Association between Sleep Traits and Lung Cancer: A Mendelian Randomization Study.
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ABSTRACT:
SUBMITTER: Wang J
PROVIDER: S-EPMC8238591 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Currently, the causal association between sleep disorders and rheumatoid arthritis (RA) has been poorly understood. In this two-sample Mendelian randomization (TSMR) study, we tried to explore whether sleep disorders are causally associated with RA. Seven sleep-related traits were chosen from the published Genome-Wide Association Study (GWAS): short sleep duration, frequent insomnia, any insomnia, sleep duration, getting up, morningness (early-to-bed/up habit), and snoring, 27, 53, 57, 57, 70, 274, and 42 individual single-nucleotide polymorphisms (SNPs) (P < 5 × 10-8) were obtained as instrumental variables (IVs) for these sleep-related traits. Outcome variables were obtained from a public GWAS study that included 14,361 cases and 43,923 European Ancestry controls. The causal relationship between sleep disturbances and RA risk were evaluated by a two-sample Mendelian randomization (MR) analysis using inverse variance weighted (IVW), MR-Egger regression, weighted median, and weight mode methods. MR-Egger Regression and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) were used to test for horizontal pleomorphism and outliers. There was no evidence of a link between RA and frequent insomnia (IVW, odds ratio (OR): 0.99; 95% interval (CI): 0.84-1.16; P = 0.858), any insomnia (IVW, OR: 1.09; 95% CI: 0.85-1.42; P = 0.489), sleep duration (IVW, OR: 0.65, 95% CI: 0.38-1.10, P = 0.269), getting up (IVW, OR: 0.56, 95% CI: 0.13-2.46, P = 0.442), morningness (IVW, OR: 2.59; 95% CI: 0.73-9.16; P = 0.142), or snoring (IVW, OR: 0.95; 95% CI: 0.68-1.33; P = 0.757). Short sleep duration (6h) had a causal effect on RA, as supported by IVW and weighted median (OR: 1.47, 95% CI: 1.12-1.94, P = 0.006; OR: 1.43, 95%CI:1.01-2.05, P = 0.047). Sensitivity analysis showed that the results were stable. Our findings imply that short sleep duration is causally linked to an increased risk of RA. Therefore, sleep length should be considered in disease models, and physicians should advise people to avoid short sleep duration practices to lower the risk of RA.
| S-EPMC9280285 | biostudies-literature
Project description:Evidence on whether habitual sleep duration and sleep quality are associated with increased insulin resistance is inconsistent. Here, we investigated the associations between different measures of habitual sleep with glycemic traits through cross-sectional and Mendelian randomization (MR) analyses. We assessed the associations of sleep duration and sleep quality with glycemic traits using multivariable linear regression models adjusted for potential confounders in 4672 middle-aged (45-65 years; 48% men) nondiabetic participants of the Netherlands Epidemiology of Obesity (NEO) study. Genetic variants for total, short, and long sleep duration were used as instrumental variables in MR analyses using summary-level data of glycemic traits in nondiabetic individuals (MAGIC; n = 58,074). In cross-sectional analyses, shortest sleepers (median 5.0 h of sleep per night) had 14.5% (95% confidence interval (CI): 2.0; 28.6%) higher fasting insulin level and 16.3% (95% CI: 2.7; 31.7%) higher HOMA-β. Bad sleep quality was associated with higher insulin resistance (e.g., 14.3% (95% CI: 4.7; 24.9%) higher HOMA-IR). All these associations disappeared after adjustment for BMI and the risk of sleep apnea. MR analyses did not indicate a causal association between total, short or long sleep duration and glycemic traits. Therefore, our used measures of habitual sleep duration and sleep quality are unlikely to directly associate with insulin resistance.
| S-EPMC6572144 | biostudies-other
Project description:Background and Aim: Aberrant sleep parameters are associated with the risk of nonalcoholic fatty liver disease (NAFLD). However, existing information is inconsistent among studies and involves reverse causation. Therefore, we aimed to investigate the observational associations and causations between sleep traits and NAFLD. Methods: We performed multivariable regression to assess observational associations of seven sleep traits (sleep duration, easiness of getting up in the morning, chronotype, nap during day, snoring, insomnia, and narcolepsy), and NAFLD in the UK Biobank (1,029 NAFLD). The Cox proportional hazards model was applied to derive hazard ratios and 95% confidence intervals (CIs). Furthermore, a bidirectional two-sample Mendelian randomization (MR) approach was used to explore the causal relationships between sleep traits and NAFLD. Results: In the multivariable regression model adjusted for potential confounders, getting up in the morning not at all easy (HR, 1.51; 95% CI, 1.27-1.78) and usually insomnia (HR, 1.46; 95% CI, 1.21-1.75) were associated with the risk of NAFLD. Furthermore, the easiness of getting up in the morning and insomnia showed a dose-response association with NAFLD (Ptrend <0.05). MR analysis found consistent causal effects of NAFLD on easiness of getting up in the morning (OR, 0.995; 95% CI, 0.990-0.999; p = 0.033) and insomnia (OR, 1.006; 95% CI, 1.001-1.011; p = 0.024). These results were robust to weak instrument bias, pleiotropy, and heterogeneity. Conclusions: Findings showed consistent evidence of observational analyses and MR analyses that trouble getting up in the morning and insomnia were associated with an increased risk of NAFLD. Bidirectional MR demonstrated causal effects of NAFLD on sleep traits.
| S-EPMC9152285 | biostudies-literature
Project description:ObjectivesThis study aims to investigate the relationship between five sleep traits (insomnia, sleep duration, getting up in morning, snoring, and daytime nap) and temporomandibular disorders (TMD) using bi-directional Mendelian randomization.MethodsThe bi-directional Mendelian randomization study was conducted in two stages. Initially, sleep traits were examined as exposures while TMD was evaluated as an outcome, whereas the second step was reversed. The inverse variance weighted (IVW) method and other Mendelian randomization methods were used for analysis. Furthermore, we performed the MR-Egger intercept, MR-PRESSO, Cochran's Q test, and "Leave-one-out" to assess the levels of pleiotropy and heterogeneity.ResultsThe IVW method indicates that getting up in the morning reduces the risk of developing TMD (OR = 0.50, 95% CI 0.30-0.81, p = 0.005), while insomnia may increase the risk of TMD (OR = 2.05, 95% CI 1.10-3.85, p = 0.025). However, other sleep traits are not associated with the risk of TMD, and having TMD does not alter an individual's sleep traits. After removing outliers, the results remained robust, with no pleiotropy detected.ConclusionGenetically determined difficulty in getting up in the morning and insomnia can increase the risk of TMD. By optimizing sleep, the risk of developing TMD can be reduced. This underscores the importance of sleep in preventing TMD.
| S-EPMC11303139 | biostudies-literature
Project description:A correlation between sleep and systemic lupus erythematosus (SLE) has been observed in a number of prior investigations. However, little is known regarding the potential causative relationship between them. In this study, we selected genetic instruments for sleep traits from pooled data from published genome-wide association studies (GWAS). Independent genetic variants associated with six sleep-related traits (chronotype, sleep duration, short sleep duration, long sleep duration, insomnia, and daytime sleepiness) were selected as instrumental variables. A two-sample Mendelian randomization (TSMR) study was first conducted to assess the causal relationship between sleep traits and SLE (7219 cases versus 15,991 controls). The reverse MR analysis was then used to infer the causal relationship between SLE and sleep traits. Inverse variance weighted (IVW), MR Egger, Weighted median, and Weighted mode were applied to perform the primary MR analysis. MR Egger regression and the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test were used to detect horizontal pleiotropy, and Cochran's Q was used to detect heterogeneity. In studies of the effect of sleep traits on SLE risk, the IVW method demonstrated no causal relationship between chronotype, sleep duration, short sleep duration, long sleep duration, insomnia, daytime sleepiness and SLE risk. The remaining three methods agreed with the results of IVW. In studies of the effect of SLE on the risk of sleep traits, neither IVW, MR Egger, Weighted median, nor Weighted mode methods provided evidence of a causal relationship between SLE and the risk of sleep traits. Overall, our study found no evidence of a bidirectional causal relationship between genetically predicted sleep traits and SLE.
| S-EPMC9248809 | biostudies-literature
Project description:Background: The roles of obesity-related biomarkers and their molecular pathways in the development of postmenopausal colorectal cancer (CRC) have been inconclusive. We examined insulin resistance (IR) as a major hormonal pathway mediating the association between obesity and CRC risk in a Mendelian randomization (MR) framework. Methods: We performed MR analysis using individual-level data of 11,078 non-Hispanic white postmenopausal women from our earlier genome-wide association study. We identified four independent single-nucleotide polymorphisms associated with fasting glucose (FG), three with fasting insulin (FI), and six with homeostatic model assessment-IR (HOMA-IR), which were not associated with obesity. We estimated hazard ratios (HRs) for CRC by adjusting for potential confounding factors plus genetic principal components. Results: Overall, we observed no direct association between combined 13 IR genetic instruments and CRC risk (HR = 0.96, 95% confidence interval [CI]: 0.78-1.17). In phenotypic analysis, genetically raised HOMA-IR exhibited its effects on the increased risk and FG and FI on the reduced risk for CRC, but with a lack of statistical power. Subgroup analyses by physical activity level and dietary fat intake with combined phenotypes showed that genetically determined IR was associated with reduced CRC risk in both physical activity-stratified (single contributor: MTRR rs722025; HR = 0.12, 95% CI: 0.02-0.62) and high-fat diet subgroups (main contributor: G6PC2 rs560887; HR = 0.59, 95% CI: 0.37-0.94). Conclusions: Complex evidence was observed for a potential causal association between IR and CRC risk. Our findings may provide an additional value of intervention trials to lower IR and reduce CRC risk.
| S-EPMC7396568 | biostudies-literature
Project description:Alzheimer's disease (AD) manifests with a higher rate of occurrence in women. Previous epidemiological studies have suggested a potential association between AD and gynecological cancers, but the causal relationship between them remains unclear. This study aims to explore the causal link between 12 types of gynecological cancers and AD using a bidirectional Mendelian randomization (MR) approach. We obtained genetic correlation tools for AD using data from the most extensive genome-wide association study. Genetic correlation data for 12 types of gynecological cancers were also sourced from the Finnish Biobank. These cancers include breast cancer (BC), cervical adenocarcinoma (CA), cervical squamous cell carcinoma (CSCC), cervical cancer (CC), endometrial cancer (EC), ovarian endometrioid carcinoma (OEC), ovarian cancer (OC), ovarian serous carcinoma (OSC), breast carcinoma in situ (BCIS), cervical carcinoma in situ (CCIS), endometrial carcinoma in situ (ECIS), and vulvar carcinoma in situ (VCIS). We used the inverse-variance weighted (IVW) model for causal analysis and conducted horizontal pleiotropy tests, heterogeneity tests, MR-PRESSO tests, and leave-one-out analyses to ensure the robustness of our results. We also applied replication analysis and meta-analysis to further validate our experimental results. The study found that EC (P_IVW =0.037, OR [95% CI] = 1.032 [1.002, 1.064]) and CCIS (P_IVW = 0.046, OR [95% CI] = 1.032 [1.011, 1.064]) increase the risk of AD, whereas OC was negatively correlated with AD (P_IVW = 0.016, OR [95% CI] = 0.974[0.954, 0.995]). In reverse MR analysis, AD increased the risk of CC (P_IVW = 0.039, OR [95% CI] = 1.395 [1.017, 1.914]) and VCIS (P_IVW = 0.041, OR [95% CI] = 1.761 [1.027, 2.021]), but was negatively correlated with OEC (P_IVW = 0.034, OR [95% CI] = 0.634 [0.417, 0.966]). Sensitivity analysis results demonstrated robustness. These findings were further substantiated through replication and meta-analyses. Our MR study supports a causal relationship between AD and gynecological cancers. This encourages further research into the incidence of gynecological cancers in female Alzheimer's patients and the active prevention of AD.
| S-EPMC11337634 | biostudies-literature
Project description:ObjectiveExtensive literature put forward the link between sleep and type 2 diabetes mellitus (T2DM), however, little is known about the underlying causality of the associations. Here we aim to assess the causal relationships between five major sleep-related traits and T2DM.Design setting and participantsTwo-sample Mendelian randomization (MR) was utilized to investigate the potential causal relations. Independent genetic variants associated with five sleep-related phenotypes-insomnia, sleep duration, short sleep duration, long sleep duration, and morningness-were chosen as instrumental variables to estimate the causal associations with T2DM. Summary statistics were acquired from the genome-wide association studies of UK Biobank and 23andMe (for sleep-related measures), the DIAbetes Genetics Replication And Meta-analysis and the FinnGen (for T2DM).Main methodsIndividual Cochran's Q statistic was applied to remove the pleiotropic instruments, global Q statistics and MR-Egger regression were adopted to test for the global heterogeneity and horizontal pleiotropy of the screened instruments, respectively. Two T2DM cohorts were selected to analyze their associations with sleep traits. A modified inverse variance weighted (IVW) estimate was performed to combine the ratio estimators from each instrument and acquire the causal estimate, alternative methods including IVW with first-order weights, simple and weighted median estimations, and MR-Egger regression were conducted as sensitivity analyses, to ensure the robustness and solidity of the findings.ResultsTwo-sample MR supported findings for an adverse effect of genetically predicted insomnia on T2DM risk (odds ratio [OR] = 1.14, 95% confidence interval [CI]: 1.09-1.19, p = 1.29E-08) at the Bonferroni-adjusted level of significance (p < 0.005). We further investigated the causal role of T2DM on insomnia but obtained a non-significant estimation. There was also little evidence for the causal effect of other sleep-related measures on T2DM. Results were largely consistent when leveraging two different T2DM cohorts, and were robust among various sensitivity analyses.ConclusionFindings provide significant evidence for an adverse effect of insomnia on T2DM risk. The study extends fundamental knowledge to further understanding of the pathophysiological mechanisms of T2DM, and points out the non-negligible role of insomnia on epidemiologic intervention and clinical therapeutics of T2DM.
| S-EPMC7770175 | biostudies-literature
Project description:BACKGROUND:Short and long sleep duration have been linked with poorer cognitive outcomes, but it remains unclear whether these associations are causal. METHODS:We conducted the first Mendelian randomization (MR) study with 77 single-nucleotide polymorphisms (SNPs) for sleep duration using individual-participant data from the UK Biobank cohort (N?=?395?803) and summary statistics from the International Genomics of Alzheimer's Project (N cases/controls?=?17?008/37?154) to investigate the potential impact of sleep duration on cognitive outcomes. RESULTS:Linear MR suggested that each additional hour/day of sleep was associated with 1% [95% confidence interval (CI)?=?0-2%; P?=?0.008] slower reaction time and 3% more errors in visual-memory test (95% CI?=?0-6%; P?=?0.05). There was little evidence to support associations of increased sleep duration with decline in visual memory [odds ratio (OR) per additional hour/day of sleep?=?1.10 (95% CI?=?0.76-1.57); P?=?0.62], decline in reaction time [OR?=?1.28 (95% CI?=?0.49-3.35); P?=?0.61], all-cause dementia [OR?=?1.19 (95% CI?=?0.65-2.19); P?=?0.57] or Alzheimer's disease risk [OR?=?0.89 (95% CI?=?0.67-1.18); P?=?0.41]. Non-linear MR suggested that both short and long sleep duration were associated with poorer visual memory (P for non-linearity?=?3.44e-9) and reaction time (P for non-linearity?=?6.66e-16). CONCLUSIONS:Linear increase in sleep duration has a small negative effect on reaction time and visual memory, but the true association might be non-linear, with evidence of associations for both short and long sleep duration. These findings suggest that sleep duration may represent a potential causal pathway for cognition.
| S-EPMC6659373 | biostudies-literature
Project description:Objective:To investigate whether overall obesity (as measured by BMI) and abdominal obesity (as measured by waist-to-hip ratio adjusted for BMI) are associated with gout risk and serum urate concentrations using Mendelian randomization. Methods:Single nucleotide polymorphisms associated with BMI (n = 97) and waist-to-hip ratio adjusted for BMI (n = 49) were analysed for association with gout risk in 2115 gout cases and 67 259 controls, and with serum urate concentrations in 110 347 individuals from the Global Urate Genetics Consortium. Results:Genetically higher BMI, but not waist-to-hip ratio adjusted for BMI, was positively associated with risk of gout and serum urate concentrations. Each standard deviation (about 4.6 kg/m2) increase in genetically predicted BMI was associated with an odds ratio of gout of 2.24 (95% CI 1.70, 2.95; P = 8.4 × 10-9) and with a 0.30 mg/dl (95% CI 0.25, 0.35; P = 1.6 × 10-36) increase in serum urate concentrations. Conclusion:These findings provide support that overall obesity may be a risk factor for gout and is associated with higher serum urate concentrations.
| S-EPMC6697177 | biostudies-literature