Sleep Traits Research Articles

Causal relationship between sleep traits and erectile dysfunction: Evidence from Mendelian Randomization analysis

IntroductionAlthough 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 methodsInstrumental 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.ResultsMR 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.ConclusionsThis 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.

Polygenic Risk Score-Based Association Analysis Identifies Genetic Comorbidities Associated with Age-Related Hearing Difficulty in Two Independent Samples.

Age-related hearing loss is the most common form of permanent hearing loss that is associated with various health traits, including Alzheimer's disease, cognitive decline, and depression. The present study aims to identify genetic comorbidities of age-related hearing loss. Past genome-wide association studies identified multiple genomic loci involved in common adult-onset health traits. Polygenic risk scores (PRS) could summarize the polygenic inheritance and quantify the genetic susceptibility of complex traits independent of trait expression. The present study conducted a PRS-based association analysis of age-related hearing difficulty in the UK Biobank sample (N = 425,240), followed by a replication analysis using hearing thresholds (HTs) and distortion-product otoacoustic emissions (DPOAEs) in 242 young adults with self-reported normal hearing. We hypothesized that young adults with genetic comorbidities associated with age-related hearing difficulty would exhibit subclinical decline in HTs and DPOAEs in both ears. A total of 111,243 participants reported age-related hearing difficulty in the UK Biobank sample (> 40years). The PRS models were derived from the polygenic risk score catalog to obtain 2627 PRS predictors across the health spectrum. HTs (0.25-16kHz) and DPOAEs (1-16kHz, L1/L2 = 65/55dB SPL, F2/F1 = 1.22) were measured on 242 young adults. Saliva-derived DNA samples were subjected to low-pass whole genome sequencing, followed by genome-wide imputation and PRS calculation. The logistic regression analyses were performed to identify PRS predictors of age-related hearing difficulty in the UK Biobank cohort. The linear mixed model analyses were performed to identify PRS predictors of HTs and DPOAEs. The PRS-based association analysis identified 977 PRS predictors across the health spectrum associated with age-related hearing difficulty. Hearing difficulty and hearing aid use PRS predictors revealed the strongest association with the age-related hearing difficulty phenotype. Youth with a higher genetic predisposition to hearing difficulty revealed a subclinical elevation in HTs and a decline in DPOAEs in both ears. PRS predictors associated with age-related hearing difficulty were enriched for mental health, lifestyle, metabolic, sleep, reproductive, digestive, respiratory, hematopoietic, and immune traits. Fifty PRS predictors belonging to various trait categories were replicated for HTs and DPOAEs in both ears. The study identified genetic comorbidities associated with age-related hearing loss across the health spectrum. Youth with a high genetic predisposition to age-related hearing difficulty and other related complex traits could exhibit sub-clinical decline in HTs and DPOAEs decades before clinically meaningful age-related hearing loss is observed. We posit that effective communication of genetic risk, promoting a healthy lifestyle, and reducing exposure to environmental risk factors at younger ages could help prevent or delay the onset of age-related hearing difficulty at older ages.

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

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. 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. 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. 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.

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

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. 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. 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. 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.

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

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. 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. 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). Decreased sleep duration was associated with increased risk of thyroid cancer, which indicated the importance of adequate sleep for the prevention of thyroid cancer.

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

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. 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. 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. 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.

Relationships between orofacial pain and sleep: Analysis of UK biobank and genome-wide association studies data

Background/purposeOrofacial pain is common in dental practices. This study aimed to explore relationships between orofacial pain and sleep using the UK Biobank dataset and, based on epidemiological associations, to investigate the causal association using genome-wide association studies data. Materials and methodsFirst, a cross-sectional study was conducted with 196,490 participants from UK Biobank. Information on pain conditions and sleep traits was collected. Multivariable models were used to explore the relationships with odds ratio (OR). Second, Mendelian randomization analyses were conducted using data for orofacial pain, including temporomandibular joint disorders-related pain (n = 377,277) and atypical facial pain (n = 331,749), and sleep traits, including sleep duration (n = 446,118), short sleep (n = 411,934), long sleep (n = 339,926), snoring (n = 359,916), ease of getting up (n = 385,949), insomnia (n = 453,379), daytime dozing (n = 452,071), daytime napping (n = 452,633), and chronotype (n = 403,195). ResultsThe cross-sectional study confirmed the bidirectionality between pain and sleep. Participants experiencing pain all over the body showed a significant association with an unhealthy sleep pattern (OR = 1.18, P < 0.001) and other sleep traits (P < 0.05). Risks of chronic orofacial pain were associated with sleep duration in a non-linear relationship (P = 0.032). The Mendelian randomization analyses indicated that long sleep was causally associated with temporomandibular joint disorders-related pain (OR = 6.77, P = 0.006). ConclusionThe relationship between pain and sleep is bidirectional. Long sleep is found to be causally associated with chronic orofacial pain.

Dissecting the genetic and causal relationship between sleep-related traits and common brain disorders

BackgroundThere is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated. MethodsUtilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways. ResultsLDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships. ConclusionsThis study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.

Association of genetically determined chronotype with circulating testosterone: a Mendelian randomization study.

Low testosterone levels in men have been linked to decreased physical and mental function, as well as a reduced quality of life. Previous prospective observational studies have suggested an association between testosterone and sleep traits, but the causality of this relationship remains unclear. We aimed to explore the potential causal link between genetically determined sleep traits and testosterone levels in men using Mendelian randomization (MR) analysis from the UK Biobank dataset. Our exposures were genetic variants associated with sleep traits (chronotype and sleep duration), whereas our outcomes were traits of sex steroid hormones (total testosterone, TT; bioavailable testosterone, BAT; and sex hormone-binding globulin, SHBG). We employed inverse variance weighted (IVW) and weighted median (WM) methods to assess the causal associations. The IVW method offers a robust estimate of causality, whereas the WM method provides reliable results even when some genetic variants are invalid instruments. Our main analysis involving sex steroid hormones and chronotype identified 155 chronotype-related variants. The primary findings from the analysis, which used chronotype as the exposure and sex steroid hormones as the outcomes, showed that a genetically predicted chronotype score was significantly associated with an increased levels of TT (association coefficient β, 0.08; 95% confidence interval [CI], 0.02-0.14; P = 0.008) and BAT (β, 0.08; 95% CI, 0.02-0.14; P = 0.007), whereas there was no significant association with SHBG (β, 0.01; 95% CI, -0.02-0.03; P = 0.64). Meanwhile, MR analysis of sex steroid hormones and sleep duration was performed, and 69 variants associated with sleep duration were extracted. There were no significant association between sleep duration and sex steroid hormones (TT, P = 0.91; BAT, P = 0.82; and SHBG, P = 0.95). Our data support a causal association between chronotype and circulating testosterone levels in men. These findings underscore a potential causal relationship between chronotype and testosterone levels in men, suggesting that lifestyle adjustments are crucial for men's health. Recognizing factors that influence testosterone is essential. One limitation of this study is the use of one-sample MR, which can introduce potential bias due to non-independence of genetic associations for exposure and outcome. In conclusion, our findings indicate that a morning preference is correlated with circulating testosterone levels, emphasizing the potential impact of lifestyle habits on testosterone levels in men.

Variation in Sleep Traits in the Indian Population During Social Restriction

Aim: We conducted this study to investigate the impact of social restrictions on chronotype categories, social jetlag, and sleep parameters in the Indian population. Materials and Methods: A cross-sectional study was conducted in 2021 with 139 participants. We used an online questionnaire (Google Form) enclosing respondents' sociodemographic information Social jetlag and sleep parameters were measured with the µ-MCTQ and chronotype was assessed by the r-MEQ. Chi-square, paired t-tests, and One-way ANOVA were used to analyse the data. Pearson correlation was used to determine the strength of the relationship between the variables. Results: Our results highlighted that a total of 23.8% of volunteers reported social jetlag before social restriction and it significantly reduced to 13.7% (P = .001) in the social restricted condition. There is no significant difference in sleep duration during the workday and free days of socially restriction (P = .11). We found a difference between midsleep free day (MSf) and midsleep free day corrected (MSfsc) (mean of 13 min before restrictions (P = .05) and 10 min during restrictions; P = .001). Conclusion: Our findings provide crucial insights into variations in sleep/wake schedule stability, as seen by changes in the decrease of social jetlag between restriction. It was established that the individuals had significantly equivalent total sleep at both time points, as well as a later sleep-wake time under the social restriction.

A resting-state EEG dataset for sleep deprivation

To investigate the impact of sleep deprivation (SD) on mood, alertness, and resting-state electroencephalogram (EEG), we present an eyes-open resting-state EEG dataset. The dataset comprises EEG recordings and cognitive data from 71 participants undergoing two testing sessions: one involving SD and the other normal sleep. In each session, participants engaged in eyes-open resting-state EEG. The Psychomotor Vigilance Task (PVT) was employed for alertness measurement. Emotional and sleepiness were measured using Positive and Negative Affect Scale (PANAS) and Stanford Sleepiness Scale (SSS). Additionally, to examine the influence of individual sleep quality and traits on SD, Pittsburgh Sleep Quality Index (PSQI) and Buss-Perry Aggression Questionnaire (BPAQ) were utilized. This dataset’s sharing may contribute to open EEG measurements in the field of SD.

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

BackgroundSleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study.MethodsGenome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran’s Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability.ResultsForward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003–1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096–2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results.ConclusionThis study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

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

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. 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. 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. 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.

Causal effects of sleep traits on metabolic syndrome and its components: a Mendelian randomization study.

Previous observational studies have suggested an association between sleep disturbance and metabolic syndrome (MetS). However, it remains unclear whether this association is causal. This study aims to investigate the causal effects of sleep-related traits on MetS using Mendelian randomization (MR). Single-nucleotide polymorphisms strongly associated with daytime napping, insomnia, chronotype, short sleep, and long sleep were selected as genetic instruments from the corresponding genome-wide association studies (GWAS). Summary-level data for MetS were obtained from two independent GWAS datasets. Univariable and multivariable MR analyses were conducted to investigate and verify the causal effects of sleep traits on MetS. The univariable MR analysis demonstrated that genetically predicted daytime napping and insomnia were associated with increased risk of MetS in both discovery dataset (OR daytime napping = 1.630, 95% CI 1.273, 2.086; OR insomnia = 1.155, 95% CI 1.108, 1.204) and replication dataset (OR daytime napping = 1.325, 95% CI 1.131, 1.551; OR insomnia = 1.072, 95% CI 1.046, 1.099). For components, daytime napping was positively associated with triglycerides (beta = 0.383, 95% CI 0.160, 0.607) and waist circumference (beta = 0.383, 95% CI 0.184, 0.583). Insomnia was positively associated with hypertension (OR = 1.101, 95% CI 1.042, 1.162) and waist circumference (beta = 0.067, 95% CI 0.031, 0.104). The multivariable MR analysis indicated that the adverse effect of daytime napping and insomnia on MetS persisted after adjusting for BMI, smoking, drinking, and another sleep trait. Our study supported daytime napping and insomnia were potential causal factors for MetS characterized by central obesity, hypertension, or elevated triglycerides.

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

Previous studies have suggested a potential association between Autoimmune thyroid disease Thyroid nodules and Sleep Traits, but the evidence is limited and controversial, and the exact causal relationship remains uncertain. Therefore, we employed a MR analysis to investigate the causal relationship between Autoimmune thyroid disease, Thyroid nodules and Sleep Traits. To explore the interplay between Autoimmune thyroid disease Thyroid nodules and Sleep Traits, we employed MR studies utilizing summary statistics derived from GWAS in individuals of European ancestry. To ensure robustness, multiple techniques were employed to assess the stability of the causal effect, including random-effect inverse variance weighted, weighted median, MR-Egger regression, and MR-PRESSO. Heterogeneity was evaluated using Cochran's Q value. Additionally, we investigated the presence of horizontal pleiotropy through MR-Egger regression and MR-PRESSO. The IVW method indicates a significant causal relationship between "Getting up" and autoimmune hypothyroidism, as revealed by the IVW method (OR: 0.59, 95% CI: 0.45 to 0.78, P-value = 1.99e-4). Additionally, there might be a potential correlation between sleep duration and autoimmune hypothyroidism (OR: 0.76, 95% CI: 0.60 to 0.79, P-value = 0.024). Moreover, the observed potential positive link between daytime nap and thyroid nodules (OR: 1.66, 95% CI: 1.07 to 2.58, P-value = 0.023) is subject to caution, as subsequent MR PRESSO testing reveals the presence of horizontal pleiotropy, raising concerns about the reliability of the findings. The findings suggested a potential inverse association between Autoimmune hypothyroidism and Getting up (OR: 0.99, 95% CI: 0.98 to 1.00, P-value = 6.66e-3).As the results of MR-Egger method(OR: 1.00, 95% CI: 0.98 to 1.02, P-value = 0.742) exhibited an opposing trend to that observed with the IVW method and the results did not reach significance after P-value correction. The results of our study reveal a notable cause-and-effect relationship between Getting up and Autoimmune hypothyroidism, indicating its potential role as a protective factor against this condition. However, no causal connection was observed between sleep traits and Graves' disease or Thyroid nodules.

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

BackgroundMyopia 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.MethodsLSB, 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.ResultsComputer 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.ConclusionOur 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.

No evidence linking sleep traits with white blood cell counts: Multivariable-adjusted and Mendelian randomization analyses.

Disturbances in habitual sleep have been associated with multiple age-associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable-adjusted linear regression and Mendelian randomization. Cross-sectional multivariable-adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/μL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two-sample Mendelian randomization analyses were done using instruments for sleep traits derived from European-ancestry participants from UK Biobank (over 410,000 participants) and using SNP-outcome data derived from European-ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep-disease associations.

Sleep traits and associated factors among people living with HIV/AIDS in Iran: a two-step clustering analysis

Sleep plays an essential role in improving the quality of life of people living with HIV (PLWH); however, sleep traits in this population are not well studied. This study aims to evaluate the sleep traits and related associated factors among PLWH in Iran. A nationwide cross-sectional study was conducted with 1185 PLWH who attended Voluntary Counseling and Testing centers in 15 provinces in Iran between April 2021 and March 2022. The Berlin Obstructive Sleep Apnea questionnaire, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index were used. A two-step clustering method was employed to identify the number of sleep clusters in PLWH. Prevalence of poor sleep quality, sleepiness and insomnia were 49.6%, 21.15% and 42.7% respectively. Three sleep trait clusters were identified: I. minor sleep problems (45.6%); II. Snoring & sleep apnea (27.8%), and III. poor sleep quality and insomnia (26.7%). Age (Odds Ratio (OR) 1.033, 95% Confidence Interval (CI) 1.017–1.050), academic education (OR 0.542, 95% CI 0.294–0.998) and HIV duration were associated with being in Snoring & sleep apnea cluster, while age (OR = 1.027, 95% CI 1.009–1.040) was associated with being in Poor sleep quality and insomnia cluster. PLWH with depression had higher odds of being in Poor sleep quality and insomnia cluster, and those with anxiety had higher odds of being in Snoring & sleep apnea cluster and Poor sleep quality and insomnia cluster. A significant proportion of PLWH have poor sleep quality, sleepiness, and insomnia. The identification of three distinct sleep trait clusters underscores the need for increased attention and tailored interventions to address the specific sleep issues experienced by PLWH.

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

BackgroundDiabetic 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.MethodsThis 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.ResultsOver 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).ConclusionsIn 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.

Nightmares share genetic risk factors with sleep and psychiatric traits.

Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e-06), depressive (rg = 0.562, p = 1.282e-07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e-07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual's liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.