Causal association of sleep traits with the risk of thyroid cancer: A mendelian randomization study.

BACKGROUND: This study was to explore the causal associations of sleep traits including sleep duration, snoring, chronotype, sleep disorders, getting up in the morning, sleeplessness/insomnia and nap during day with the risk of thyroid cancer based on Mendelian randomization (MR) analysis. METHOD: Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published genome-wide association studies (GWASs) using the FinnGen and UK Biobank databases. A series of screening processes were performed to select qualified SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the Mendelian Randomization robust adjusted profile score (MR-RAPS), the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and the Weighted Median to estimate the causal links between sleep traits and the risk of thyroid cancer. Odds ratio (OR) and 95% confidence interval (CI) were calculated. RESULTS: The IVW results showed that getting up in the morning (OR = 0.055, 95%CI: 0.004-0.741) and napping during day (OR = 0.031, 95%CI: 0.002-0.462) were associated with decreased risk of thyroid cancer in the Italian population. A 1.30-h decrease of sleep duration was associated with 7.307-fold of thyroid cancer risk in the Finnish population (OR = 7.307, 95%CI: 1.642-32.519). Cronotype could decrease the risk of thyroid cancer in the Finnish population (OR = 0.282, 95%CI: 0.085-0.939). Sleep disorders increased the risk of thyroid cancer in the Finnish population (OR = 2.298, 95%CI: 1.194-4.422). The combined results revealed that sleep duration was correlated with increased risk of thyroid cancer (OR = 5.600, 95%CI: 1.458-21.486). CONCLUSION: Decreased sleep duration was associated with increased risk of thyroid cancer, which indicated the importance of adequate sleep for the prevention of thyroid cancer.

Association of sleep traits with myopia in children and adolescents: A meta-analysis and Mendelian randomization study.

PURPOSE: The association between sleep and myopia in children and adolescents has been reported, yet it remains controversial and inconclusive. This study aimed to investigate the influence of different sleep traits on the risk of myopia using meta-analytical and Mendelian randomization (MR) techniques. METHODS: The literature search was performed in August 31, 2023 based on PubMed, Embase, Web of Science, and Cochrane library. The meta-analysis of observational studies reporting the relationship between sleep and myopia was conducted. MR analyses were carried out to assess the causal impact of genetic pre-disposition for sleep traits on myopia. RESULTS: The results of the meta-analysis indicated a significant association between the risk of myopia and both short sleep duration [odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.08-1.42, P = 0.003] and long sleep duration (OR = 0.75, 95% CI = 0.66-0.86, P < 0.001). MR analyses revealed no significant causal associations of genetically determined sleep traits with myopia, including chronotype, sleep duration, short sleep duration and long sleep duration (all P > 0.05). CONCLUSIONS: No evidence was found to support a causal relationship between sleep traits and myopia. While sleep may not independently predict the risk of myopia, the potential impact of sleep on the occurrence and development of myopia cannot be disregarded.

Potential causal associations between leisure sedentary behaviors, physical activity, sleep traits, and myopia: a Mendelian randomization study.

BACKGROUND: Myopia is the most prevalent refractive error and a growing global health concern that significantly affects visual function. Researchers have recently emphasized considerably on the influence of lifestyle on myopia incidence and development. This study investigates the relationship between leisure sedentary behaviors (LSB)/physical activity (PA)/sleep traits and myopia. METHODS: LSB, PA, and sleep trait-associated genetic variants were used as instrument variables in a Mendelian randomization (MR) study to examine their causal effects on myopia. Summary genome-wide association studies (GWASs) statistical data for LSB and PA were obtained from UK Biobank, and the data of sleep traits was obtained from UK Biobank, UK Biobank and 23andMe, and FinnGen. We used summary statistics data for myopia from MRC IEU. The MR analyses was performed using the inverse variance-weighted (IVW), MR-Egger, weighted median, and MR Pleiotropy RESidual Sum and Outlier methods. RESULTS: Computer use was genetically predicted to increase the myopia risk [IVW odds ratio (OR) = 1.057; 95% confidence interval (CI), 1.038-1.078; P = 7.04 × 10- 9]. The self-reported moderate-to-vigorous physical activity (MVPA) (IVW OR = 0.962; 95% CI, 0.932-0.993; P = 1.57 × 10- 2) and television watching (IVW OR = 0.973; 95% CI, 0.961-0.985, P = 1.93 × 10- 5) were significantly associated with a lower myopia risk. However, genetically predicted sleep traits or accelerometer-measured physical activity had no significant associations with myopia. CONCLUSION: Our results indicated that computer use is a risk factor for myopia, whereas television watching and MVPA may protect against myopia. These findings shed new light on possible strategies for reducing the prevalence of myopia.

Association between sleep traits and primary liver cancer: A Mendelian randomization analysis.

BACKGROUND: Primary liver cancer (PLC) is the sixth most frequently occurring cancer, representing one of the top 5 leading causes of cancer-related mortality worldwide. Recently, researchers have focused more on the impact of living habits on the incidence and development of tumours. This study reports a relationship between sleep traits and PLC. METHODS: In this study, we used published genome-wide association studies to obtain exposure factors of 6 sleep traits. Mendelian randomization (MR) analysis was used to assess the causal relationship between sleep traits and PLC via inverse-variance weighted (IVW), MR Egger and weighted median. Sensitivity analysis was used to reduce the bias. RESULTS: Our investigation revealed that there was a negative correlation between sleep duration and the group of liver and bile duct cancer by IVW (p-value = .042), and this result was similarly observed in the liver cell carcinoma group by Weighted Median (p-value = .026). In contrast, there was a positive correlation found between napping during the day and primary liver cancer in the cohorts of liver and bile duct cancer (p-value = .030), liver cell carcinoma (p-value = .043) and malignant neoplasm of other and unspecified parts of the biliary tract (p-value = .016) by IVW. Furthermore, our study also revealed a positive correlation between insomnia and malignant neoplasm of the liver and intrahepatic bile ducts by IVW (p-value = .022). CONCLUSIONS: Overall, our study indicates that insomnia and nap during the day may be risk factors of PLC and adequate night sleep might keep us away from PLC.

The causal relationship between sleep traits and the risk of schizophrenia: a two-sample bidirectional Mendelian randomization study.

BACKGROUND: Observational studies suggest that sleep disturbances are commonly associated with schizophrenia. However, it is uncertain whether this relationship is causal. To investigate the bidirectional causal relation between sleep traits and schizophrenia, we performed a two-sample bidirectional Mendelian randomization (MR) study with the fixed effects inverse-variance weighted (IVW) method. METHODS: As genetic variants for sleep traits, we selected variants from each meta-analysis of genome-wide association studies (GWASs) conducted using data from the UK Biobank (UKB). RESULTS: We found that morning diurnal preference was associated with a lower risk of schizophrenia, while long sleep duration and daytime napping were associated with a higher risk of schizophrenia. Multivariable MR analysis also showed that sleep duration was associated with a higher risk of schizophrenia after adjusting for other sleep traits. Furthermore, genetically predicted schizophrenia was negatively associated with morning diurnal preference and short sleep duration and was positively associated with daytime napping and long sleep duration. CONCLUSIONS: Therefore, sleep traits were identified as a potential treatment target for patients with schizophrenia.

Influence of DNA-Polymorphisms in Selected Circadian Clock Genes on Clock Gene Expression in Subjects from the General Population and Their Association with Sleep Duration.

Background and Objectives: Circadian rhythms have an important implication in numerous physiological and metabolic processes, including the sleep/wake cycle. Inter-individual differences in factors associated with circadian system may be due to gene differences in gene expression. Although several studies have analyzed the association between DNA polymorphisms and circadian variables, the influence on gene expression has been poorly analyzed. Our goal was to analyze the association of genetic variations in the clock genes and the gene expression level. Materials and Methods: We carried out a cross-sectional study of 102 adults (50.9% women). RNA and DNA were isolated from blood and single-nucleotide polymorphisms (SNPs), and the main circadian clock genes were determined. Gene expression of CLOCK, PER1, and VRK2 genes was measured by Reverse-transcription polymerase chain reaction (RT-PCR). The association between the DNA-SNPs and gene expression was analyzed at the gene level. In addition, a polygenic risk score (PRS), including all the significant SNPs related to gene expression, was created for each gene. Multivariable model analysis was performed. Results: Sex-specific differences were detected in PER1 expression, with these being higher in women (p = 0.034). No significant differences were detected in clock genes expression and lifestyle variables. We observed a significant association between the ARNTL-rs7924734, ARNTL-rs10832027, VRK2- rs2678902 SNPs, and CLOCK gene expression; the PER3-rs228642 and PER3-rs10127838 were related to PER1 expression, and the ARNTL-rs10832027, ARNTL-rs11022778, and MNTR1B-rs10830963 were associated with VRK2 gene expression (p < 0.05). The specific PRS created was significantly associated with each of the gene expressions analyzed (p < 0.001). Finally, sleep duration was associated with PER3-rs238666 (p = 0.008) and CLOCK-rs4580704 (p = 0.023). Conclusion: We detected significant associations between DNA-SNPs in the clock genes and their gene expression level in leukocytes and observed some differences in gene expression per sex. Moreover, we reported for the first time an association between clock gene polymorphisms and CLOCK, PER1, and VRK2 gene expression. These findings need further investigation.

Genetic polymorphisms associated with sleep-related phenotypes; relationships with individual nocturnal symptoms of insomnia in the HUNT study.

BACKGROUND: In recent years, several GWAS (genome wide association studies) of sleep-related traits have identified a number of SNPs (single nucleotides polymorphism) but their relationships with symptoms of insomnia are not known. The aim of this study was to investigate whether SNPs, previously reported in association with sleep-related phenotypes, are associated with individual symptoms of insomnia. METHODS: We selected participants from the HUNT study (Norway) who reported at least one symptom of insomnia consisting of sleep onset, maintenance or early morning awakening difficulties, (cases, N = 2563) compared to participants who presented no symptoms at all (controls, N = 3665). Cases were further divided in seven subgroups according to different combinations of these three symptoms. We used multinomial logistic regressions to test the association among different patterns of symptoms and 59 SNPs identified in past GWAS studies. RESULTS: Although 16 SNPS were significantly associated (p < 0.05) with at least one symptom subgroup, none of the investigated SNPs remained significant after correction for multiple testing using the false discovery rate (FDR) method. CONCLUSIONS: SNPs associated with sleep-related traits do not replicate on any pattern of insomnia symptoms after multiple tests correction. However, correction in this case may be overly conservative.

Associations Between Sleep Traits and Social Isolation: Observational and Bidirectional Mendelian Randomization Study.

Social isolation has been found associated with multiple sleep traits in conventional observational studies. However, whether this association is causal and if so, its direction is uncertain. We analyzed the association between social isolation and multiple sleep traits in 30 430 participants from the Guangzhou Biobank Cohort Study. In bidirectional Mendelian randomization, we used 6, 17, and 11 single nucleotide polymorphisms associated with attendance at sports club/gym, religious group, and pub/social club from the UK Biobank (n = 452 302), respectively, and 152 single nucleotide polymorphisms associated with insomnia from the combination of UK Biobank and 23andme (n = 1 331 010). Observationally in the Guangzhou Biobank Cohort Study, insomnia (yes/no) (beta = 0.12, 95% confidence interval (CI) 0.10-0.16) and poor sleep quality (yes/no) (beta = 0.12, CI: 0.08-0.15), but not sleep duration and chronotype, were associated with a higher social isolation score (severe social isolation). In bidirectional MR, genetically predicted insomnia decreases the odds of attendance at sports club/gym (beta = 0.98, CI: 0.98-0.99) and religious groups (beta = 0.99, CI: 0.98-0.99), but not pub/social club. However, these 3 types of social activity were not associated with insomnia. Our results support the causal effects of insomnia on social activity. Further clinical investigations into the utility of insomnia treatment in alleviating social isolation are needed.

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.

Causality between sleep traits and the risk of frailty: a Mendelian randomization study.

Background: Research based on observation has demonstrated a relationship between sleep traits and frailty; however, it remains uncertain if this correlation indicates causation. The purpose of this study was to look at the causal relationship that exists between frailty and sleep traits. Method: Using summaries from a genome-wide association study of self-reported sleep features and frailty index, we performed a bidirectional Mendelian randomization (MR) analysis. Examining the causal relationships between seven sleep-related traits and frailty was the goal. The major method used to calculate effect estimates was the inverse-variance weighted method, supplemented by the weighted median and MR-Egger approaches. The study investigated pleiotropy and heterogeneity using several methodologies, such as the MR-Egger intercept, the MR-PRESSO approach, and the Cochran's Q test. We took multivariate Mendelian randomization and genetic correlations between related traits to enhance the confidence of the results. Furthermore, we used MRlap to correct for any estimation bias due to sample overlap. Results: Insomnia, napping during the day, and sleep apnea syndrome exhibited a positive connection with the frailty index in forward MR analysis. Conversely, there is a negative link between getting up in the morning, snoring and sleep duration with the frailty index. During the reverse MR analysis, the frailty index exhibited a positive correlation with insomnia, napping during the day, and sleep apnea syndrome, while demonstrating a negative correlation with sleep duration. There was no direct correlation between snoring, chronotype, and frailty. In MVMR analyses, the causal effect of sleep characteristics on frailty indices remained consistent after adjusting for potential confounders including BMI, smoking, and triglycerides. Conclusion: The findings of our investigation yield novel evidence that substantiates the notion of a bidirectional causal connection between sleep traits and frailty. Through the optimization of sleep, it is potentially feasible to hinder, postpone, or even reverse the state of frailty, and we proposed relevant interventions.

Sleep traits and breast cancer risk: a two-sample Mendelian randomization study.

Globally, breast cancer continues to be the leading cause of cancer-related incidence and mortality among females. Research has shown that sleep patterns significantly influence tumor onset and progression. In this research, the association was examined through the application of a two-sample Mendelian randomization (MR) approach. For the analysis of seven sleep patterns, genetic tools were sourced from both the UK Biobank and 23andMe, including morning/evening person (chronotype) n = 177,604, morning person (chronotype) n = 248,094, daytime dozing/sleepiness n = 193,472, getting up in the morning n = 193,717, and sleeplessness n = 193,987; sleep duration n = 192,810; and nap during the day n = 166,853. The Breast Cancer Association Consortium (BCAC) supplied genome-wide association studies (GWAS) data, including 133,384 breast cancer cases and 113,789 controls, alongside subtype-specific data with 106,278 cases and 91,477 controls. We discovered that chronotype encompasses both morning and evening types contributes to the risk of overall breast cancer. While daytime dozing and morning person (chronotype) are linked to a lower risk of breast cancer in general, In subtype-specific analyses, morning person (chronotype) was negatively associated with luminal B, HER2-negative-like, and daytime dozing was negatively correlated with luminal A-like, luminal B-like, and HER2-enriched-like. The study corroborates that chronotype is a danger element for breast cancer, aligning with previous observational findings. The association between being a morning person (chronotype) or having daytime dozing and a decreased risk of breast cancer underscores the significance of sleep patterns in formulating strategies for cancer prevention.

Increased susceptibility to new-onset atrial fibrillation in diabetic women with poor sleep behaviour traits: findings from the prospective cohort study in the UK Biobank.

BACKGROUND: Diabetic individuals often encounter various sleep-related challenges. Although the association between sleep duration and atrial fibrillation (AF) have been explored, the association of other sleep traits with the incidence of AF remains unclear. A comprehensive understanding of these traits is essential for a more accurate assessment of sleep conditions in patients with diabetes and the development of novel AF prevention strategies. METHODS: This study involved 23,785 patients with diabetes without any pre-existing cardiovascular disease, drawn from the UK Biobank. Sleep behaviour traits examined encompassed sleep duration, chronotype, insomnia, snoring and daytime sleepiness. Sleep duration was categorised into three groups: low (≤ 5 h), proper (6-8 h) and long (≥ 9 h). We assessed associations using multivariate Cox proportional risk regression models. Furthermore, four poor sleep behaviours were constructed to evaluate their impact on the risk of new-onset AF. RESULTS: Over a mean follow-up period of 166 months, 2221 (9.3%) new cases of AF were identified. Short (hazard ratio (HR), 1.28; 95% confidence interval (CI) 1.10-1.50) and long sleep durations (HR 1.16; 95% CI 1.03-1.32) consistently exhibited an elevated risk of AF compared to optimal sleep duration. Early chronotype, infrequent insomnia and daytime sleepiness were associated with 11% (HR 0.89; 95% CI 0.82-0.97), 15% (HR 0.85; 95% CI 0.77-0.95) and 12% (HR 0.88; 95% CI 0.81-0.96) reduced risk of new-onset AF, respectively. However, no significant association was found between snoring and the incidence of AF (HR 0.99; 95% CI 0.91-1.07). CONCLUSIONS: In diabetic populations, sleep duration, chronotype, insomnia and daytime sleepiness are strongly associated with AF incidence. An optimal sleep duration of 6-8 h presents the lowest AF risk compared to short or long sleep duration. Additionally, poor sleep patterns present a greater risk of new-onset AF in women than in men.

Causal Relationship Between Sleep Traits and Hypothalamic-Pituitary-Target Gland Axis Function: A Mendelian Randomization Study.

Background: In recent years, multiple observational studies have confirmed the association between sleep traits and various human physiopathological states. However, the causal relationship between sleep traits and hypothalamic-pituitary-target gland axis (HPTGA) function remains unknown. Methods: We obtained summary statistics on sleep traits (insomnia, chronotype, and sleep duration (long and short)) from the UK Biobank database. Data related to the HPTGA functions were obtained from the publicly available database. Subsequently, a two-sample Mendelian randomization (MR) analysis was performed to investigate the causal relationship between different sleep traits and the HPTGA function. Reverse MR analysis was conducted to examine the direction of causality. Results: The MR analysis results suggested that chronotype is associated with decreased levels of six hormones in HPTGA. Sleep duration was causally associated with decreased levels of free thyroxine and progesterone. Both long and short sleep durations are detrimental to the secretion of prolactin-releasing peptide, somatostatin, and plasma cortisol, while short sleep duration can promote progesterone secretion. After gender stratification, we found that female reproductive function is more susceptible to the influence of unfavorable sleep traits. Conclusion: Our MR analysis indicated a significant causal association between chronotype and suppressed gonadal function in healthy adult humans, with no apparent gender-specific effect. Extreme sleep durations were also found to be detrimental to the maintenance of normal HPTGA secretion function. Compared to males, gonadal function in the female cohort is more susceptible to extreme sleep habits. Subsequent observational studies are urgently needed to confirm the underlying mechanisms.

Association of sleep traits with benign prostatic hyperplasia in middle-aged and elderly men: A prospective analysis in UK Biobank.

AIMS: The association of sleep traits (insomnia, sleep duration, chronotype, daytime sleepiness, and snoring) with benign prostatic hyperplasia (BPH) is unclear. This research aimed to examine the effects of sleep traits on BPH risk. METHODS: A total of 170 241 men aged 38 to 73 years from UK Biobank were included. An overall healthy sleep score was created based on five sleep traits. A Cox regression model was utilized to compute adjusted hazard ratios (HRs) and population attributable fractions (PAFs) with 95% confidence intervals (CIs) for BPH risk in relation to sleep traits. RESULTS: During a median of 12.0 years follow-up, 13 026 incident BPH cases occurred. We observed that sleep duration (7-8 h/d; HR 0.95; 95% CI 0.92-0.99), no frequent insomnia (HR 0.71; 95% CI 0.69-0.74), and no frequent daytime sleepiness (HR 0.86; 95% CI 0.79-0.93) were significantly related to reduced BPH risk. Each one-point increment of the healthy sleep score was related to a decreased BPH risk, with an adjusted HR of 0.90 (95% CI 0.89-0.92). The multivariable-adjusted HR in men adopting five versus zero to one low-risk sleep traits was 0.68 (95% CI 0.61-0.75) for BPH risk. Estimates of the PAF indicated that 9.1% (95% CI 5.8-12.5%) of BPH cases would be prevented if all individuals had adopted all five low-risk sleep traits, assuming causality. CONCLUSIONS: Our study indicates an association between a healthy sleep pattern and a lower risk of BPH, emphasizing the importance of adhering to such patterns for potentially reducing BPH risk. Geriatr Gerontol Int 2024; 24: 675-682.

Association between sleep traits and sarcopenia-related traits: A two-sample bidirectional Mendelian randomization study.

AIM: Despite limited evidence regarding the impact of sleep quality on sarcopenia, it is widely recognized as being associated with various diseases. This study aimed to explore the causal relationship between sleep traits and sarcopenia-related traits. METHODS: This study utilized a two-sample bidirectional Mendelian randomization analysis. Genetic genome-wide summary data of sleep quality indicators, including chronotype, morning wake-up time, sleep duration, daytime napping, insomnia and daytime dozing, were used. Data on sarcopenia-related traits, such as appendicular lean mass, grip strength of both hands, walking pace and waist circumference, were collected from a large cohort study. The primary method used was the inverse-variance weighted analysis. RESULTS: A causal association was found between chronotype and appendicular lean mass (odds ratio [OR] 1.019, 95% confidence interval [CI] 1.016-1.211, P = 0.021). Napping during the day was connected with walking pace (OR 0.879, 95% CI 0.834-0.928, P = 2.289 × 10-6) and waist circumference (OR 1.234, 95% CI 1.081-1.408, P = 0.002). Insomnia was related to lower grip strength of the right hand (OR 0.844, 95% CI 0.747-0.954, P = 0.007), left hand (OR 0.836, 95% CI 0.742-0.943, P = 0.003), as well as walking pace (OR 0.871, 95% CI 0.798-0.951, P = 0.002). Furthermore, the reverse Mendelian randomization analysis showed associations between certain sarcopenia-related traits and poor sleep quality. CONCLUSIONS: Some sleep traits were associated with the occurrence of sarcopenia. These findings emphasized the significance of prioritizing sleep quality as a preventive measure against sarcopenia. Geriatr Gerontol Int 2024; 24: 537-545.

Mendelian randomization of individual sleep traits associated with major depressive disorder.

BACKGROUND: Observational studies have shown that individual sleep traits habits are potential risk factors for major depression. However, it is not known whether there is a causal relationship between individual sleep traits habits such as continuous sleep duration, short sleep duration, short sleep duration, insomnia, nap during the day, snoring, and major depression. In this study, Mendelian randomization (MR) was used to predict major depressive disorder (MDD) in individuals sleep traits habits. METHODS: Data were obtained from the genome-wide association study (GWAS). Nine MR analysis methods were used: Inverse Variance Weighted (IVW) [fixed effects/multiplicative random effects], simple mode, simple mode, weighted mode, simple median, weighted median, penalised weighted median, and MR-Egger, MR Egger (bootstrap). IVW was used as the main analysis method for the MR analysis of two samples, and the other methods were used as supplements. RESULTS: The results obtained through the IVW method supported a causal relationship between sleep duration and decreased risk of MDD (odds ratio, ORivw: 0.998; 95 % CI: 0.996-0.999, P<0.001). Two-Sample MR, results showed that short sleep duration has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.179; 95 % CI: 1.108-1.255, P<0.001). However, there were no sufficient evidence supported that long sleep duration has a causal effect on the decreased risk of MDD (odds ratio, ORivw: 0.991; 95 % CI: 0.924-1.062, P = 0.793). A significant causal relationship between insomnia and increased risk of MDD was observed (OR: 1.233; 95 % CI: 1.214-1.253, P<0.001). Interestingly, our study also found that daytime napping has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.519; 95 % CI: 1.376-1.678, P<0.001). The present results did not show a significant causal relationship between snoring and the risk of MDD (ORivw: 1.000; 95 % CI: 0.998-1.002, P = 0.906). Obstructive sleep apnea (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) and morning person (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) have no causal effect on the increased risk of MDD. LIMITATIONS: The study could not ascertain whether there were genetic differences among different ethnicities, nations, and regions, as it only included participants of European ancestry. CONCLUSIONS: In summary, our research provides genetic evidence for the relationship between individual sleep traits (short sleep duration, insomnia, daytime napping) and the increased risk of MDD. Interventions targeting lifestyle factors may reduce the risk of MDD.

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, 2024.

Causal association between sleep traits and the risk of coronary artery disease in patients with diabetes.

Background and aims: The association between sleep traits and coronary artery disease (CAD) in patients with diabetes has been reported in previous observational studies. However, whether these potential relationships are causal remains unclear. We aim to assess the causal relationship between sleep traits and CAD in diabetic. Methods: Genetic instrumental variables associated with five sleep-related traits (insomnia, sleep duration, ease of getting up, morningness and snoring) were extracted from corresponding genome-wide association studies (GWAS). The associations of genetic variants with CAD were based on 15,666 individuals with diabetes (3,968 CAD cases and 11,696 controls). The primary analysis was derived using the inverse variance weighting method. Further sensitivity analysis was conducted to confirm the robustness and consistency of the main results. Results: Genetic liability to insomnia was significantly related to the increased risk of CAD in individuals with diabetes [odds ratio (OR): 1.163; 95% CI: 1.072-1.254; p = 0.001]. Suggestive evidence was found for the borderline associations between both sleep duration (OR: 0.629; 95% CI: 0.380-1.042, p = 0.072) and snoring (OR: 1.010, 95% CI: 1.000-1.020, p = 0.050) with CAD risk. However, no consistent evidence was found for the association between ease of getting up and morningness with the risk of CAD in diabetic. Similar results can be verified in most sensitivity analyses. Conclusions: We provide consistent evidence for the causal effect of insomnia on the increased risk of CAD in individuals with diabetes. The management of sleep health should be emphasized to prevent CAD in diabetic patients.

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: ß = -0.05, 95% CI -0.07 to -0.04, p = 1.93×10-12 ), daytime sleepiness (average cortical thickness: ß = -0.12, 95% CI -0.22 to -0.02, p = 0.023), and daytime napping (fluid intelligence: ß = -0.47, 95% CI -0.87 to -0.07, p = 0.021; hippocampal volume in Alzheimer's disease: ß = -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.

Causal associations of sleep traits with cancer incidence and mortality.

To explore the correlation and causality between multidimensional sleep traits and pan-cancer incidence and mortality among patients with cancer. The multivariable Cox regression, linear and nonlinear Mendelian randomization (MR), and survival curve analyses were conducted to assess the impacts of chronotype, sleep duration, and insomnia symptoms on pan-cancer risk (N = 326,417 from United Kingdom Biobank) and mortality (N = 23,956 from United Kingdom Biobank). In the Cox regression, we observed a linear and J-shaped association of sleep duration with pan-cancer incidence and mortality among cancer patients respectively. In addition, there was a positive association of insomnia with pan-cancer incidence (HR, 1.03, 95% CI: 1.00-1.06, p = 0.035), all-cause mortality (HR, 1.17, 95% CI: 1.06-1.30, p = 0.002) and cancer mortality among cancer patients (HR, 1.25, 95% CI: 1.11-1.41, p < 0.001). In the linear MR, there was supporting evidence of positive associations between long sleep duration and pan-cancer incidence (OR, 1.41, 95% CI: 1.08-1.84, p = 0.012), and there was a positive association between long sleep duration and all-cause mortality in cancer patients (OR, 5.56, 95% CI: 3.15-9.82, p = 3.42E-09). Meanwhile, a strong association between insomnia and all-cause mortality in cancer patients (OR, 1.41, 95% CI: 1.27-1.56, p = 4.96E-11) was observed in the linear MR. These results suggest that long sleep duration and insomnia play important roles in pan-cancer risk and mortality among cancer patients. In addition to short sleep duration and insomnia, our findings highlight the effect of long sleep duration in cancer prevention and prognosis.