Multidimensional sleep trait, which is related to circadian rhythms closely, affects some cancers predominantly, while the relationship between sleep and lung cancer is rarely illustrated. We aimed to investigate whether sleep is causally associated with risk of lung cancer, through a two-sample Mendelian randomization study. The main analysis used publicly available GWAS summary data from two large consortia (UK Biobank and International Lung Cancer Consortium). Two-sample Mendelian randomization (MR) analysis was used to examine whether chronotype, getting up in the morning, sleep duration, nap during the day, or sleeplessness was causally associated with the risk of lung cancer. Additionally, multivariate MR analysis was also conducted to estimate the direct effects between sleep traits and lung cancer risks independent of smoking status including pack years of smoking or current tobacco smoking. There was no evidence of causal association between chronotype, getting up in the morning, or nap during the day and lung cancer. Sleeplessness was associated with higher risk of lung adenocarcinoma (odds ratio 5.75, 95% confidence intervals 2.12-15.65), while sleep duration played a protective role in lung cancer (0.46, 0.26-0.83). In multivariate MR analysis, sleeplessness and sleep duration remained to have similar results. In conclusion, we found robust evidence for effect of sleeplessness on lung adenocarcinoma risk and inconsistent evidence for a protective effect of sleep duration on lung cancer risk.
Lung cancer, which accounts for 11.6% of all newly diagnosed cancer cases and 18.4% of cancer-related deaths [
Many studies have shown that sleep plays an important role in cancer by affecting circadian rhythms, especially in breast cancer [
Mendelian randomization (MR) can use genetic variants that are associated robustly with exposure as instrumental variables to evaluate causal effects between the modifiable risk factors and the diseases [
Furthermore, sleep is a multidimensional concept, including chronotype, getting up in the morning, sleep duration, nap during the day, and sleeplessness. Therefore, the exploration of association between sleep and lung cancer should not be finite to sleep duration. Based on the limited evidence for effects of sleep traits on lung cancer and the significant association between unfavorable sleep duration and lung function [
Our exposure data were extracted from the UK Biobank, a large cohort study with deep genetic and phenotypic data collected on more than 500,000 individuals from across the United Kingdom [
GWAS summary data of lung cancer were extracted from the International Lung Cancer Consortium (ILCCO) [
The associations between exposure (sleeping traits) and outcome (lung cancer) were calculated with two-sample MR analysis [
To further detect causal estimates for potential violation of the MR assumptions, we also performed RadialMR [
Considering that smoking is recognized as the common risk factor for lung cancer, we conducted IVW multivariable MR to estimate the effect of each sleeping traits after adjusting for pack years of smoking or current tobacco smoking status. To further eliminate the interaction effect between different exposures and avoid the multicollinearity, we also performed IVW multivariable MR after applying LASSO feature selection to identify effects of sleep duration, nap during the day, and sleeplessness for lung cancer. All analyses were replicated on squamous cell cancer and adenocarcinoma.
MR analyses were performed using the R package “TwoSampleMR” (version 0.5.5) in R (version 4.0.3).
Table
Characteristics of sleep traits in UK Biobank and lung cancer consortium.
Exposure | Consortium | Sample size | Population |
---|---|---|---|
Chronotype | MRC-IEU | 413343 | European |
Getting up in the morning | MRC-IEU | 461658 | European |
Sleep duration | MRC-IEU | 460099 | European |
Nap during the day | MRC-IEU | 462400 | European |
Sleeplessness/insomnia | MRC-IEU | 462341 | European |
Current tobacco smoking | MRC-IEU | 462434 | European |
Pack years of smoking | MRC-IEU | 142387 | European |
Outcomes | Consortium | Cases/control | Sample size | Population |
---|---|---|---|---|
Lung cancer | ILCCO | 11348/15861 | 27209 | European |
Squamous cell cancer | ILCCO | 3275/15038 | 18313 | European |
Adenocarcinoma | ILCCO | 3442/14894 | 18336 | European |
We found adverse effects of sleeplessness (OR 2.53, 95% CI 1.25-5.12) and protective effects of sleep duration (0.46, 0.26-0.83) on lung cancer risk. However, the effects of chronotype, getting up in the morning, and nap during the day were not statistically significant (0.98, 0.70-1.16 for chronotype; 0.99, 0.62-1.60 for getting up in the morning; 1.37, 0.77-2.24 for sleep duration).
All MR results were not statistically significant (0.87, 0.99-3.79 for chronotype; 1.08, 0.55-2.12 for getting up in the morning; 0.46, 0.18-1.18 for sleep duration; 1.07, 0.48-2.35 for nap during the day; and 2.46, 0.83-7.34 for sleeplessness).
We observed a strongly hazardous effect of sleeplessness (5.75, 2.12-15.65) on the risk of lung adenocarcinoma, while little evidence of causal effects of other sleeping traits was obtained (0.85, 0.61-1.2 for chronotype; 2.21, 0.81-5.99 for getting up in the morning; 0.62, 0.29-1.31 for sleep duration; and 2.04, 0.66-6.35 for nap during the day).
In multivariate MR analysis, sleeplessness still showed an adverse effect on lung adenocarcinoma adjusted for pack years of smoking (4.55, 1.23-16.87) or current tobacco smoking (4.99, 1.79-13.90), while sleep duration showed a protective influence on lung cancer adjusted for these two smoking statuses (0.47, 0.25-0.90, and 0.53, 0.31-0.90, respectively). Figure
Flow diagram of Mendelian randomization.
Two-sample Mendelian randomization estimations showing the effect of sleep traits on cancer using the IVW method.
Exposure | Method | OR (95% CI) | |
---|---|---|---|
Chronotype | Inverse variance weighted | 0.90 (0.70-1.16) | 0.42 |
MVMR adjusted for pack years for smoking | 0.90 (0.68-1.19) | 0.46 | |
MVMR adjusted for current tobacco smoking | 0.92 (0.71-1.18) | 0.50 | |
Getting up in the morning | Inverse variance weighted | 0.99 (0.62-1.60) | 0.98 |
MVMR adjusted for pack years for smoking | 1.18 (0.66-2.12) | 0.57 | |
MVMR adjusted for current tobacco smoking | 1.30 (0.80-2.10) | 0.29 | |
Sleep duration | Inverse variance weighted | 0.46 (0.26-0.83) | 0.01 |
MVMR adjusted for pack years for smoking | 0.47 (0.25-0.90) | 0.02 | |
MVMR adjusted for current tobacco smoking | 0.53 (0.31-0.90) | 0.02 | |
Nap during the day | Inverse variance weighted | 1.37 (0.77-2.44) | 0.29 |
MVMR adjusted for pack years for smoking | 1.04 (0.53-2.01) | 0.92 | |
MVMR adjusted for current tobacco smoking | 1.17 (0.66-2.07) | 0.60 | |
Sleeplessness | Inverse variance weighted | 2.53 (1.25-5.12) | 0.01 |
MVMR adjusted for pack years for smoking | 1.64 (0.59-4.59) | 0.34 | |
MVMR adjusted for current tobacco smoking | 1.94 (0.99-3.79) | 0.05 | |
Chronotype | Inverse variance weighted | 0.87 (0.59-1.27) | 0.46 |
MVMR adjusted for pack years for smoking | 0.83 (0.57-1.21) | 0.33 | |
MVMR adjusted for current tobacco smoking | 0.86 (0.59-1.24) | 0.42 | |
Getting up in the morning | Inverse variance weighted | 1.08 (0.55-2.12) | 0.82 |
MVMR adjusted for pack years for smoking | 1.20 (0.59-2.43) | 0.61 | |
MVMR adjusted for current tobacco smoking | 1.20 (0.60-2.38) | 0.61 | |
Sleep duration | Inverse variance weighted | 0.46 (0.18-1.18) | 0.11 |
MVMR adjusted for pack years for smoking | 0.50 (0.21-1.19) | 0.12 | |
MVMR adjusted for current tobacco smoking | 0.57 (0.25-1.30) | 0.18 | |
Nap during the day | Inverse variance weighted | 1.07 (0.48-2.35) | 0.87 |
MVMR adjusted for pack years for smoking | 0.81 (0.36-1.80) | 0.60 | |
MVMR adjusted for current tobacco smoking | 0.86 (0.39-1.88) | 0.70 | |
Sleeplessness | Inverse variance weighted | 2.46 (0.83-7.34) | 0.11 |
MVMR adjusted for pack years for smoking | 1.36 (0.43-4.24) | 0.60 | |
MVMR adjusted for current tobacco smoking | 1.76 (0.70-4.41) | 0.23 | |
Chronotype | Inverse variance weighted | 0.85 (0.61-1.20) | 0.37 |
MVMR adjusted for pack years for smoking | 0.83 (0.57-1.20) | 0.32 | |
MVMR adjusted for current tobacco smoking | 0.86 (0.60-1.22) | 0.39 | |
Getting up in the morning | Inverse variance weighted | 1.60 (0.73-3.49) | 0.24 |
MVMR adjusted for pack years for smoking | 2.01 (0.89-4.55) | 0.10 | |
MVMR adjusted for current tobacco smoking | 2.03 (0.95-4.33) | 0.07 | |
Sleep duration | Inverse variance weighted | 0.62 (0.29-1.31) | 0.21 |
MVMR adjusted for pack years for smoking | 0.63 (0.28-1.43) | 0.27 | |
MVMR adjusted for current tobacco smoking | 0.70 (0.34-1.43) | 0.32 | |
Nap during the day | Inverse variance weighted | 1.67 (0.72-3.87) | 0.23 |
MVMR adjusted for pack years for smoking | 1.20 (0.48-2.99) | 0.70 | |
MVMR adjusted for current tobacco smoking | 1.56 (0.67-3.65) | 0.30 | |
Sleeplessness | Inverse variance weighted | 5.75 (2.12-15.65) | <0.01 |
MVMR adjusted for pack years for smoking | 4.55 (1.23-16.87) | 0.02 | |
MVMR adjusted for current tobacco smoking | 4.99 (1.79-13.90) | <0.01 |
OR: odds ratios; 95% CI: 95% confidence interval; IVW: inverse variants weighted; MVMR: multivariable variant Mendelian randomization.
Forest plot of Mendelian randomization (MR) estimates for association between sleep traits and cancer risk. OR: odds ratios; 95% CI: 95% confidence interval; IVW: inverse variants weighted; MVMR: multivariable variant Mendelian randomization.
Through the LASSO feature selection function, only relevant features and instruments were retained. The results of MVMR performed on remaining SNP data were also similar with univariate analysis (in Supplementary Table
Other results estimated by MR Egger, weighted median, and weighted mode are available in Supplementary Table
In this study, we explored the causal effects of five sleep traits including chronotype, getting up in the morning, sleep duration, nap during the day, and sleeplessness on lung cancer, squamous cell lung cancer, and lung adenocarcinoma. Insomnia was causally associated with a higher risk of lung adenocarcinoma, while sleep duration showed a protective effect on lung cancer risk.
Previous epidemiological studies have just focused on the relationship between sleep duration and lung cancer. Some studies have reported the U-shaped association [
In addition to sleep duration, other sleep traits also reflect sleep conditions; a comprehensive evaluation should contain the impacts of chronotype, getting up in the morning, and sleeplessness on lung cancer. Only Xie and his colleagues [
The mechanisms underlying these associations are poorly understood. One possible pathway is that sleep disturbances may lead to chronic lung disease through circadian rhythm disruption [
To our knowledge, this study is the first to explore connections between sleep traits and lung cancer risks at the level of genes. Although random control trial (RCT) can provide the most compelling evidence, it involves many ethical issues and costs much money. For observation studies, despite these results from observed studies that were adjusted by other relative variables, undetected biases could not be ignored. Therefore, the results provided by MR are the most convincing. Bias due to confounding and reverse sources could be decreased by MR. To minimize the potential violation of the MR assumption, we also conducted serials of sensitivity analysis and detected any outliers by RadialMR analysis. We also conducted multivariable MR to adjust for smoking, the most common and important risk factor of lung cancer.
Several limitations should be considered in our study. First, our study was based on the European population. Thus, whether our study could be generalizable to other populations requires further investigations. Second, the summary data used in our MR analyses were not stratified by gender or smoking. Finally, all sleep traits were self-reported. Thus, it is possible to lead to misclassification of exposure.
In conclusion, MR analysis provides stronger evidence for the causal effect of sleeplessness on lung adenocarcinoma and highlights the importance of sleep duration in lung cancer incidence. Although other sleep traits did not show protective or adverse effects on lung cancer, these findings imply that we still need to pay attention to sleep health to mitigate the risk of incident lung cancer. Our results may further emphasize the importance of enough sleep for health. Further studies are needed to illustrate the association between sleep traits and lung cancer in females and nonsmokers.
Our data was from the UK Biobank and the International Lung Cancer Consortium, the two open-access datasets (
The authors declare no financial or commercial conflict of interest.
Jie Wang and Haibo Tang contributed equally to this work.
This work was funded by the following grants and associations: National Natural Science Foundation of China (81974465 and 81900199), Hunan province natural science funds for Excellent Young Scholars (2019JJ30043), and the recruitment program for Huxiang talents (2019RS1009).
Supplementary Table 1: two-sample Mendelian randomization estimations showing the effect of sleep traits on cancer using the MR Egger, weighted median, and weighted mode method. Supplementary Table 2: sensitivity analysis performed by Egger regression intercept and heterogeneity test. Supplementary Table 3: SNPs of sleep traits extracted from UK Biobank with statistically significant threshold [