Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank

Investigating the link between genetic predictive factors of brain functional networks and two specific sleep disorders: Sleep apnoea and snoring

BACKGROUND

Sleep disorders are a widespread public health issue globally. Investigating the causal relationship between resting-state brain functional abnormalities and sleep disorders can provide scientific evidence for precision medicine interventions.

METHODS

We screened single nucleotide polymorphisms (SNPs) associated with rs-fMRI phenotype as instrumental variables Using bidirectional two-sample Mendelian randomization (MR), mediation MR, and multivariate MR based on Bayesian methods, the study tested the causal relationship between genetically predicted rs-fMRI and nine common sleep disorders.

RESULTS

The main IVW-MR analysis identified four rs-fMRI phenotypes that are causally associated with the risk of sleep disorders. For example, increased amplitude in nodes of the parietal, precuneus, occipital, temporal, and cerebellum regions, as well as the default mode network (DMN), central executive network (CEN) and attention network (AN) was associated with an increased risk of sleep apnoea. Enhanced neural activity in the calcarine or lingual and cerebellum regions and increased functional connectivity with the visual and subcortical-cerebellum networks was associated with a reduced risk of snoring. The mediation MR analysis shows that, BMI plays a significant mediating role in the risk of sleep apnoea by modulating the amplitude of nodes in the parietal, temporal, and cerebellum regions, as well as the connectivity changes in the DMN, CEN, and AN.

CONCLUSIONS

This study identified three rs-fMRI phenotypes linked to increased sleep apnoea risk and one associated with decreased snoring risk, providing an important target for the treatment of sleep disorders at the level of brain functional networks.

Insights into modifiable risk factors of migraine: a Mendelian randomization analysis

OBJECTIVES

Increasing epidemiological evidence has reported that various factors are associated with migraine risk and subtypes. Nevertheless, definitive conclusions regarding whether the putative modifiable risk factors are causally related to the pathogenesis of migraine have not been drawn.

METHODS

Using single-nucleotide polymorphisms as instrumental variables, we conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal effects of 38 modifiable factors, including dietary nutrients, lifestyle factors, cardiometabolic diseases, and associated traits, as well as reproductive characteristics and sex hormones, on the risk of migraine, migraine with aura (MA), and migraine without aura (MO). Subsequently, meta-analyses were performed to combine causal estimates from two independent genome-wide association studies.

RESULTS

In the combined findings with multiple test correction, genetically predicted higher alcohol intake frequency (odds ratio [OR]: 1.25; 95% confidence interval [CI]: 1.12-1.40), lifetime smoking index (OR: 1.24; 95% CI: 1.08-1.42), insomnia (OR: 1.20; 95% CI: 1.17-1.24), long sleep duration (OR: 1.26; 95% CI: 1.07-1.50), and hypertension (OR: 1.76; 95% CI: 1.47-2.11) were causally linked to migraine incidence. Subgroup analyses revealed higher carbohydrate and sugar intake, alcohol consumption frequency, lifetime smoking index, insomnia, and hypertension causally increased susceptibility to MA, while later age at first birth (AFB) had a protective effect on MA risk. Meanwhile, the MR findings revealed a detrimental association between alcohol intake frequency, insomnia, hypertension, and early AFB and MO incidence.

DISCUSSION

Overall, our study demonstrated various causal risk factors for migraine and its subtypes risk, providing insights into its pathogenesis and potential prevention strategies. Further research is needed to validate these findings and explore their clinical implications and underlying mechanisms.

The genetic overlap and causal relationship between attention deficit hyperactivity disorder and obstructive sleep apnea: a large-scale genomewide cross-trait analysis

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) and Obstructive sleep apnea (OSA) are highly clinically co-occurring, but the mechanisms behind this remain unclear, so this article analyzes the reasons for the co-morbidities from a genetic perspective.

METHODS

We examined the genetic architecture of ADHD and OSA based on the large genome-wide association studies (GWAS). The global genetic relationship between OSA and ADHD was explored. Cross-trait analysis from single nucleotide polymorphism (SNP) and gene level was performed subsequently to detect the crucial genomic regions. Finally, we revealed the anatomical change on which genetic overlap relies and further explored whether genetic factors exert a causal effect.

RESULTS

After using both linkage disequilibrium score regression (LDSC) and High-definition likelihood inference (HDL) methods, we identified a significant genetic correlation between OSA and ADHD (PLDSC = 2.45E-28, PHDL = 1.09E-25), demonstrating a consistent direction. Furthermore, through the application of various cross-trait methods, we pinpointed 5 loci and 57 genes involved in regulating the co-occurrence of these disorders. These genetic regions were thought to be associated with the prefrontal lobes (P = 3.07E-06) and the nucleus accumbens basal ganglia (P = 2.85E-06). Lastly, utilizing Mendelian randomization (MR), we established a link indicating that individuals with ADHD were at an elevated risk of developing OSA (PIVM = 0.02, OR (95%CI):1.09 (1.01-1.17)).

CONCLUSIONS

This study reveals a strong genetic correlation between ADHD and OSA. It offers insights for future drug target development and sleep management in ADHD.

Snoring as a Possible Protective Factor for Temporomandibular Joint Disorders

BACKGROUND

Previous studies have linked sleep quality to temporomandibular joint disorders (TMD), suggesting a role for snoring in this association. However, the directionality of this relationship remains a subject of debate. This investigation aimed to elucidate the connections between snoring and TMD.

METHODS

This research employed a two-sample Mendelian randomization (MR) approach, leveraging publicly available large-scale genome-wide association study (GWAS) data on snoring and TMD. We utilised a suite of analytical methods, including the inverse variance weighted (IVW) method, maximum likelihood estimation, adjusted profile score, weighted median, MR-Egger regression, and a series of sensitivity analyses, to rigorously assess the existence of relationships.

RESULTS

Our findings indicate that a greater genetic predisposition to snoring is significantly associated with a reduced risk of TMD (IVW method; odds ratio [OR] = 0.156, 95% confidence interval [CI] = 0.028-0.843, p = 0.0309). Conversely, the analysis did not support a potential influence of TMD on snoring susceptibility (IVW method; 95% CI = 0.990 to 1.002, p = 0.1926). Additionally, our sensitivity analyses did not reveal any significant pleiotropy that could bias these findings.

CONCLUSION

This MR study provides limited but novel genetic evidence supporting a potential causal link between snoring and a decreased risk of developing TMD. On the other hand, it does not substantiate an effect of TMD on the likelihood of snoring.

Poor sleep and high rheumatoid arthritis risk: Evidence from large UK Biobank cohort

OBJECTIVE

To evaluate the relationship between sleep behaviors and rheumatoid arthritis (RA) risk.

METHODS

First, based on large-scale data from the UK Biobank, we analyzed the associations between multiple sleep factors and RA risk and calculated a poor sleep score (PSS) to assess their combined effect. Then we constructed genetic risk scores (GRS) based on a large genome-wide association study and assessed the interaction or combined effect of sleep and genetic factors on RA risk. Finally, we conducted a case-control study to explore the effect of RA on sleep.

RESULTS

Sleep duration, getting up, napping during the day, insomnia, and daytime dozing were associated with the risk of RA, but no associations were observed for chronotype and snoring with RA. Participants in the high genetic risk and high PSS group had a 363.1% higher risk of developing RA compared to those with low genetic risk and low PSS. We also found that women were more likely than men to be affected by the combined effects of PSS and GRS. In the case-control study, there were statistically significant associations of RA with getting up, PSS grade and PSS.

CONCLUSIONS

Unhealthy sleep patterns were associated with increasing risk of RA among participants with low, intermediate, or high genetic risk.

The role of sleep traits in prostate, endometrial, and epithelial ovarian cancers: An observational and Mendelian randomisation study

Background

Sleep traits may influence cancer risk; however, their associations with prostate (PCa), endometrial (ECa), and epithelial ovarian (EOCa) cancer remain unclear.

Methods

We conducted an observational analysis using the UK Biobank cohort and a two-sample Mendelian randomisation (MR) analysis to investigate the association of six sleep traits-duration, chronotype, insomnia, daytime napping, daytime sleepiness, and snoring-with PCa, ECa, and EOCa risk. Cox proportional hazards models were used for the observational analysis, while the inverse variance-weighted (IVW) method was applied in MR, with multiple sensitivity analyses. A Bonferroni correction accounted for multiple testing.

Results

Among 8,608 PCa, 1,079 ECa, and 680 EOCa incident diagnoses (median follow-up: 6.9 years), snoring was associated with reduced EOCa risk (HR=0.78, 95%CI: 0.62-0.98), while daytime sleepiness was associated with increased EOCa risk (HR=1.23, 95%CI: 1.03-1.47). However, these associations were not confirmed in MR. MR suggested higher odds of PCa (OR IVW =1.05, 95%CI: 1.01-1.11) and aggressive PCa (OR IVW =1.10, 95%CI: 1.02-1.19) for evening compared to morning chronotype. None of the findings survived multiple testing correction.

Conclusion

Sleep traits were not associated with PCa, ECa, or EOCa risk, but evening chronotype may increase PCa risk. Further research is needed to verify this association and investigate potential underlying mechanisms.

Impact

The proposed results have potential utility in reproductive cancer prevention.

What is already known on this topic

Sleep traits have been implicated in cancer risk, but their associations with prostate, endometrial, and epithelial ovarian cancer remain unclear.

What this study adds

This study found suggestive evidence that an evening chronotype may be associated with an increased risk of overall and aggressive prostate cancer.

How this study might affect research practice or policy

Further research is needed to confirm the potential association between chronotype and prostate cancer risk, which could inform personalised cancer prevention strategies.

Cardiovascular Effect of Snoring in Asians: What Do Biobank and Genomic Studies Say?

See related article

Association of Sleep Traits With Venous Thromboembolism: Prospective Cohort and Mendelian Randomization Studies

Previous research indicates an association between sleep traits and venous thromboembolism (VTE) risk, though causal relationships remain uncertain. This study evaluated combined and independent associations between sleep traits and VTE risk using UK Biobank data and explored the causal associations between sleep traits and VTE through two-sample Mendelian randomization (MR) analyses. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the associations between the healthy sleep score, as well as individual sleep traits (including sleep duration, insomnia, daytime sleepiness, snoring, and chronotype), and VTE risk were calculated using Cox proportional hazards regression models. Additionally, the two-sample MR analyses used the inverse-variance weighted method to determine odds ratios (ORs) and 95% CIs for causal associations. In the cohort analysis, 314 077 VTE-free participants were followed for a median of 12.3 years, during which 7176 VTE cases occurred. In comparison to those with a sleep score of 0-1, participants with a score of 5 were associated with a 30% lower risk of VTE (HR: 0.70; 95% CI: 0.61-0.80). A U-shaped association was noted between sleep duration and VTE risk. Both short (≤ 6 h) and long (≥ 9 h) sleep durations increased VTE risk. Excessive daytime sleepiness, snoring, and evening chronotype also elevated VTE risk. MR analyses supported a causal relationship for short sleep duration (OR: 1.24; 95% CI: 1.04-1.47) with VTE risk, while other sleep traits showed no causal association. These findings underscore the importance of optimal sleep in reducing VTE risk.

Real-Time Snoring Detection Using Deep Learning: A Home-Based Smartphone Approach for Sleep Monitoring

Background

Despite the prevalence of sleep-related disorders, few studies have developed deep learning models to predict snoring using home-recorded smartphone audio. This study proposes a real-time snoring detection method utilizing a Vision Transformer-based deep learning model and smartphone recordings.

Methods

Participants' sleep-breathing sounds were recorded using smartphones, with concurrent Level I or II polysomnography (PSG) conducted in home or hospital settings. A total of 200 minutes of smartphone audio per participant, corresponding to 400 30-second sleep stage epochs on PSG, were sampled. Each epoch was annotated independently by two trained labelers, with snoring labeled only when both agreed. Model performance was evaluated by epoch-by-epoch prediction accuracy and correlation between observed and predicted snoring ratios.

Results

The study included 214 participants (85,600 epochs). Hospital audio data from 105 participants (42,000 epochs) were used for training, while home audio data from 109 participants were split into 54 participants (21,600 epochs) for training and 55 participants (22,000 epochs) for testing. On the test dataset, the model demonstrated a sensitivity of 89.8% and a specificity of 91.3%. Correlation analysis showed strong agreement between observed and predicted snoring ratios (r = 0.97, 95% CI: 0.95-0.99).

Conclusion

This study demonstrates the feasibility of using deep learning for real-time snoring detection from home-recorded smartphone audio. With high accuracy and scalability, the approach offers a practical and accessible tool for monitoring sleep-related disorders, paving the way for home-based sleep health management solutions.

Sleep traits causally affect epigenetic age acceleration: a Mendelian randomization study

Sleep disorders (SDs) are a common issue in the elderly. Epigenetic clocks based on DNA methylation (DNAm) are now considered highly accurate predictors of the aging process and are associated with age-related diseases. This study aimed to investigate the causal relationship between sleep traits and the epigenetic clock using Mendelian randomization (MR) analysis. The genome-wide association study (GWAS) statistics for epigenetic clocks (HannumAge, intrinsic epigenetic age acceleration [IEAA], PhenoAge, and GrimAge) and sleep traits were obtained from the UK Biobank (UKB), 23andMe and Finngen. Moreover, crucial instrumental variables (IVs) were evaluated. Inverse variance weighted (IVW), MR-Egger, weighted median (WM), weighted mode, and simple mode methods were employed to assess the causal relationship between them. Multiple analyses were performed for quality control evaluation. Our study showed that self-reported insomnia may speed up the aging process by GrimAge clock, while GrimAge acceleration could faintly reduce self-reported insomnia. Epigenetic clocks mainly influence sleep traits by PhenoAge and GrimAge with weak effects. This may indicate that early interventions of SDs could be a breaking point for aging and age-related diseases. Further studies are required to elucidate the potential mechanisms involved.

Genetic Evidence Supporting a Causal Role of Snoring in Keratoconus: A Bidirectional Mendelian Randomization Study

PURPOSE

To clarify the controversial causal association between snoring and keratoconus (KCN), which is crucial in clinical prevention and treatment.

METHODS

This is a 2-sample bidirectional mendelian randomization (MR) case-control study. MR is an innovative method that uses genetic variation as a natural experiment to investigate the causal relationships between potentially modifiable risk factors and health outcomes in observational data. The single nucleotide polymorphisms associated with snoring were retrieved from the UK biobank cohort with 218,346 participants (61,792 cases and 156,554 controls). The summary statistics of KCN were obtained from the European ancestry with 209,598 subjects (311 cases and 209,287 controls). The inverse-variance-weighted method was applied as the primary estimate, whereas weighted median and MR-pleiotropy residual sum and outlier played a subsidiary role.

RESULTS

Elevated risk of snoring showed a robust causal effect on KCN (inverse-variance-weighted: causal effect = 9.821, 95% confidence interval [CI], 1.944-17.699, P = 0.015), which was consistent with complementary methods of the weighted median (causal effect = 11.117, 95% CI, 2.603-19.631, P = 0.010), maximum likelihood (causal effect = 10.245, 95% CI, 3.967-16.523, P = 0.001), and MR-pleiotropy residual sum and outlier (causal effect = 9.793, 95% CI, 2.316-17.269, P = 0.028). However, there was no causality of KCN on the increasing risk of snoring.

CONCLUSIONS

This study provides genetic evidence supporting the causal role of snoring on KCN. Our findings provide new insights into potential strategies to manage KCN.

Sleep characteristics and intervertebral disc degeneration risk: an observational and Mendelian randomization study

OBJECTIVES

Sleep disorders are considered a risk factor for aging and skeletal degeneration, but their impact on intervertebral disc degeneration (IDD) remains unclear. The aim of this study was to assess associations between sleep characteristics and IDD, and to identify potential causal relationships.

METHODS

Exposure factors included six unhealthy sleep characteristics: insomnia, short sleep duration (< 7 h), long sleep duration (≥ 9 h), evening chronotype, daytime sleepiness, and snoring. The primary outcomes included cervical disc degeneration (CDD) and lumbar disc degeneration (LDD). Firstly, we examined the associations between sleep characteristics and IDD risk in 368,348 participants from the UK Biobank using Cox proportional hazards model. Two-sample Mendelian randomization (MR) analyses were conducted to validate associations found in observational analyses, using genome-wide association data from the UK Biobank and FinnGen consortia.

RESULTS

During a median follow-up time of 13.8 years, a total of 1,637 cases of CDD and 7,654 cases of LDD were identified. Observational analyses found that almost all unhealthy sleep characteristics were associated with an elevated risk of IDD, except snoring. Conversely, the risk of IDD decreased linearly with an increasing number of healthy sleep characteristics. MR analyses supported a causal association between genetically determined insomnia and increased risk of LDD (OR 1.25 [1.07-1.47]), and between short sleep duration and increased risk of both IDD phenotypes (OR 5.41 [1.95-15.01] for CDD; OR 3.48 [1.76-6.89] for LDD). However, long sleep duration was causally associated with a reduced risk of LDD (OR 0.13 [0.03-0.53]), which contrasts with the observational findings.

CONCLUSION

We found associations between multiple sleep characteristics and IDD risk and confirmed that insomnia and short sleep duration increased IDD risk. Although more research is needed to confirm the underlying mechanisms, prioritizing interventions to improve sleep quality and ensure adequate sleep could help mitigate IDD.

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, so together may provide a more complete picture of sleep health, while 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 (including potential causal links) to behavioral, psychological, and cardiometabolic traits.

Snoring and risk of dementia: a prospective cohort and Mendelian randomization study

STUDY OBJECTIVES

The association between snoring, a very common condition that increases with age, and dementia risk is controversial. We aimed to investigate the observational and causal relationship between snoring and dementia, and to elucidate the role of body mass index (BMI).

METHODS

Using data from 451 250 participants who were dementia-free at baseline, we examined the association between self-reported snoring and incident dementia using Cox proportional-hazards models. Causal relationship between snoring and Alzheimer's disease (AD) was examined using bidirectional two-sample Mendelian randomization (MR) analysis.

RESULTS

During a median follow-up of 13.6 years, 8325 individuals developed dementia. Snoring was associated with a lower risk of all-cause dementia (hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.89 to 0.98) and AD (HR 0.91; 95% CI 0.84 to 0.97). The association was slightly attenuated after adjusting for BMI, and was stronger in older individuals, APOE ε4 allele carriers, and during shorter follow-up periods. MR analyses suggested no causal effect of snoring on AD; however, genetic liability to AD was associated with a lower risk of snoring. Multivariable MR indicated that the effect of AD on snoring was primarily driven by BMI.

CONCLUSIONS

The phenotypic association between snoring and lower dementia risk likely stems from reverse causation, with genetic predisposition to AD associated with reduced snoring. This may be driven by weight loss in prodromal AD. Increased attention should be paid to reduced snoring and weight loss in older adults as potential early indicators of dementia risk.

Genome-wide meta-analysis identifies 22 loci for normal tension glaucoma with significant overlap with high tension glaucoma

Primary open-angle glaucoma typically presents as two subtypes. This study aimed to elucidate the shared and distinct genetic architectures of normal-tension (NTG) and high-tension glaucoma (HTG), motivated by the need to develop intraocular pressure (IOP)-independent drug targets for the disease. We conducted a comprehensive multi-ethnic meta-analysis, prioritized variants based on functional annotation, and explored drug-gene interactions. We further assessed the genetic overlap between NTG and HTG using pairwise GWAS analysis. We identified 22 risk loci associated with NTG, 17 of which have not previously been reported for NTG. Two loci, BMP4 and TBKBP1, have not previously been associated with glaucoma at the genome-wide significance level. Our results indicate that while there is a significant overlap in risk loci between tension subtypes, the magnitude of the effect tends to be lower in NTG compared to HTG, particularly for IOP-related loci. Additionally, we identified a potential role for biologic immunomodulatory treatments as neuroprotective agents.

Genetically Predicted Sleep Traits and Sensorineural Hearing Loss: A Mendelian Randomization Study

OBJECTIVE

Observational studies suggest a potential association between sleep characteristics, sensorineural hearing loss (SNHL), and sudden SNHL (SSNHL), but causal evidence is scarce. We sought to clarify this issue using two-sample Mendelian randomization analysis.

METHODS

The inverse-variance weighted (IVW) method was performed as primary analysis to assess bidirectional causal associations between sleep traits (chronotype, sleep duration, insomnia, daytime sleepiness, and snoring) and SNHL/SSNHL using publicly available Genome-Wide Association Studies summary data from two large consortia (UK Biobank and FinnGen). Sensitivity analyses, including Mendelian randomization (MR)-Egger, Mendelian randomization pleiotropy residual sum and outlier, weight median, Cochran's Q test, leave-one-out analysis, and potential pleiotropy analysis, were conducted to ensure robustness.

RESULTS

IVW analysis found suggestive associations of morning chronotype (odds ratio [OR] = 1.08, 95% confidence interval [CI] = 1.01-1.16, p = 0.031) and daytime sleepiness (OR = 1.88, 95% CI = 1.24-2.87, p = 0.003) with SNHL onset. Additionally, morning chronotype was nominally associated with SSNHL onset using IVW method (OR = 1.37, 95% CI = 1.10-1.71, p = 0.006). However, there was no evidence for the causal effect of SNHL and SSNHL on different sleep traits (all p > 0.05). Sensitivity analysis showed that the results were stable.

CONCLUSION

Within the MR limitations, morning chronotype and daytime sleepiness were underlying causal contributors to the burden of SNHL, indicating that optimal sleep might facilitate the prevention and development of SNHL.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:4723-4729, 2024.

Causal Links Between Systemic Disorders and Keratoconus in European Population

PURPOSE

To establish the presence of a causal linkage between prevalent systemic diseases and keratoconus (KC).

DESIGN

Mendelian randomization (MR) analysis.

METHODS

After an exhaustive screening process, genetic variants linked to various systemic diseases were identified as instrumental variables at the genome-wide significance level. Subsequently, MR analyses were conducted to elucidate their potential causal connection with KC (N = 26,742). The encompassed systemic ailments comprise diabetes, hay fever/allergic rhinitis/eczema, obstructive sleep apnea, thyroid dysfunction, aortic aneurysm, major depressive disorder, inflammatory bowel disease (including Crohn's disease and ulcerative colitis), and mitral valve prolapse. Our study adheres to the principles of Strengthening the Reporting of Observational Studies in Epidemiology Using MR guidelines.

RESULTS

Using inverse variance weighting as the primary MR analysis method, our findings revealed that hay fever/allergic rhinitis/eczema (odds ratio, 10.144; 95% CI, 2.441-42.149; P = .001) and ulcerative colitis (odds ratio, 1.147; 95% CI, 1.054-1.248; P = .002) were associated with an increased risk of KC within the largest population under scrutiny. Conversely, the prolonged hyperglycemic state did not exhibit a potentially protective effect in delaying the pathogenesis of KC, and no correlation was observed between the two (odds ratio, 0.320; 95% CI, 0.029-3.549; P = .353). Also, obstructive sleep apnea, thyroid function, aortic aneurysm, major depressive disorder, Crohn's disease, and mitral valve prolapse did not exhibit a causal association with KC (P > .05 for all comparisons).

CONCLUSIONS

This study indicates an increased risk of KC related to hay fever/allergic rhinitis/eczema and ulcerative colitis, with diabetes not providing a protective effect. These findings may potentially contribute some insights to inform clinical interventions.

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.

[Causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus: a two-sample bidirectional Mendelian randomization study]

OBJECTIVE

To explore the causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus (iNPH) using two-sample bidirectional Mendelian randomization.

METHODS

The exposure data including 8 sleep phenotypes used in this study were obtained from GWAS catalog, FinnGenR10 and MRCIEU GWAS. The outcome data for idiopathic normal-pressure hydrocephalus were obtained from FinnGen R10. We used the inverse-variance weighted (IVW) method to perform the principal analyses. Cochrane Q-statistics test was used to assess the heterogeneity and MR Egger‑intercept test performed to evaluate the pleiotropy for sensitivity analyses.

RESULTS

IVW result showed that frequent daytime nap was associated with higher odds of iNPH (OR=3.3393, 95 CI% : 1.0646-10.4742, P=0.0270). Cochrane Q-statistics test and MR Egger‑intercept test showed that the MR analysis had no pleiotropy or heterogeneity (P > 0.05). The external validation reproduced this result (OR=2.5660, 95 CI% : 1.1680-5.6373, P=0.0189; OR=4.0424, 95 CI% : 1.5709-10.4024, P=0.0038). Reverse Mendelian randomization suggested that iNPH did not have significant impact on sleep phenotype.

CONCLUSION

The frequency of daytime naps is causally associated with iNPH, and reducing the frequency of weekly daytime naps can reduce the risk of iNPH in the elderly population.

The Genetics of Human Sleep and Sleep Disorders

Healthy sleep is vital for humans to achieve optimal health and longevity. Poor sleep and sleep disorders are strongly associated with increased morbidity and mortality. However, the importance of good sleep continues to be underrecognized. Mechanisms regulating sleep and its functions in humans remain mostly unclear even after decades of dedicated research. Advancements in gene sequencing techniques and computational methodologies have paved the way for various genetic analysis approaches, which have provided some insights into human sleep genetics. This review summarizes our current knowledge of the genetic basis underlying human sleep traits and sleep disorders. We also highlight the use of animal models to validate genetic findings from human sleep studies and discuss potential molecular mechanisms and signaling pathways involved in the regulation of human sleep.

Disadvantaged social status contributed to sleep disorders: An observational and genome-wide gene-environment interaction analysis

BACKGROUND

Sleep is a natural and essential physiological need for individuals. Our study aimed to research the associations between accumulated social risks and sleep disorders.

METHODS

In this study, we came up with a polysocial risk score (PsRS), which is a cumulative social risk index composed of 13 social determinants of health. This research includes 239,165 individuals with sleep disorders and social determinants of health data from the UK Biobank cohort. First, logistic regression models were performed to examine the associations of social determinants of health and sleep disorders, including chronotype, narcolepsy, insomnia, snoring, short and long sleep duration. Then, PsRS was calculated based on statistically significant social determinants of health for each sleep disorder. Third, a genome-wide gene-environment interaction study was conducted to explore the interactions between single-nucleotide polymorphisms and PsRS in relation to sleep disorders.

RESULTS

Higher PsRS scores were associated with worse sleep status, with the adjusted odds ratio (OR) ranging from 1.10 (95% Confidence interval [CI]: 1.09-1.11) to 1.29 (95% CI: 1.27-1.30) for sleep disorders. Emotional stress (OR = 1.36, 95% CI: 1.28-1.43) and not in paid employment (OR = 2.62, 95% CI: 2.51-2.74) were found to have significant contributions for sleep disorders. Moreover, multiple single-nucleotide polymorphisms were discovered to have interactions with PsRS, such as FRAS1 (P = 2.57 × 10-14) and CACNA1A (P = 8.62 × 10-14) for narcolepsy, and ACKR3 (P = 1.24 × 10-8) for long sleep.

CONCLUSIONS

Our findings suggested that cumulative social risks was associated with sleep disorders, while the interactions between genetic susceptibility and disadvantaged social status are risk factors for the development of sleep disorders.

Gut microbiome and metabolic pathways linked to sleep quality

Sleep quality is a vital determinant of human health as sleep disorders are associated with cognitive deficits, and chronic sleep deprivation is associated with a broad range of health complications. Previous studies on the association between the gut microbiome and sleep quality have been constrained by small sample sizes or have focused on specific sleep disorders, thus yielding inconsistent results. Herein, we investigated the relationship between microbial composition and sleep quality in a cohort of 159 Koreans. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI), determined through a self-administered questionnaire. Gut microbiome analyses were performed using 16S rRNA amplicons. We found no direct correlation between microbial alpha diversity metrics and sleep; however, we identified differences in beta diversity among sleep quality groups (with a PSQI score > 5 indicating poor sleep quality and PSQI ≤5 indicating good sleep quality). We also found differential microbial signatures (Bacteroides, Prevotella 9, and Faecalibacterium) among the groups. Furthermore, functional metabolic pathway profiles revealed significant linear correlations of the L-arginine and L-tryptophan biosynthetic pathways as well as 4-aminobutanoate degradation with sleep status. In particular, Faecalibacterium prausnitzii, which harbors these metabolic pathways, showed differences between sleep quality groups and a linear association with sleep quality scores and was thus identified as the species most strongly associated with sleep status. This study provides a significant advance in our understanding of the relationship between gut microbiota and sleep regulation. The current findings provide a basis for further research into potential therapeutic strategies for sleep disorders targeting the gut microbiome.

No genetic association between sleep traits and periodontitis: A bidirectional two-sample Mendelian randomization study

OBJECTIVE

This study aimed to investigate the potential genetic link between sleep traits and periodontitis.

METHODS

A two-sample bidirectional Mendelian randomization (MR) analysis was conducted using publicly available genome-wide association studies data on chronotype, daytime sleepiness, daytime napping frequency, insomnia, sleep duration, snoring, and the apnea-hypopnea index (AHI), along with a separate dataset on periodontitis.

RESULTS

Chronotype (OR = 0.929, 95% CI = 0.788-1.095), daytime sleepiness (OR = 0.492, 95% CI = 0.186-1.306), daytime napping frequency (OR = 1.178, 95% CI = 0.745-1.863), sleep duration (OR = 0.868, 95% CI = 0.644-1.169), AHI (OR = 1.124, 95% CI = 0.980-1.289), insomnia (OR = 0.832, 95% CI = 0.440-1.573), and snoring (OR = 0.641, 95% CI = 0.198-2.075) had no effect on periodontitis. Similarly, periodontitis demonstrated no significant effect on sleep traits.

CONCLUSIONS

There is no evidence of a bidirectional genetic relationship between sleep traits and the risk of periodontitis.

Sex-specific associations between habitual snoring and cancer prevalence: insights from a US Cohort Study

Study Objectives

To investigate the sex-specific association between habitual snoring and overall cancer prevalence and subtypes, and to examine the influence of age, body mass index (BMI), and sleep duration on this association.

Methods

This study utilized data from the National Health and Nutrition Examination Survey cycles between 2005 and 2020 and included 15 892 participants aged 18 and over. We employed inverse probability of treatment weighting based on propensity scores to adjust for confounders when comparing the prevalence of cancer between habitual snorers and non-habitual snorers for each sex and cancer type. Subgroup analyses were conducted based on sleep duration, age, and BMI categories.

Results

The cohort (mean age 48.2 years, 50.4% female, and 30.5% habitual snorers) reported 1385 cancer cases. In men, habitual snoring was linked to 26% lower odds of any cancer (OR 0.74, 95% CI: 0.66 to 0.83), while in women, it showed no significant difference except lower odds of breast cancer (OR 0.77, 95% CI: 0.63 to 0.94) and higher odds of cervix cancer (OR 1.54, 95% CI: 1.18 to 2.01). Age and sleep duration significantly influenced the snoring-cancer relationship, with notable variations by cancer type and sex.

Conclusions

Habitual snoring exhibits sex-specific associations with cancer prevalence, showing lower prevalence in men and varied results in women. These findings emphasize the critical need for further research to uncover the biological mechanisms involved. Future investigations should consider integrating sleep characteristics with cancer prevention and screening strategies, focusing on longitudinal research and the integration of genetic and biomarker analyses to fully understand these complex relationships.

The causal relationship between sleep and risk of psychiatric disorders: A two-sample mendelian randomization study

Introduction

Sleep is associated with psychiatric disorders. However, their causality remains unknown.

Methods

The study explored the causal relationship between seven sleep parameters (sleep duration, insomnia, sleep apnea, chronotype, daytime dozing, napping during the day, and snoring) and three psychiatric disorders including major depressive disorder (MDD), schizophrenia, and attention-deficit/hyperactivity disorder (ADHD) using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for sleep parameters were obtained from the United Kingdom biobank, FinnGen biobank, and EBI databases. MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW(fixed effects) were used to perform the MR analysis. The heterogeneity was detected by Cochran's Q statistic. The horizontal pleiotropy was detected by MR Egger. The sensitivity was investigated by the leave-one-out analysis.

Results

Insomnia (OR = 2.02, 95%CI = 1.34-3.03, p = 0.001, False-discovery rate (FDR) corrected p-value = 0.011) and napping during the day (OR = 1.81, 95%CI = 1.34-2.44, FDR corrected p-value<0.001) were associated with an increased risk of MDD. Longer sleep duration (OR = 2.20, 95%CI = 1.24-3.90, FDR corrected p-value = 0.049) had an association with the increased risk of schizophrenia, while daytime dozing (OR = 4.44, 95%CI = 1.20-16.41, corrected p-value = 0.088)and napping during the day (OR = 2.11, 95%CI = 1.11-4.02, FDR corrected p-value = 0.088) had a suggestive association with an increased risk of schizophrenia. Longer sleep duration had a suggestive association with a decreased risk of ADHD (OR = 0.66, 95%CI = 0.42-0.93, FDR corrected p-value = 0.088).

Conclusion

This study provides further evidence for a complex relationship between sleep and psychiatric disorders. Our findings highlight the potential benefits of addressing sleep problems in the prevention of psychiatric disorders.

Causal relationship between sleep traits and erectile dysfunction: evidence from Mendelian randomization analysis

Introduction

Although several observational studies have explored the association between sleep traits and the risk of erectile dysfunction (ED), it remains controversial. In the present study, we included a wide range of sleep traits that are commonly observed in clinical practice. We investigated the causal relationship between these sleep traits and ED using univariate and multivariate Mendelian randomization (MR) methods.

Material and methods

Instrumental variables (IVs) for eight sleep traits (insomnia, sleep duration, chronotype, and sleep apnea syndrome), five confounders (depression, body mass index, smoking initiation, alcohol consumption, and type 2 diabetes), and ED were derived from genome-wide association study (GWAS) data of individuals of European ancestry. The primary analysis technique used was the inverse-variance weighted (IVW) approach. Furthermore, several sensitivity analyses were conducted to evaluate heterogeneity, horizontal pleiotropy, and stability.

Results

MR analysis revealed that increased snoring, short sleep, and frequent insomnia were associated with a higher risk of ED. Furthermore, we found evidence of a significant association between being a morning person and the risk of developing ED. This association persisted in multivariable MR analyses after adjusting for potential confounding factors. Sensitivity analysis suggested that the results were robust with no evidence of pleiotropy or heterogeneity.

Conclusions

This study provides further evidence supporting the association between genetically predicted snoring, insomnia, and an increased risk of ED. Additionally, the study highlights the causal relationship of short sleep duration and chronotype with ED.

Shared genetic aetiology of respiratory diseases: a genome-wide multitraits association analysis

OBJECTIVE

This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms.

METHODS

This genome-wide pleiotropic association study uses multiple statistical methods to systematically analyse the shared genetic basis between five respiratory diseases (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, lung cancer and snoring) using the largest publicly available genome wide association studies summary statistics. The missions of this study are to evaluate global and local genetic correlations, to identify pleiotropic loci, to elucidate biological pathways at the multiomics level and to explore causal relationships between respiratory diseases. Data were collected from 27 November 2022 to 30 March 2023 and analysed from 14 April 2023 to 13 July 2023.

MAIN OUTCOMES AND MEASURES

The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects.

RESULTS

Significant genetic correlations were found for 10 paired traits in 5 respiratory diseases. Cross-Phenotype Association identified 12 400 significant potential pleiotropic single-nucleotide polymorphism at 156 independent pleiotropic loci. In addition, multitrait colocalisation analysis identified 15 colocalised loci and a subset of colocalised traits. Gene-based analyses identified 432 potential pleiotropic genes and were further validated at the transcriptome and protein levels. Both pathway enrichment and single-cell enrichment analyses supported the role of the immune system in respiratory diseases. Additionally, five pairs of respiratory diseases have a causal relationship.

CONCLUSIONS AND RELEVANCE

This study reveals the common genetic basis and pleiotropic genes among respiratory diseases. It provides strong evidence for further therapeutic strategies and risk prediction for the phenomenon of respiratory disease comorbidity.

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.

Snoring is associated with hypertension and diabetes mellitus among adults in north Sudan: a cross-sectional study

BACKGROUND

Different levels of association between snoring, hypertension, and diabetes mellitus (DM) are reported. There are few published studies on this topic in African countries, and no investigation was conducted in Sudan. This study aimed to assess the prevalence and factors associated with snoring and the association between snoring, hypertension, and type 2 DM (T2DM) in northern Sudan.

METHODS

A community-based cross-sectional study using a multistage sampling technique was conducted in four villages in the River Nile state of northern Sudan from July to September 2021. Sociodemographic characteristics were collected using a questionnaire. Body mass index (BMI) was measured using standard methods, and a multivariate analysis was conducted using the Statistical Package for the Social Sciences® (SPSS®) for Windows, version 22.0.

RESULTS

Of the 384 adults, 193 (50.3%) were males and 191 (49.7%) were females. Of the adults, 38 (9.9%) were underweight, 121 (31.5%) had average weight, 113 (29.4%) were overweight, and 112 (29.2%) were obese. One hundred and six (27.6%) adults were snorers. Multivariate analysis showed that increasing age (adjusted odds ratio [AOR] = 1.02, 95% confidence interval [CI] = 1.01‒1.04), increasing BMI (AOR = 1.04, 95 CI = 1.01‒1.08), obesity (AOR = 2.0, 95% CI = 1.10‒3.69), and alcohol consumption (AOR = 2.32, 95% CI = 1.14‒4.74) were positively associated with snoring. Of the 384 adults, 215 (56.0%) had hypertension. Multivariate analysis showed that increasing age (AOR = 1.04, 95% CI = 1.02‒1.06), increasing BMI (AOR = 1.08, 95% CI = 1.04‒1.13), female sex (AOR = 1.7, 95% CI = 1.08‒2.73), and snoring (AOR = 1.69, 95% CI = 1.02‒2.82) were positively associated with hypertension. One hundred and six (27.6%) adults had T2DM. Multivariate analysis showed that increasing age (AOR = 1.03, 95% CI = 1.01‒1.05) and snoring (AOR = 1.78, 95% CI = 1.09‒2.91) were associated with T2DM.

CONCLUSION

Around one-fourth of the adults in Northern Sudan are snorers. Snoring is more common among obese adults. Snoring is associated with increased odds of hypertension and T2DM. Adults who snore must pay close attention to their blood pressure and blood glucose levels to prevent hypertension and DM.

Associations between sleep-behavioral traits and healthspan: A one-sample Mendelian randomization study based on 388,909 participants of the UK-Biobank

BACKGROUND

Although the association between sleep behavior and morbidity and mortality risk has been reported before, there is still uncertainty whether the observed associations are causal or confounding. Therefore, we investigated the causal relationships between sleep-behavioral traits and terminated healthspan risk using Mendelian randomization (MR).

METHODS

We conducted a one-sample MR analysis to evaluate causality between six sleep-behavioral traits (sleep duration, chronotype/morningness, napping, sleeplessness/insomnia, and getting up from bed) and risk of healthspan termination among 388, 909 UK Biobank (UKB) participants. Instrumental variables for sleep behaviors (N = 590) were obtained from recent genome-wide association studies (GWAS). We defined healthspan based on eight predominant health-terminating events associated with longevity (congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, diabetes, cancer, and death). We further constructed a sleep score and a weighted genetic risk score to increase the predictive ability of the sleep-behavioral traits. Cox regression models and Inverse Probability Treatment Weighting (IPTW) were implemented, followed by MR to assess causation. We used inverse-variance-weighted MR to estimate causal effects, and weighted-median and MR-egger for sensitivity analysis to test the pleiotropic effects.

RESULTS

In IPTW, we observed a decreased risk of terminated healthspan for healthy sleep behaviors such as 'sleep duration 7-8h/d' (Hazard ratio, HR = 0.93; 95 % confidence interval, CI: 0.92-0.96; P < 0.001); 'morningness' (HR = 0.95; 95%CI: 0.93-0.98; P < 0.01); 'napping' (HR = 0.93; 95%CI: 0.91-0.94; P < 0.001); 'easy getting up from bed' (HR = 0.91; 95%CI: 0.88-0.93; P < 0.001); and, 'never/rarely experience sleeplessness/insomnia' (HR = 0.94; 95%CI: 0.92-0.96; P < 0.001). MR results further indicated causal associations between healthy sleep duration (OR = 0.98; 95%CI: 0.97-1.00; P = 0.036) and insomnia (OR = 1.02; 95%CI: 1.01-1.03; P < 0.001) with terminated healthspan. MR-egger did not suggest any potential pleiotropy.

CONCLUSION

This study supports abnormal sleep duration and insomnia as potential causal risk factors for terminated healthspan. Thus, healthy sleep behavior is valuable for the extension of healthspan, and well-designed and tailored sleep health interventions are warranted.

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.

Association between sleep traits and biological aging risk: a Mendelian randomization study based on 157 227 cases and 179 332 controls

STUDY OBJECTIVES

To investigate whether sleep traits are associated with the risk of biological aging using a case-control design with Mendelian randomization (MR) analyses.

METHODS

We studied 336 559 participants in the UK Biobank cohort, including 157 227 cases of accelerated biological aging and 179 332 controls. PhenoAge, derived from clinical traits, estimated biological ages, and the discrepancies from chronological age were defined as age accelerations (PhenoAgeAccel). Sleep behaviors were assessed with a standardized questionnaire. propensity score matching matched control participants to age-accelerated participants, and a conditional multivariable logistic regression model estimated odds ratio (OR) and 95% confidence intervals (95% CI). Causal relationships between sleep traits and PhenoAgeAccel were explored using linear and nonlinear MR methods.

RESULTS

A U-shaped association was found between sleep duration and PhenoAgeAccel risk. Short sleepers had a 7% higher risk (OR = 1.07; 95% CI: 1.03 to 1.11), while long sleepers had an 18% higher risk (OR = 1.18; 95% CI: 1.15 to 1.22), compared to normal sleepers (6-8 hours/day). Evening chronotype was linked to higher PhenoAgeAccel risk than morning chronotype (OR = 1.14; 95% CI: 1.10 to 1.18), while no significant associations were found for insomnia or snoring. Morning chronotype had a protective effect on PhenoAgeAccel risk (OR = 0.87, 95% CI: 0.79 to 0.95) per linear MR analysis. Genetically predicted sleep duration showed a U-shaped relationship with PhenoAgeAccel, suggesting a nonlinear association (pnonlinear < 0.001).

CONCLUSIONS

The study suggests that improving sleep can slow biological aging, highlighting the importance of optimizing sleep as an intervention to mitigate aging's adverse effects.

A genome-wide association study based on the China Kadoorie Biobank identifies genetic associations between snoring and cardiometabolic traits

Despite the high prevalence of snoring in Asia, little is known about the genetic etiology of snoring and its causal relationships with cardiometabolic traits. Based on 100,626 Chinese individuals, a genome-wide association study on snoring was conducted. Four novel loci were identified for snoring traits mapped on SLC25A21, the intergenic region of WDR11 and FGFR, NAA25, ALDH2, and VTI1A, respectively. The novel loci highlighted the roles of structural abnormality of the upper airway and craniofacial region and dysfunction of metabolic and transport systems in the development of snoring. In the two-sample bi-directional Mendelian randomization analysis, higher body mass index, weight, and elevated blood pressure were causal for snoring, and a reverse causal effect was observed between snoring and diastolic blood pressure. Altogether, our results revealed the possible etiology of snoring in China and indicated that managing cardiometabolic health was essential to snoring prevention, and hypertension should be considered among snorers.

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 snoring and stroke: a Mendelian randomization study in a Chinese population

Background

Previous observational studies established a positive relationship between snoring and stroke. We aimed to investigate the causal effect of snoring on stroke.

Methods

Based on 82,339 unrelated individuals with qualified genotyping data of Asian descent from the China Kadoorie Biobank (CKB), we conducted a Mendelian randomization (MR) analysis of snoring and stroke. Genetic variants identified in the genome-wide association analysis (GWAS) of snoring in CKB and UK Biobank (UKB) were selected for constructing genetic risk scores (GRS). A two-stage method was applied to estimate the associations of the genetically predicted snoring with stroke and its subtypes. Besides, MR analysis among the non-obese group (body mass index, BMI <24.0 kg/m2), as well as multivariable MR (MVMR), were performed to control for potential pleiotropy from BMI. In addition, the inverse-variance weighted (IVW) method was applied to estimate the causal association with genetic variants identified in CKB GWAS.

Findings

Positive associations were found between snoring and total stroke, hemorrhagic stroke (HS), and ischemic stroke (IS). With GRS of CKB, the corresponding HRs (95% CIs) were 1.56 (1.15, 2.12), 1.50 (0.84, 2.69), 2.02 (1.36, 3.01), and the corresponding HRs (95% CIs) using GRS of UKB were 1.78 (1.30, 2.43), 1.94 (1.07, 3.52), and 1.74 (1.16, 2.61). The associations remained stable in the MR among the non-obese group, MVMR analysis, and MR analysis using the IVW method.

Interpretation

This study suggests that, among Chinese adults, genetically predicted snoring could increase the risk of total stroke, IS, and HS, and the causal effect was independent of BMI.

Funding

National Natural Science Foundation of China, Kadoorie Charitable Foundation Hong Kong, UK Wellcome Trust, National Key R&D Program of China, Chinese Ministry of Science and Technology.

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.

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.

Association between sleep-related phenotypes and gut microbiota: a two-sample bidirectional Mendelian randomization study

Background

An increasing body of evidence suggests a profound interrelation between the microbiome and sleep-related concerns. Nevertheless, current observational studies can merely establish their correlation, leaving causality unexplored.

Study objectives

To ascertain whether specific gut microbiota are causally linked to seven sleep-related characteristics and propose potential strategies for insomnia prevention.

Methods

The study employed an extensive dataset of gut microbiota genetic variations from the MiBioGen alliance, encompassing 18,340 individuals. Taxonomic classification was conducted, identifying 131 genera and 196 bacterial taxa for analysis. Sleep-related phenotype (SRP) data were sourced from the IEU OpenGWAS project, covering traits such as insomnia, chronotype, and snoring. Instrumental variables (IVs) were selected based on specific criteria, including locus-wide significance, linkage disequilibrium calculations, and allele frequency thresholds. Statistical methods were employed to explore causal relationships, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted Mode. Sensitivity analyses, pleiotropy assessments, and Bonferroni corrections ensured result validity. Reverse causality analysis and adherence to STROBE-MR guidelines were conducted to bolster the study's rigor.

Results

Bidirectional Mendelian randomization (MR) analysis reveals a causative interplay between selected gut microbiota and sleep-related phenotypes. Notably, outcomes from the rigorously Bonferroni-corrected examination illuminate profound correlations amid precise compositions of the intestinal microbiome and slumber-associated parameters. Elevated abundance within the taxonomic ranks of class Negativicutes and order Selenomonadales was markedly associated with heightened susceptibility to severe insomnia (OR = 1.03, 95% CI: 1.02-1.05, p = 0.0001). Conversely, the augmented representation of the phylum Lentisphaerae stands in concord with protracted sleep duration (OR = 1.02, 95% CI: 1.01-1.04, p = 0.0005). Furthermore, heightened exposure to the genus Senegalimassilia exhibits the potential to ameliorate the manifestation of snoring symptoms (OR = 0.98, 95% CI: 0.96-0.99, p = 0.0001).

Conclusion

This study has unveiled the causal relationship between gut microbiota and SRPs, bestowing significant latent value upon future endeavors in both foundational research and clinical therapy.

Relationship of serum 25-hydroxyvitamin D, obesity with new-onset obstructive sleep apnea

OBJECTIVE

The prospective association between vitamin D and obstructive sleep apnea (OSA) remains uncertain. We aimed to assess the association between serum 25-hydroxyvitamin D (25(OH)D), a major circulating form of vitamin D, and new-onset OSA, and examine the modifying effect of obesity.

MATERIALS AND METHODS

This prospective cohort study included 444,975 participants from UK Biobank without prior OSA. The primary outcome was new-onset OSA.

RESULTS

During a median follow-up duration of 12.0 years, 6051 (1.4%) participants occurred new-onset OSA. Overall, there was an inverse relation of serum 25(OH)D concentrations with the risk of new-onset OSA (per SD increment, HR, 0.92; 95%CI: 0.89-0.95). In the analysis of the interactions of serum 25(OH)D with the combination of BMI (<25, 25- < 30, and ≥30 kg/m2) and waist circumference (WC) (<90 and ≥90 cm) categories on new-onset OSA, the significantly inverse association of serum 25(OH)D and new-onset OSA was mainly found in participants with both BMI ≥ 25 kg/m2 and WC ≥ 90 cm (BMI 25-30 kg/m2 and WC ≥ 90 cm: per SD increment, HR, 0.90; 95%CI: 0.84-0.95; BMI ≥ 30 kg/m2 and WC ≥ 90 cm: per SD increment, HR, 0.85; 95%CI: 0.81-0.88), but not in other four groups with BMI < 25 kg/m2 or WC < 90 cm (P -interaction = 0.004).

CONCLUSIONS

There was an inverse relation of serum 25(OH)D with the risk of new-onset OSA in participants with both BMI ≥ 25 kg/m2 and WC ≥ 90 cm. Our findings suggest the importance of maintaining a higher serum 25(OH)D concentration for primary prevention of OSA in a population with obesity.

Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank

BACKGROUND

To explore the relationship between sleep patterns and cardiovascular disease (CVD) incidence and mortality risk in a population with type 2 diabetes through a UK Biobank sample.

METHODS

A total of 6860 patients with type 2 diabetes were included in this study. Five sleep factors (including Chronotype, sleep duration, insomnia, daytime sleepiness, and snoring) were collected as a questionnaire. The calculation generates a sleep score of 0-5, and then three sleep patterns were defined based on the sleep scores: poor sleep pattern (0-2), Intermediate sleep pattern (3-4), and healthy sleep pattern (5). HRs and 95% confidence intervals were calculated by multivariate COX proportional risk model adjustment. Restricted cubic splines were used to validate linear associations between sleep scores CVD events.

RESULTS

Our results found a reduced risk of CVD events in individuals with healthy sleep patterns compared to participants with poor sleep patterns. CVD Mortality (HR, 0.690; 95% CI 0.519-0.916), ASCVD (Atherosclerosis CVD) (HR, 0.784; 95% CI 0.671-0.915), CAD (Coronary Artery Disease) (HR, 0.737; 95% CI 0.618-0.879), PAD (Peripheral Arterial Disease) (HR, 0.612; 95% CI 0.418-0.896), Heart Failure (HR, 0.653; 95% CI 0.488-0.875). Restricted cubic spline responded to a negative linear correlation between sleep scores and CVD Mortality, ASCVD, CAD, PAD, and Heart Failure.

CONCLUSIONS

Healthy sleep patterns are significantly associated with a reduced risk of CVD Mortality, ASCVD, CAD, PAD, and Heart Failure in the diabetes population.

Usual dietary intake and change in DNA methylation over years: EWAS in KORA FF4 and KORA fit

Introduction

Changes in DNA methylation can increase or suppress the expression of health-relevant genes. We investigated for the first time the relationship between habitual food consumption and changes in DNA methylation.

Methods

The German KORA FF4 and KORA Fit studies were used to study the change in methylation over a median follow-up of 4 years. Only subjects participating in both surveys and with available dietary and methylation data were included in the analysis (n = 465). DNA methylation was measured using the Infinium MethylationEPIC BeadChip (Illumina), resulting in 735,527 shared CpGs across both studies. Generalized estimating equation models with an interaction term of exposure and time point were used to analyze the association of 34 food groups, folic acid, and two dietary patterns with changes in DNA methylation over time.

Results

The results were corrected for genomic inflation. Significant interaction terms indicate different effects between both time points. We observed only a few significant associations between food intake and change in DNA methylation, except for cream and spirit consumption. The annotated genes include CLN3, PROM1, DLEU7, TLL2, and UGT1A10.

Discussion

We identified weak associations between food consumption and DNA methylation change. The differential results for cream and spirits, both consumed in low quantities, require replication in independent studies.

Airways Type-2 Related Disorders: Multiorgan, Systemic or Syndemic Disease?

Chronic rhinosinusitis (CRS) has recently undergone a significant paradigm shift, moving from a phenotypical classification towards an "endotype-based" definition that places more emphasis on clinical and therapeutic aspects. Similar to other airway diseases, like asthma, most cases of CRS in developed countries exhibit a dysregulated type-2 immune response and related cytokines. Consequently, the traditional distinction between upper and lower airways has been replaced by a "united airway" perspective. Additionally, type-2 related disorders extend beyond respiratory boundaries, encompassing conditions beyond the airways, such as atopic dermatitis. This necessitates a multidisciplinary approach. Moreover, consideration of possible systemic implications is crucial, particularly in relation to sleep-related breathing diseases like Obstructive Sleep Apnoea Syndrome (OSAS) and the alteration of systemic inflammatory mediators such as nitric oxide. The trends in epidemiological, economic, and social burden are progressively increasing worldwide, indicating syndemic characteristics. In light of these insights, this narrative review aims to present the latest evidence on respiratory type-2 related disorders, with a specific focus on CRS while promoting a comprehensive perspective on the "united airways". It also introduces a novel concept: viewing these conditions as a multiorgan, systemic, and syndemic disease.

Screening for Obstructive Sleep Apnea and Associated Risk Factors in Adolescents and Adults With Isolated Robin Sequence

OBJECTIVE

To investigate the subjective risk for obstructive sleep apnea (OSA) in adolescents and young adults with isolated Robin sequence (IRS). Additionally, to investigate the association of OSA risk with respiratory signs/symptoms, and retrognathia.

DESIGN

Prospective, observational, and cross-sectional study.

SETTING

Tertiary reference hospital for the rehabilitation of craniofacial anomalies.

PARTICIPANTS

Adolescents and adults (n = 30) with IRS were clinically evaluated and screened through the Berlin Questionnaire (BQ) and Respiratory Symptoms Questionnaire. The maxillomandibular relationship was assessed on lateral cephalograms of those that reached skeletal maturity (n = 13). Polysomnography (PSG) was performed in a subgroup of 4 individuals.

RESULTS

The mean age of the sample was 18.2 (±3.4) years, 17 (56.7%) were adolescents (14-19 years), and 16 were (53.3%) female, all presented a repaired cleft palate.

CLINICAL PARAMETERS

Systemic arterial pressure (118.0 ± 4.1/76.3 ± 4.9 mmHg), body mass index (BMI) (20.9 ± 2.8 kg/m2), neck (33.2 ± 2.3 cm), and waist circumferences (72.0 ± 5.8 cm) were within normal ranges. A skeletal class I pattern was observed in 61.5% of the participants while a class II was seen in 15.4% of them. A high risk for OSA was detected in 16.7%, and it was associated with nasal obstruction, snoring and drowsiness, and a skeletal class II pattern (P ≤ .05). One patient presented with mild OSA (apnea-hypopnea index [AHI] = 10.1 events/hour) at the PSG exam.

CONCLUSIONS

A high risk for OSA can be observed with a moderate frequency among adolescents and young adults with IRS, especially among those who are concurrently suffering from nasal obstruction, snoring and retrognathia.

Identification of novel biomarkers in obstructive sleep apnea via integrated bioinformatics analysis and experimental validation

Background

Obstructive sleep apnea (OSA) is a complex and multi-gene inherited disease caused by both genetic and environmental factors. However, due to the high cost of diagnosis and complex operation, its clinical application is limited. This study aims to explore potential target genes associated with OSA and establish a corresponding diagnostic model.

Methods

This study used microarray datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) related to OSA and perform functional annotation and pathway analysis. The study employed multi-scale embedded gene co-expression network analysis (MEGENA) combined with least absolute shrinkage and selection operator (LASSO) regression analysis to select hub genes and construct a diagnostic model for OSA. In addition, the study conducted correlation analysis between hub genes and OSA-related genes, immunoinfiltration, gene set enrichment analysis (GSEA), miRNA network analysis, and identified potential transcription factors (TFs) and targeted drugs for hub genes. Finally, the study used chronic intermittent hypoxia (CIH) mouse model to simulate OSA hypoxic conditions and verify the expression of hub genes in CIH mice.

Results

In this study, a total of 401 upregulated genes and 275 downregulated genes were identified, and enrichment analysis revealed that these differentially expressed genes may be associated with pathways such as vasculature development, cellular response to cytokine stimulus, and negative regulation of cell population proliferation. Through MEGENA combined with LASSO regression, seven OSA hub genes were identified, including C12orf54, FOS, GPR1, OR9A4, MYO5B, RAB39B, and KLHL4. The diagnostic model constructed based on these genes showed strong stability. The expression levels of hub genes were significantly correlated with the expression levels of OSA-related genes and mainly acted on pathways such as the JAK/STAT signaling pathway and the cytosolic DNA-sensing pathway. Drug-target predictions for hub genes were made using the Connectivity Map (CMap) database and the Drug-Gene Interaction database (Dgidb), which identified targeted therapeutic drugs for the hub genes. In vivo experiments showed that the hub genes were all decreasing in the OSA mouse model.

Conclusions

This study identified novel biomarkers for OSA and established a reliable diagnostic model. The transcriptional changes identified may help to reveal the pathogenesis, mechanisms, and sequelae of OSA.

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.

Correlations in sleeping patterns and circadian preference between spouses

Spouses may affect each other's sleeping behaviour. In 47,420 spouse-pairs from the UK Biobank, we found a weak positive phenotypic correlation between spouses for self-reported sleep duration (r = 0.11; 95% CI = 0.10, 0.12) and a weak inverse correlation for chronotype (diurnal preference) (r = -0.11; -0.12, -0.10), which replicated in up to 127,035 23andMe spouse-pairs. Using accelerometer data on 3454 UK Biobank spouse-pairs, the correlation for derived sleep duration was similar to self-report (r = 0.12; 0.09, 0.15). Timing of diurnal activity was positively correlated (r = 0.24; 0.21, 0.27) in contrast to the inverse correlation for chronotype. In Mendelian randomization analysis, positive effects of sleep duration (mean difference=0.13; 0.04, 0.23 SD per SD) and diurnal activity (0.49; 0.03, 0.94) were observed, as were inverse effects of chronotype (-0.15; -0.26, -0.04) and snoring (-0.15; -0.27, -0.04). Findings support the notion that an individual's sleep may impact that of their partner, promoting opportunities for sleep interventions at the family-level.

Snoring and risk of dementia: a prospective cohort and Mendelian randomization study

Background

The association between snoring, a very common condition that increases with age, and dementia risk is controversial. Snoring is linked to obstructive sleep apnoea and cardiometabolic conditions, both of which are associated with an increased risk of dementia. However, snoring also increases with body mass index (BMI), which in late life is linked to lower dementia risk, possibly due to metabolic changes during prodromal dementia.

Methods

The prospective cohort study used data from 450,027 UK Biobank participants with snoring measured at baseline (2006 - 2010), and followed up for dementia diagnosis (censored at 2022). Two-sample Mendelian randomization (MR) analysis used summary statistics for genome-wide association studies of Alzheimer's disease (AD) (n = 94,437; cases = 35,274) and snoring (n = 408,317; snorers = 151,011).

Results

During a median follow-up of 13.5 years, 7,937 individuals developed dementia. Snoring was associated with an 8% lower risk of all-cause dementia (hazard ratio [HR] 0.92; 95% confidence interval [CI] 0.88 to 0.97) and AD (HR 0.92; 95% CI 0.86 to 0.99). The association was stronger in older individuals, APOE ε4 allele carriers, and during shorter follow-up periods. MR analyses suggested no causal effect of snoring on AD, however, genetic liability to AD was associated with a lower risk of snoring. Multivariable MR indicated that the effect of AD on snoring was primarily driven by BMI.

Conclusions

The phenotypic association between snoring and lower dementia risk likely stems from reverse causation, with genetic predisposition to AD associated with reduced snoring. This may be driven by weight loss in prodromal AD.

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.

Snoring-related polygenic risk and its relationship with lifestyle factors in a Korean population: KoGES study

Whereas lifestyle-related factors are recognized as snoring risk factors, the role of genetics in snoring remains uncertain. One way to measure the impact of genetic risk is through the use of a polygenic risk score (PRS). In this study, we aimed to investigate whether genetics plays a role in snoring after adjusting for lifestyle factors. Since the effect of polygenic risks may differ across ethnic groups, we calculated the PRS for snoring from the UK Biobank and applied it to a Korean cohort. We sought to evaluate the reproducibility of the UK Biobank PRS for snoring in the Korean cohort and to investigate the interaction of lifestyle factors and genetic risk on snoring in the Korean population. In this study, we utilized a Korean cohort obtained from the Korean Genome Epidemiology Study (KoGES). We computed the snoring PRS for the Korean cohort based on the UK Biobank PRS. We investigated the relationship between polygenic risks and snoring while controlling for lifestyle factors, including sex, age, body mass index (BMI), alcohol consumption, smoking, physical activity, and sleep time. Additionally, we analyzed the interaction of each lifestyle factor and the genetic odds of snoring. We included 3526 snorers and 1939 nonsnorers from the KoGES cohort and found that the PRS, a polygenic risk factor, was an independent factor for snoring after adjusting for lifestyle factors. In addition, among lifestyle factors, higher BMI, male sex, and older age were the strongest lifestyle factors for snoring. In addition, the highest adjusted odds ratio for snoring was higher BMI (OR 1.98, 95% CI 1.76-2.23), followed by male sex (OR 1.54, 95% CI 1.28-1.86), older age (OR 1.23, 95% CI 1.03-1.35), polygenic risks such as higher PRS (OR 1.18, 95% CI 1.08-1.29), drinking behavior (OR 1.18, 95% CI 1.03-1.35), late sleep mid-time (OR 1.17, 95% CI 1.02-1.33), smoking behavior (OR 0.99, 95% CI 0.82-1.19), and lower physical activity (OR 0.92, 95% CI 0.85-1.00). Our study identified that the UK Biobank PRS for snoring was reproducible in the Korean cohort and that genetic risk served as an independent risk factor for snoring in the Korean population. These findings may help to develop personalized approaches to reduce snoring in individuals with high genetic risk.

Positive correlation between snoring and dyslipidemia in adults: results from NHANES

BACKGROUND

A few studies have shown that snoring, in certain populations, is associated with dyslipidemia. However, there are currently no large-scale national studies available that explore this association. Thus, for further clarification, studies using a large sample of the general population need to be conducted. This study aimed to explore this association using the National Health and Nutrition Examination Survey (NHANES) database.

METHODS

A cross-sectional survey was conducted using data from the NHANES database; 2005 to 2008 and 2015 to 2018 datasets were used (weighted to be representative of United States adults aged ≥ 20 years). Information on snoring status, lipid levels, and confounding factors were included. Logistic regression of the generalized linear model was used to analyze the relationship between snoring and dyslipidemia, and hierarchical analysis, interaction analysis, and sensitivity analysis were used to explore the stability of the results.

RESULTS

Data from 28,687 participants were analyzed, and 67% of the participants had some degree of snoring. The fully adjusted multivariate logistic regression results demonstrated that snoring frequency was significantly positively associated with dyslipidemia (P < 0.001 for linear trend). Adjusted odds ratios (aORs) of dyslipidemia among those who snored rarely, occasionally, and frequently were 1.1 (95% confidence interval [CI], 1.02-1.18), 1.23 (95% CI, 1.10-1.38), and 1.43 (95% CI, 1.29-1.58), respectively, compared with that among those who never snored. In addition, age and snoring frequency showed a correlation (P = 0.02). Sensitivity analysis demonstrated that frequent snoring was significantly associated with lipid levels (all P ≤ 0.01 for linear trend), including increased low-density lipoprotein cholesterol (LDL-C) (β = 0.09 mmol/L; 95% CI, 0.02-0.16), triglyceride (TG) (β = 0.18 mmol/L; 95% CI, 0.10-0.26), total cholesterol (TC) (β = 0.11 mmol/L; 95% CI, 0.05-0.16), and decreased high-density lipoprotein cholesterol (HDL-C) (β=-0.04 mmol/L; 95% CI, -0.06--0.03).

CONCLUSIONS

A statistically significant positive association was identified between sleep snoring and dyslipidemia. It was suggested that sleep snoring interventions may reduce the risk of dyslipidemia.