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: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:AimsPrevious studies investigated the associations between sleep traits and cardiac diseases, but the evidence for the causal inferences was unclear. This study aimed to explore the causal relationship between sleep and cardiac diseases by virtue of Mendelian randomization (MR).Methods and resultsSummary-level data for exposure variables (sleep duration, chronotype, and insomnia) and outcome variables (ischaemic heart disease, atrial fibrillation, myocardial infarction, and heart failure) were derived from UK Biobank. Data from the FinnGen consortium was used as a robustness check. In MR analysis, the inverse variance weighted (IVW) method was applied to infer causality between exposure and outcome. MR-Egger regression was used to identify pleiotropy, and MR-PRESSO outlier test was used to remove the pleiotropy of the genetic instruments. Based on UK Biobank, MR analysis suggested that sleep duration was weakly associated with atrial fibrillation (OR = 0.9999, 95% CI: 0.9998-0.9999) and ischaemic heart disease (OR = 0.9997, 95% CI: 0.9995-0.9998). Insomnia was associated with ischaemic heart disease (OR = 1.0117, 95% CI: 1.0051-1.0183) and myocardial infarction (OR = 1.0049, 95% CI: 1.0019-1.0079). No associations were found between chronotype and cardiac diseases (P > 0.05). We did not find pleiotropy except for insomnia with ischaemic heart disease and myocardial infarction using MR-Egger regression, and MR-PRESSO analysis consistent with IVW. Finally, we obtained the same direction as with UK Biobank using the FinnGen data.ConclusionsSleep duration and insomnia might be the potential causal risk factors of cardiac diseases. As the OR was small, these associations are probably not clinically relevant. Further validation studies are needed.
| S-EPMC9715768 | biostudies-literature
Project description:BackgroundEmerging evidence suggests bidirectional causal relationships between sleep disturbance and psychiatric disorders, but the underlying mechanisms remain unclear. Understanding the bidirectional causality between sleep traits and brain imaging-derived phenotypes (IDPs) will help elucidate the mechanisms. Although previous studies have identified a range of structural differences in the brains of individuals with sleep disorders, it is still uncertain whether grey matter (GM) volume alterations precede or rather follow from the development of sleep disorders.ResultsAfter Bonferroni correction, the forward MR analysis showed that insomnia complaint remained positively associated with the surface area (SA) of medial orbitofrontal cortex (β, 0.26; 95% CI, 0.15-0.37; P = 5.27 × 10-6). In the inverse MR analysis, higher global cortical SA predisposed individuals less prone to suffering insomnia complaint (OR, 0.89; 95%CI, 0.85-0.94; P = 1.51 × 10-5) and short sleep (≤ 6 h; OR, 0.98; 95%CI, 0.97-0.99; P = 1.51 × 10-5), while higher SA in posterior cingulate cortex resulted in a vulnerability to shorter sleep durations (β, - 0.09; 95%CI, - 0.13 to - 0.05; P = 1.21 × 10-5).ConclusionsSleep habits not only result from but also contribute to alterations in brain structure, which may shed light on the possible mechanisms linking sleep behaviours with neuropsychiatric disorders, and offer new strategies for prevention and intervention in psychiatric disorders and sleep disturbance.
| S-EPMC10544625 | biostudies-literature
Project description:ObjectiveThe aim of this study was to systematically evaluate the direction of any potential causal effect between sleep and adiposity traits.MethodsTwo-sample Mendelian randomization was used to assess the association of genetically predicted sleep traits with adiposity and vice versa. Using data from UK Biobank and 23andMe, the sleep traits explored were morning preference (chronotype; N = 697,828), insomnia (N = 1,331,010), sleep duration (N = 446,118), napping (N = 452,633), and daytime sleepiness (N = 452,071). Using data from the Genetic Investigation of ANthropometric Traits (GIANT) and Early Growth Genetics (EGG) consortia, the adiposity traits explored were adult BMI, hip circumference (HC), waist circumference (WC), waist-hip ratio (WHR; N = 322,154), and childhood BMI (N = 35,668).ResultsThis study found evidence that insomnia symptoms increased mean WC, BMI, and WHR (difference in means, WC = 0.39 SD [95% CI: 0.13-0.64], BMI = 0.47 SD [95% CI: 0.22-0.73], and WHR = 0.34 SD [95% CI: 0.16-0.52]). Napping increased mean WHR (0.23 SD [95% CI: 0.08-0.39]). Higher HC, WC, and adult BMI increased odds of daytime sleepiness (HC = 0.02 SD [95% CI: 0.01-0.04], WC = 0.04 SD [95% CI: 0.01-0.06], and BMI 0.02 SD [95% CI: 0.00-0.04]). This study also found that higher mean childhood BMI resulted in lower odds of napping (-0.01 SD [95% CI: 0.02-0.00]).ConclusionsThe effects of insomnia on adiposity and of adiposity on daytime sleepiness suggest that poor sleep and weight gain may contribute to a feedback loop that could be detrimental to overall health.
| S-EPMC10946465 | biostudies-literature
Project description:BackgroundObservational studies reported an association between psoriasis and risk of lung cancer. However, whether psoriasis is causally associated with lung cancer is unclear.MethodsGenetic summary data of psoriasis were retrieved from two independent genome-wide association studies (GWAS). Genetic information of lung cancer was retrieved from GWAS of International Lung Cancer Consortium. A set of quality control steps were conducted to select instrumental tools. We performed two independent two-sample Mendelian randomization (MR) analyses and a meta-analysis based on the two independent MR estimates to assess the causal relationship between psoriasis and lung cancer (LUCA) as well as its subtypes, squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD).ResultsBetween-SNP heterogeneity was present for most MR analyses, whereas horizontal pleiotropy was not detected for all MR analyses. Multiplicative random-effect inverse variance weighted (IVW-MRE) method was therefore selected as the primary MR approach. Both IVW-MRE estimates from the two independent MR analyses suggested that there was no significant causal relationship between psoriasis and LUCA as well as its histological subtypes. Sensitivity analyses using other four MR methods gave similar results. Meta-analysis of the two IVW-MRE derived MR estimates yielded an odds ratio (OR) of 1.00 (95% CI 0.95-1.06) for LUCA, 1.01 (95% CI 0.93-1.08) for LUSC, and 0.97 (95% CI 0.90-1.06) for LUAD.ConclusionOur results do not support a genetic association between psoriasis and lung cancer and its subtypes. More population-based and experimental studies are warranted to further dissect the complex correlation between psoriasis and lung cancer.
| S-EPMC9814449 | biostudies-literature
Project description:BackgroundUnhealthy 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.MethodsGenome-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.ResultsThe 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.ConclusionOur 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.
| S-EPMC11296273 | biostudies-literature
Project description:ObjectiveThis study aimed to investigate the causal associations between several liver traits (liver iron content, percent liver fat, alanine transaminase levels, and liver volume) and colorectal cancer (CRC) risk using a Mendelian randomization (MR) approach to improve our understanding of the disease and its management.MethodsGenetic variants were used as instrumental variables, extracted from genome-wide association studies (GWAS) datasets of liver traits and CRC. The Two-Sample MR package in R was used to conduct inverse variance weighted (IVW), MR Egger, Maximum likelihood, Weighted median, and Inverse variance weighted (multiplicative random effects) MR approaches to generate overall estimates of the effect. MR analysis was conducted with Benjamini-Hochberg method-corrected P values to account for multiple testing (P < 0.013). MR-PRESSO was used to identify and remove outlier genetic variants in Mendelian randomization (MR) analysis. The MR Steiger test was used to assess the validity of the assumption that exposure causes outcomes. Leave-one-out validation, pleiotropy, and heterogeneity testing were also conducted to ensure the reliability of the results. Multivariable MR was utilized for validation of our findings using the IVW method while also adjusting for potential confounding or pleiotropy bias.ResultsThe MR analysis suggested a causal effect between liver volume and a reduced risk of CRC (OR 0.60; 95% CI, 0.44-0.82; P = 0.0010) but did not provide evidence for causal effects of liver iron content, percent liver fat, or liver alanine transaminase levels. The MR-PRESSO method did not identify any outliers, and the MR Steiger test confirmed that the causal direction of the analysis results was correct in the Mendelian randomization analysis. MR results were consistent with heterogeneity and pleiotropy analyses, and leave-one-out analysis demonstrated the overall values obtained were consistent with estimates obtained when all available SNPs were included in the analysis. Multivariable MR was utilized for validation of our findings using the IVW method while also adjusting for potential confounding or pleiotropy bias.ConclusionThe study provides tentative evidence for a causal role of liver volume in CRC, while genetically predicted levels of liver iron content, percent liver fat, and liver alanine transaminase levels were not associated with CRC risk. The findings may inform the development of targeted therapeutic interventions for colorectal liver metastasis (CRLM) patients, and the study highlights the importance of MR as a powerful epidemiological tool for investigating causal associations between exposures and outcomes.
| S-EPMC10699049 | 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-literature
Project description:BackgroundThe two geriatric diseases, sarcopenia and cardiovascular disease (CVD), often coexist, yet the causal relationship is unclear. However, few studies focus on the effect of muscle mass on CVD. This comprehensive study is dedicated to unearthing the potential connection between sarcopenia-related traits and CVD at the genetic level.MethodA two-sample bi-directional Mendelian randomization (MR) study was conducted. In the first stage, we performed MR analysis regarding coronary heart disease (CHD), stroke, and myocardial infarction (MI) as exposure factors to reveal their effect on appendicular lean mass (ALM) and hand grip strength. In the second stage, we reverse the position of exposures and outcomes. The inverse variance weighted (IVW) method was used as the primary approach to reveal the potential causation between the exposure and outcome.ResultsThe results of the IVW method revealed a negative causal effect of ALM on CHD (OR = 0.848, 95% CI = 0.804 to 0.894, p = 8.200E-10), stroke (OR = 0.931, 95% CI = 0.890 to 0.975, p = 2.220E-03), and MI (OR = 0.810, 95% CI = 0.694 to 0.901, p = 1.266E-13). Additionally, the left-hand grip strength is a significant protective factor for CHD (OR = 0.737, 95% CI = 0.601 to 0.904, p = 3.353E-03) and MI (OR = 0.631, 95% CI = 0.515 to 0.765, p = 2.575E-06), but is not causally linked to the stroke (OR = 0.971, 95% CI =0.829 to 1.139, p = 0.720). Meanwhile, the same conclusion about the effect of right-hand grip strength on CHD (OR = 0.681, 95% CI = 0.558 to 0.832, p = 1.702E-05), MI (OR = 0.634, 95% CI = 0.518 to 0.776, p = 9.069E-06), and stroke (OR = 1.041, 95% CI = 0.896 to 1.209, p = 0.604) was obtained. However, no significant causal effect of CVD (CHD, stroke, MI) on sarcopenia-related traits (ALM, handgrip strength) was found.ConclusionThere is a unidirectional causal relationship between sarcopenia and CVD. The loss of muscle mass and strength has a significant causal role in promoting the occurrence and development of CVD, providing a reference for the prevention and treatment of comorbidities in older people.
| S-EPMC10613058 | biostudies-literature