An umbrella review of a complex construct

Sleepiness involves many dimensions that require investigation. Since sleepiness is often defined operationally, we exhaustively inventoried all the assessment tools designed to measure it in an umbrella review, without any preconceptions, i.e. a review of reviews. We included all reviews and systematic reviews related to sleepiness assessment tools published up to March 2021. Three investigators independently assessed the eligibility of studies for inclusion and identified 36 relevant reviews. In total, 99 tools were identified and classified into 8 categories. We classified them depending on their category, their publication year and the number of mentions in the 36 included reviews. The 6 most frequently cited were the Epworth sleepiness scale, the multiple sleep latency test, the maintenance of wakefulness test, the Stanford sleepiness scale, the Karolinska sleepiness scale, and the psychomotor vigilance task. Despite the limitation that we may have missed some recently developed tools, this historical perspective on sleepiness measurement is a first step toward a better delineation of the different dimensions underlying the constructs of sleepiness, and will serve as a basis for further discussion in the clinical and research sleep community.

Variant-to-gene mapping followed by cross-species genetic screening identifies GPI-anchor biosynthesis as a regulator of sleep

Genome-wide association studies (GWAS) in humans have identified loci robustly associated with several heritable diseases or traits, yet little is known about the functional roles of the underlying causal variants in regulating sleep duration or quality. We applied an ATAC-seq/promoter focused Capture C strategy in human iPSC-derived neural progenitors to carry out a "variant-to-gene" mapping campaign that identified 88 candidate sleep effector genes connected to relevant GWAS signals. To functionally validate the role of the implicated effector genes in sleep regulation, we performed a neuron-specific RNA interference screen in the fruit fly, Drosophila melanogaster, followed by validation in zebrafish. This approach identified a number of genes that regulate sleep including a critical role for glycosylphosphatidylinositol (GPI)-anchor biosynthesis. These results provide the first physical variant-to-gene mapping of human sleep genes followed by a model organism-based prioritization, revealing a conserved role for GPI-anchor biosynthesis in sleep regulation.

Genetics of circadian rhythms and sleep in human health and disease

Circadian rhythms and sleep are fundamental biological processes integral to human health. Their disruption is associated with detrimental physiological consequences, including cognitive, metabolic, cardiovascular and immunological dysfunctions. Yet many of the molecular underpinnings of sleep regulation in health and disease have remained elusive. Given the moderate heritability of circadian and sleep traits, genetics offers an opportunity that complements insights from model organism studies to advance our fundamental molecular understanding of human circadian and sleep physiology and linked chronic disease biology. Here, we review recent discoveries of the genetics of circadian and sleep physiology and disorders with a focus on those that reveal causal contributions to complex diseases.

Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of Latinos

BACKGROUND

Sleep phenotypes have been reported to be associated with cognitive ageing outcomes. However, there is limited research using genetic variants as proxies for sleep traits to study their associations. We estimated associations between Polygenic Risk Scores (PRSs) for sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnoea (OSA) and measures of cogntive ageing in Hispanic/Latino adults.

METHODS

We used summary statistics from published genome-wide association studies to construct PRSs representing the genetic basis of each sleep trait, then we studied the association of the PRSs of the sleep phenotypes with cognitive outcomes in the Hispanic Community Healthy Study/Study of Latinos. The primary model adjusted for age, sex, study centre, and measures of genetic ancestry. Associations are highlighted if their p-value <0.05.

FINDINGS

Higher PRS for insomnia was associated with lower global cognitive function and higher risk of mild cognitive impairment (MCI) (OR = 1.20, 95% CI [1.06, 1.36]). Higher PRS for daytime sleepiness was also associated with increased MCI risk (OR = 1.14, 95% CI [1.02, 1.28]). Sleep duration PRS was associated with reduced MCI risk among short and normal sleepers, while among long sleepers it was associated with reduced global cognitive function and with increased MCI risk (OR = 1.40, 95% CI [1.10, 1.78]). Furthermore, adjustment of analyses for the measured sleep phenotypes and APOE-ε4 allele had minor effects on the PRS associations with the cognitive outcomes.

INTERPRETATION

Genetic measures underlying insomnia, daytime sleepiness, and sleep duration are associated with MCI risk. Genetic and self-reported sleep duration interact in their effect on MCI.

FUNDING

Described in Acknowledgments.

Putative Animal Models of Restless Legs Syndrome: A Systematic Review and Evaluation of Their Face and Construct Validity

Restless legs syndrome (RLS) is a sensorimotor disorder that severely affects sleep. It is characterized by an urge to move the legs, which is often accompanied by periodic limb movements during sleep. RLS has a high prevalence in the population and is usually a life-long condition. While its origins remain unclear, RLS is initially highly responsive to treatment with dopaminergic agonists that target D2-like receptors, in particular D2 and D3, but the long-term response is often unsatisfactory. Over the years, several putative animal models for RLS have been developed, mainly based on the epidemiological and neurochemical link with iron deficiency, treatment efficacy of D2-like dopaminergic agonists, or genome-wide association studies that identified risk factors in the patient population. Here, we present the first systematic review of putative animal models of RLS, provide information about their face and construct validity, and report their role in deciphering the underlying pathophysiological mechanisms that may cause or contribute to RLS. We propose that identifying the causal links between genetic risk factors, altered organ functions, and changes to molecular pathways in neural circuitry will eventually lead to more effective new treatment options that bypass the side effects of the currently used therapeutics in RLS, especially for long-term therapy.

Genome-Wide Association Study of Obstructive Sleep Apnea and Objective Sleep-related Traits Identifies Novel Risk Loci in Han Chinese Individuals

Rationale: Previous genetic studies of obstructive sleep apnea (OSA) have limitations in terms of precise case definition, integrated quantitative traits, and interpretation of genetic functions; thus, the heritability of OSA remains poorly explained. Objectives: To identify novel genetic variants associated with OSA and objective sleep-related traits and to explore their functional roles. Methods: A genome-wide association study was performed in 20,590 Han Chinese individuals (5,438 OSA and 15,152 control samples). Human samples and point mutation knockin mice were used for follow-up investigation of gene functions. Measurements and Main Results: Two characteristic study-wide significant loci (P < 2.63 × 10^-9) for OSA were identified: the PACRG intronic variant rs6455893 on 6q26 (odds ratio [OR] = 1.62; 95% confidence interval [CI], 1.39-1.89; P = 6.98 × 10^-10) and the missense variant rs3746804 (p.Pro267Leu) in the riboflavin transporter SLC52A3 on 20p13 (OR = 0.83; 95% CI, 0.79-0.88; P = 7.57 × 10^-10). In addition, 18 genome-wide significant loci associated with quantitative OSA and objective sleep-related traits were identified, 5 of which exceeded the study-wide significance threshold. Rs3746804 was associated with elevated serum riboflavin concentrations, and the corresponding mutation in mice increased riboflavin concentrations, suggesting that this variant may facilitate riboflavin uptake and riboflavin-dependent physiological activity. Conclusions: We identified several novel genome-wide significant loci associated with OSA and objective sleep-related traits. Our findings provide insight into the genetic architecture of OSA and suggest that SLC52A3 might be a therapeutic target, whereas riboflavin might be a therapeutic agent.

Causal association of sleep disturbances and low back pain: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have shown that low back pain (LBP) often coexists with sleep disturbances, however, the causal relationship remains unclear. In the present study, the causal relationship between sleep disturbances and LBP was investigated and the importance of sleep improvement in the comprehensive management of LBP was emphasized.

METHODS

Genetic variants were extracted as instrumental variables (IVs) from the genome-wide association study (GWAS) of insomnia, sleep duration, short sleep duration, long sleep duration, and daytime sleepiness. Information regarding genetic variants in LBP was selected from a GWAS dataset and included 13,178 cases and 164,682 controls. MR-Egger, weighted median, inverse-variance weighted (IVW), penalized weighted median, and maximum likelihood (ML) were applied to assess the causal effects. Cochran's Q test and MR-Egger intercept were performed to estimate the heterogeneity and horizontal pleiotropy, respectively. Outliers were identified and eliminated based on MR-PRESSO analysis to reduce the effect of horizontal pleiotropy on the results. Removing each genetic variant using the leave-one-out analysis can help evaluate the stability of results. Finally, the reverse causal inference involving five sleep traits was implemented.

RESULTS

A causal relationship was observed between insomnia-LBP (OR = 1.954, 95% CI: 1.119-3.411), LBP-daytime sleepiness (OR = 1.011, 95% CI: 1.004-1.017), and LBP-insomnia (OR = 1.015, 95% CI: 1.004-1.026), however, the results of bidirectional MR analysis between other sleep traits and LBP were negative. The results of most heterogeneity tests were stable and specific evidence was not found to support the disturbance of horizontal multiplicity. Only one outlier was identified based on MR-PRESSO analysis.

CONCLUSION

The main results of our research showed a potential bidirectional causal association of genetically predicted insomnia with LBP. Sleep improvement may be important in comprehensive management of LBP.

Further Studies on the Role of BTBD9 in the Cerebellum, Sleep-like Behaviors and the Restless Legs Syndrome

Genetic analyses have linked BTBD9 to restless legs syndrome (RLS) and sleep regulation. Btbd9 knockout mice show RLS-like motor restlessness. Previously, we found hyperactivity of cerebellar Purkinje cells (PCs) in Btbd9 knockout mice, which may contribute to the motor restlessness observed. However, underlying mechanisms for PC hyperactivity in Btbd9 knockout mice are unknown. Here, we used dissociated PC recording, brain slice recording and western blot to address this question. Our dissociated recording shows that knockout PCs had increased TEA-sensitive, Ca2+-dependent K+ currents. Applying antagonist to large conductance Ca2+-activated K+ (BK) channels further isolated the increased current as BK current. Consistently, we found increased amplitude of afterhyperpolarization and elevated BK protein levels in the knockout mice. Dissociated recording also shows a decrease in TEA-insensitive, Ca2+-dependent K+ currents. The result is consistent with reduced amplitude of tail currents, mainly composed of small conductance Ca2+-activated K+ (SK) currents, in slice recording. Our results suggest that BK and SK channels may be responsible for the hyperactivity of knockout PCs. Recently, BTBD9 protein was shown to associate with SYNGAP1 protein. We found a decreased cerebellar level of SYNGAP1 in Btbd9 knockout mice. However, Syngap1 heterozygous knockout mice showed nocturnal, instead of diurnal, motor restlessness. Our results suggest that SYNGAP1 deficiency may not contribute directly to the RLS-like motor restlessness observed in Btbd9 knockout mice. Finally, we found that PC-specific Btbd9 knockout mice exhibited deficits in motor coordination and balance similar to Btbd9 knockout mice, suggesting that the motor effect of BTBD9 in PCs is cell-autonomous.

Self-reported daytime napping, daytime sleepiness, and other sleep phenotypes in the development of cardiometabolic diseases: a Mendelian randomization study

AIMS

Sleep disorders are associated with an increased risk of cardiometabolic diseases in observational studies, but the causality remains unclear. In this study, we leveraged two-sample Mendelian randomization (MR) analyses to assess the causal associations of self-reported daytime napping, daytime sleepiness, and other sleep phenotypes with cardiometabolic diseases including ischaemic stroke (IS), coronary artery disease (CAD), heart failure (HF), and Type 2 diabetes mellitus (T2DM).

METHODS AND RESULTS

We selected genetic variants as instrumental variables for self-reported daytime napping, daytime sleepiness, morning person, insomnia, short sleep duration, and long sleep duration from European-descent genome-wide association studies (GWASs). Summary statistics for cardiometabolic diseases originated from four different GWASs with a total of 2 500 086 participants. We used the inverse-variance weighted method to explore the role of self-reported sleep phenotypes on the aetiology of cardiometabolic diseases in the main analyses, followed by several sensitivity analyses for robustness validation. Genetically predicted self-reported daytime napping [T2DM: OR, 1.56 (95% confidence interval, 1.21-2.02)], insomnia [IS: OR, 1.07 (1.04-1.11)]; CAD: OR, 1.13 (1.08-1.17); HF: OR, 1.10 (1.07-1.14); T2DM: OR, 1.16 (1.11-1.22); and short sleep duration [CAD: OR, 1.37 (1.21-1.55)] were causally associated with an elevated risk of cardiometabolic diseases. Moreover, genetically determined self-reported daytime sleepiness [CAD: OR, 2.05 (1.18-3.57); HF: OR, 1.82 (1.15-2.87)] and morning person [HF: 1.06 OR, (1.01-1.11)] had potential detrimental effect on cardiometabolic risks.

CONCLUSION

Self-reported daytime napping, insomnia, and short sleep duration had causal roles in the development of cardiometabolic diseases, while self-reported daytime sleepiness and morning person was the potential risk factor for cardiometabolic diseases.

Genetic estimation of correlations and causalities between multifaceted modifiable factors and gastro-oesophageal reflux disease

BACKGROUND

Gastro-oesophageal reflux disease (GORD) is a common gastrointestinal dysfunction that significantly affects the quality of daily life, and health interventions are challenging to prevent the risk of GORD. In this study, we used Mendelian randomization framework to genetically determine the causal associations between multifaceted modifiable factors and the risk of GORD.

MATERIALS AND METHODS

Sixty-six exposures with available instrumental variables (IVs) across 6 modifiable pathways were included in the univariable MR analysis (UVMR). Summary-level genome-wide association studies (GWAS) datasets for GORD were retrieved from the Neale Lab (GORD _Neale , Ncases = 29975, Ncontrols = 390556) and FinnGen (GORD _Finn , Ncases = 13141, Ncontrols = 89695). Using the METAL software, meta-analysis for single nucleotide polymorphisms (SNPs) from GORD _Neale and GORD _Finn was conducted with an inverse variance weighted (IVW) fixed-effect model. Moreover, we leveraged partition around medoids (PAM) clustering algorithm to cluster genetic correlation subtypes, whose hub exposures were conditioned for multivariable MR (MVMR) analyses. P-values were adjusted with Bonferroni multiple comparisons.

RESULTS

Significant causal associations were identified between 26 exposures (15 risk exposures and 11 protective exposures) and the risk of GORD. Among them, 13 risk exposures [lifetime smoking, cigarette consumption, insomnia, short sleep, leisure sedentary behavior (TV watching), body mass index (BMI), body fat percentage, whole body fat mass, visceral adipose tissue, waist circumference, hip circumference, major depressive disorder, and anxious feeling], and 10 protective exposures (leisure sedentary behavior (computer use), sitting height, hand grip strength (left and right), birth weight, life satisfaction, positive affect, income, educational attainment, and intelligence) showed novel significant causal associations with the risk of GORD. Moreover, 13 exposures still demonstrated independent associations with the risk of GORD following MVMR analyses conditioned for hub exposures (educational attainment, smoking initiation and BMI). In addition, 12 exposures showed suggestive causal associations with the risk of GORD.

CONCLUSION

This study systematically elucidated the modifiable factors causally associated with the risk of GORD from multifaceted perspectives, which provided implications for prevention and treatment of GORD.

Self-reported sleepiness associates with greater brain and cortical volume and lower prevalence of ischemic covert brain infarcts in a community sample

STUDY OBJECTIVES

We evaluated if self-reported sleepiness was associated with neuroimaging markers of brain aging and ischemic damage in a large community-based sample.

METHODS

Participants from the Framingham Heart Study Offspring cohort (n = 468, 62.5 ± 8.7 years old, 49.6%M) free of dementia, stroke, and neurological diseases, completed sleep questionnaires and polysomnography followed by magnetic resonance imaging (MRI), 3 years later on average. We used linear and logistic regression models to evaluate the associations between Epworth Sleepiness Scale (ESS) scores and total brain, cortical and subcortical gray matter, and white matter hyperintensities volumes, and the presence of covert brain infarcts.

RESULTS

Higher sleepiness scores were associated with larger total brain volume, greater cortical gray matter volume, and a lower prevalence of covert brain infarcts, even when adjusting for a large array of potential confounders, including demographics, sleep profiles and disorders, organic health diseases, and proxies for daytime cognitive and physical activities. Interactions indicated that more sleepiness was associated with larger cortical gray matter volume in men only and in APOE ε4 noncarriers, whereas a trend for smaller cortical gray matter volume was observed in carriers. In longitudinal analyses, those with stable excessive daytime sleepiness over time had greater total brain and cortical gray matter volumes, whereas baseline sleepiness scores were not associated with subsequent atrophy or cognitive decline.

CONCLUSION

Our findings suggest that sleepiness is not necessarily a marker of poor brain health when not explained by diseases or sleep debt and sleep disorders. Rather, sleepiness could be a marker of preserved sleep-regulatory processes and brain health in some cases.

Depression and bipolar disorder subtypes differ in their genetic correlations with biological rhythms

Major Depression and Bipolar Disorder Type I (BIP-I) and Type II (BIP-II), are characterized by depressed, manic, and hypomanic episodes in which specific changes of physical activity, circadian rhythm, and sleep are observed. It is known that genetic factors contribute to variation in mood disorders and biological rhythms, but unclear to what extent there is an overlap between their underlying genetics. In the present study, data from genome-wide association studies were used to examine the genetic relationship between mood disorders and biological rhythms. We tested the genetic correlation of depression, BIP-I, and BIP-II with physical activity (overall physical activity, moderate activity, sedentary behaviour), circadian rhythm (relative amplitude), and sleep features (sleep duration, daytime sleepiness). Genetic correlations of depression, BIP-I, and BIP-II with biological rhythms were compared to discover commonalities and differences. A gene-based analysis tested for associations of single genes and common circadian genes with mood disorders. Depression was negatively correlated with overall physical activity and positively with sedentary behaviour, while BIP-I showed associations in the opposite direction. Depression and BIP-II had negative correlations with relative amplitude. All mood disorders were positively correlated with daytime sleepiness. Overall, we observed both genetic commonalities and differences across mood disorders in their relationships with biological rhythms: depression and BIP-I differed the most, while BIP-II was in an intermediate position. Gene-based analysis suggested potential targets for further investigation. The present results suggest shared genetic underpinnings for the clinically observed associations between mood disorders and biological rhythms. Research considering possible joint mechanisms may offer avenues for improving disease detection and treatment.

The association between sleep and depressive symptoms in US adults: data from the NHANES (2007-2014)

AIMS

To assess the association of sleep factors (sleep duration, trouble sleeping, sleep disorder) and combined sleep behaviours with the risk of clinically relevant depression (CRD).

METHODS

A total of 17 859 participants (8806 males and 9053 females) aged 20-79 years from the National Health and Nutrition Examination Survey (NHANES) 2007-2014 waves were included. Sleep duration, trouble sleeping and sleep disorder were asked in the home by trained interviewers using the Computer-Assisted Personal Interviewing (CAPI) system. The combined sleep behaviours were referred to as 'sleep patterns (healthy, intermediate and poor)', with a 'healthy sleep pattern' defined as sleeping 7-9 h per night with no self-reported trouble sleeping or sleep disorders. And intermediate and poor sleep patterns indicated 1 and 2-3 sleep problems, respectively. Weighted logistic regression was performed to evaluate the association of sleep factors and sleep patterns with the risk of depressive symptoms.

RESULTS

The total prevalence of CRD was 9.5% among the 17 859 participants analysed, with females having almost twice as frequency than males. Compared to normal sleep duration (7-9 h), both short and long sleep duration were linked with a higher risk of CRD (short sleep: OR: 1.66, 95% CI: 1.39-1.98; long sleep: OR: 2.75, 95% CI: 1.93-3.92). The self-reported sleep complaints, whether trouble sleeping or sleep disorder, were significantly related with CRD (trouble sleeping: OR: 3.04, 95% CI: 2.59-3.56; sleep disorder: OR: 1.83, 95% CI: 1.44-2.34). Furthermore, the correlations appeared to be higher for individuals with poor sleep pattern (OR: 5.98, 95% CI: 4.91-7.29).

CONCLUSIONS

In this national representative survey, it was shown that there was a dose-response relationship between sleep patterns and CRD.

Hunt for mammalian sleep-regulating genes

Genetics is one of the various approaches adopted to understand and control mammalian sleep. Reverse genetics, which is usually applied to analyze sleep in gene-deficient mice, has been the mainstream field of genetic studies on sleep for the past three decades and has revealed that various molecules, including orexin, are involved in sleep regulation. Recently, forward genetic studies in humans and mice have identified gene mutations responsible for heritable sleep abnormalities, such as SIK3, NALCN, DEC2, the neuropeptide S receptor, and β1 adrenergic receptor. Furthermore, the protein kinase A-SIK3 pathway was shown to represent the intracellular neural signaling for sleep need. Large-scale genome-wide analyses of human sleep have been conducted, and many gene loci associated with individual differences in sleep have been found. The development of genome-editing technology and gene transfer by an adeno-associated virus has updated and expanded the genetic studies on mammals. These efforts are expected to elucidate the mechanisms of sleep–wake regulation and develop new therapeutic interventions for sleep disorders.

Orexin 2 receptor-selective agonist danavorexton improves narcolepsy phenotype in a mouse model and in human patients

Narcolepsy type 1 (NT1) is a sleep disorder caused by a loss of orexinergic neurons. Narcolepsy type 2 (NT2) is heterogeneous; affected individuals typically have normal orexin levels. Following evaluation in mice, the effects of the orexin 2 receptor (OX2R)-selective agonist danavorexton were evaluated in single- and multiple-rising-dose studies in healthy adults, and in individuals with NT1 and NT2. In orexin/ataxin-3 narcolepsy mice, danavorexton reduced sleep/wakefulness fragmentation and cataplexy-like episodes during the active phase. In humans, danavorexton administered intravenously was well tolerated and was associated with marked improvements in sleep latency in both NT1 and NT2. In individuals with NT1, danavorexton dose-dependently increased sleep latency in the Maintenance of Wakefulness Test, up to the ceiling effect of 40 min, in both the single- and multiple-rising-dose studies. These findings indicate that OX2Rs remain functional despite long-term orexin loss in NT1. OX2R-selective agonists are a promising treatment for both NT1 and NT2.