Association between sleep traits and risk of colorectal cancer: a bidirectional Mendelian randomization study

Introduction

Cancer is a global public health problem and one of the leading causes of death worldwide (1). The global cancer burden is increasing as populations grow and malignancies develop at younger ages (2). Studies (3-7) have linked cancer to smoking, alcohol consumption, obesity, diabetes, reduced physical activity, irregular schedules, and other lifestyle factors. Reasonable sleep time arrangements are a part of a healthy lifestyle. However, inadequate (<7 hours) sleep, staying up late at night, insomnia, difficulty in getting up in the morning, and other poor sleep habits are becoming increasingly common in the general public (8,9).

Sleep disorders have been shown to increase the risk of diseases such as coronary heart disease, ischaemic stroke, and Parkinson’s disease (10-12). In addition, some studies (13-15) have found that sleep disorders can increase the risk of breast, liver, and prostate cancers, as well as other malignant tumors. Although some evidence has found that an appropriate amount of sleep per day, less frequent insomnia, absence of snoring, and less frequent daytime sleepiness are associated with a reduced risk of colorectal cancer (CRC) (16-18), these findings are largely from observational studies, which are easily affected by selection and information biases.

Mendelian randomization (MR) analysis is a statistical method that utilizes a large genetic database to analyze the causal association between exposure factors and outcome indicators at the gene level (19). Alleles with genetic variations are used as instrumental variables (IVs) to mitigate measurement errors and biases. IVs used in MR studies must satisfy three conditions (20): (I) single nucleotide polymorphisms (SNPs) must be closely related to sleep traits; (II) SNPs must not be associated with confounders; and (III) SNPs must influence CRC through sleep traits and must not be directly associated. Therefore, the results are more credible when MR analysis is used to investigate causal associations between diseases. Two-sample MR (TSMR) utilizes data from two independent genome-wide association study (GWAS) samples to compute the effect size between exposure traits and outcomes (20). This study aimed to analyze the potential causal association between sleep traits and CRC through MR analysis, utilizing data on sleep traits and CRC data from large published genetic studies. We present this article in accordance with the STROBE-MR reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-11/rc).

Methods

Study design

We conducted a bidirectional MR analysis to explore the causal relationship between sleep traits and CRC. Multivariable MR (MVMR) analysis was employed to account for the causal effect of high body mass index (BMI), a known risk factor for CRC (21), and to increase confidence in the findings. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Since the study was conducted using publicly available data, no ethical approval or informed consent was required.

GWAS data on sleep traits

In this study, seven sleep traits were identified as exposure factors: sleep duration, ease of getting up in the morning, morning chronotype, daytime napping, insomnia symptoms, snoring, and daytime dozing. The data were obtained from the Independent Education Union (IEU) open GWAS and primarily from the UK Biobank between 2006 and 2010, involving a study of 337,000 unrelated individuals aged 40–69 years (22). Sleep duration was determined by asking individuals about their daily hours of sleep, with 7–9 hours considered appropriate. Their genetic associations were derived from a GWAS of 335,410 samples from the UK Biobank. The ease of getting up in the morning was mainly determined through self-assessment. Aggregated GWAS data from 336,501 individuals in the UK Biobank database revealed a genetic association for an early rise. Chronotype refers to a person’s tendency to sleep at particular times, with morning chronotype indicating someone who is identified as a “morning asleep” person. A GWAS association search of 301,143 samples published in the UK Biobank provided estimates of the genetic associations of chronotypes. People who sleep inadequately at night tend to nap during the day, mostly during the middle of the day. The genetic association of daytime napping was retrieved from a GWAS of 337,074 samples from the UK Biobank. Insomnia is characterized by difficulty in falling asleep or waking at night. A GWAS association search of 336,965 samples published in the UK Biobank provided estimates of genetic associations for insomnia. Snoring was assessed based on snoring complaints from partners or relatives. The genetic association of snoring was retrieved from a GWAS of 314,449 samples from the UK Biobank. Daytime dozing refers to a state in which a person falls asleep for a short time due to excessive fatigue or insufficient rest. Aggregated GWAS data from 336,082 individuals in the UK Biobank database revealed a genetic link with daytime dozing (Table 1).

We identified SNPs strongly associated with sleep traits to generate statistically significant thresholds (P<5×10⁻⁸), eliminated linkage disequilibrium (LD) (23) (r²<0.001; LD distance >10,000 kb), and removed palindromic SNP to ensure the independence of IVs. To mitigate the bias caused by weak IVs, we assessed the R² for each IV’s exposure interpretation. Additionally, the F-statistic was calculated to determine the strength of the relationship between the SNPs and sleep traits (24). It is generally believed that SNPs with F>10 may be closely associated with sleep traits (25).

GWAS data on CRC

Genetic outcome associations for CRC, colon cancer, and rectal malignancies, as defined by the International Statistical Classification of Diseases, were derived from publicly available GWAS summary statistics in the UK Biobank database (https://gwas.mrcieu.ac.uk/). We obtained three datasets, including 5,657 patients with CRC and 372,016 controls, 2,226 patients with malignant neoplasms of the colon and 358,968 controls, and 1,170 patients with malignant neoplasms of the rectum and 360,024 controls (Table 1).

Statistical analysis

TSMR analysis

The association between sleep traits and CRC was assessed using TSMR analysis (26). The inverse variance weighted (IVW) method was employed to obtain an unbiased estimate of the causal association between exposure and outcome measures, mitigating horizontal pleiotropic (27). The same procedure was applied to analyze its subtypes (colon and rectal cancer). Results are presented as odds ratios (ORs) and 95% confidence intervals (CIs). To assess the sensitivity of the results, MR-Egger regression (28) and weighted medians were utilized to evaluate causality.

MVMR analysis

Considering that BMI is a common risk factor for CRC, we performed an IVW MVMR assessment to adjust for the confounding effects of BMI. Genetic IVs for BMI were obtained using the IEU Open GWAS of 337,074 samples from the Anthropometric Traits Genetic Survey Consortium. MVMR analysis was employed to ascertain whether a true causal association exists between sleep traits and CRC (29). All the analyses were performed for colon and rectal cancers.

Sensitivity analysis

We performed the following sensitivity analysis to determine whether SNPs influence CRC risk through sleep traits.

Cochran’s Q test

This test was used to test for differences between IVs in the presence of non-specific SNPs. Heterogeneity analysis was used to determine the effect of non-specific SNPs on the results (30). In cases of IV heterogeneity, the IVW aspect of the random effects model was employed to estimate causality.

Pleiotropy test

MR-Egger regression was utilized to assess whether there is a non-zero intercept in the regression of the causal estimate on its precision. Horizontal pleiotropy can distort MR tests, leading to inaccurate causal estimates and potentially false positive causal associations (31).

Leave-one-out sensitivity test

This test mainly calculates the residual MR results after removing each IV individually. Significant differences between the estimated MR results of other IVs and the total results after removal of the IV indicate sensitivity to that particular IV.

MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO)

To identify outliers in the MR analysis and re-analyze them after removal, we utilized the MR-PERSSO package in R for analysis using improved second-order weights.

All statistical analyses were conducted using R packages “TwoSampleMR (version 0.5.7)”, “Forestposter (version 1.1.0)”, and “MR-PRESSO (version 1.0)” in R software (version 4.2.1).

Results

We conducted bidirectional MR analyses using seven sleep traits and three CRC outcomes. Figure 1 illustrates the study process. Each SNP was extracted from different sleep traits, and its F-statistics are shown in Table S1.

Figure 1 Flow chart of MR. MR, Mendelian randomization; BMI, body mass index.

Casual association between sleep traits and CRC

Appropriate sleep duration (OR =0.989; 95% CI: 0.980, 0.998; P=0.01) and ease of getting up in the morning (OR =0.992; 95% CI: 0.984, 0.999; P=0.03) were protective factors in patients with CRC. The MVMR analysis produced the same result (P=0.04 for sleep duration and P=0.04 for ease of getting up in the morning). Insomnia symptoms were a protective factor against CRC (OR =0.988; 95% CI: 0.978, 0.997; P=0.01). However, the MVMR outcome for insomnia symptoms was not statistically significant (OR =0.993; 95% CI: 0.980, 1.006; P=0.31). In contrast, snoring did not significantly affect the incidence of CRC in the TSMR group (OR =1.010; 95% CI: 0.994, 1.027; P=0.22). Nevertheless, the MVMR results indicated that snoring had a negative effect on CRC (OR =1.021; 95% CI: 1.002, 1.041; P=0.03) (Table 2, Figures 2,3A-3C). The effects of morning chronotype, daytime napping, and daytime dozing were not statistically significant (P=0.97, P=0.63, and P=0.75, respectively). The entire MR results are presented in Table S2.

Figure 2 Forest plot of MR estimates for association between sleep traits and CRC. Sleep duration refer to persons who sleep 7–9 hours per day. Chronotype refer to persons who tend to sleep more in the morning. Insomnia refers to persons who suffering from insomnia. OR, odds ratio; CI, confidence interval; IVW, inverse variants weighted; MR, Mendelian randomization; BMI, body mass index; CRC, colorectal cancer.

Figure 3 MR analysis of sleep traits on CRC. Scatter plot of CRC associations (Y-axis) against sleep traits (X-axis). (A) Scatter plot of sleep duration on CRC. (B) Scatter plot of getting up in the morning on CRC. (C) Scatter plot of snoring on CRC. (D) Scatter plot of getting up in the morning on colon cancer. (E) Scatter plot of morning chronotype on colon cancer. (F) Scatter plot of insomnia symptoms on rectal cancer. MR, Mendelian randomization; CRC, colorectal cancer.

Casual association between sleep traits and colon cancer

We observed protective effects of appropriate sleep duration (OR =0.993; 95% CI: 0.986, 1.000; P=0.04) and ease of getting up in the morning (OR =0.995; 95% CI: 0.989, 1.000; P=0.04) on CRC. However, MVMR analyses yielded different results, with the effect of appropriate sleep duration on CRC risk not being statistically significant (OR =0.994; 95% CI: 0.987, 1.002; P=0.13). Morning chronotype did not significantly alter the incidence of CRC in the TSMR group (OR =1.002; 95% CI: 1.000, 1.005; P=0.07). However, MVMR showed that the morning chronotype had a negative effect on CRC (OR =1.004; 95% CI: 1.000, 1.007; P=0.04) (Table 1, Figures 2,3D,3E). Additionally, the effects of daytime napping, insomnia symptoms, snoring, and daytime dozing were not statistically significant (P=0.66, P=0.24, P=0.62, and P=0.53, respectively). All MR results are summarised in Table S2.

Casual association between sleep traits and rectal cancer

The results indicated that insomnia symptoms did not significantly affect the incidence of rectal cancer in the TSMR analysis (OR =0.996; 95% CI: 0.991, 1.000; P=0.06). However, MVMR showed that insomnia symptoms were a protective factor against rectal cancer (OR =0.995; 95% CI: 0.990, 0.999; P=0.03) (Table 1, Figures 2,3F). Little evidence of causal effects of other sleep traits was observed for rectal cancer (P=0.13 for appropriate sleep duration, P=0.053 for ease of getting up in the morning, P=0.88 for morning chronotype, P=0.98 for daytime napping, P=0.93 for snoring, and P=0.18 for daytime dozing). The entire MR results of the correlational analysis are presented in Table S2.

Reverse MR analysis

In our reverse MR analysis of sleep traits in CRC, the IVW found no evidence to support a causal relationship between CRC and sleep traits (P=0.84 for sleep duration, P=0.58 for ease of getting up in the morning, P=0.81 for chronotype, P=0.52 for daytime napping, P=0.89 for insomnia, P=0.38 for snoring, and P=0.24 for daytime dozing) (Table S3).

Sensitivity analysis

Heterogeneity was observed in appropriate sleep duration (P=0.01), daytime napping (P=0.01), and daytime dozing (P=0.03) in the CRC and colon cancer analyses. Additionally, snoring (P=0.04) showed heterogeneity only in the colon cancer analysis. No heterogeneity was observed in other MR results. A random benefit model was used for exposures with high heterogeneity for the MR Analysis. However, there were no significant changes in the results after the exclusion of any SNP in the leave-one-out test. The MR-Egger intercept test did not reveal any evidence of horizontal pleiotropy. Detailed heterogeneity tests and pleiotropy results are presented in Table S4. Additionally, several outlier SNPs (rs4767550, rs1983336, rs2390669, and rs1846644) were identified when MR-PRESSO was used for the outlier test. After excluding the above outlier values, an MR analysis was performed, and the results showed no significant changes.

Discussion

This study evaluated the causal association between sleep traits (appropriate sleep duration, ease of getting up in the morning, morning chronotype, daytime napping, insomnia symptoms, snoring, and daytime dozing) and CRC using MR analysis. Our study revealed that appropriate sleep duration and ease of getting up in the morning are protective factors for CRC, while snoring is identified as an adverse factor for CRC. Moreover, ease of getting up in the morning is a protective factor against colon cancer, while morning chronotype is an adverse factor for colon cancer. Additionally, insomnia symptoms are protective factors for rectal cancer. However, no causal association was observed between daytime napping, daytime dozing, and CRC. These findings underscore the importance of considering sleep traits as modifiable risk factors for cancer. Promoting health awareness and adopting a healthy lifestyle may reduce the risk of CRC.

Epidemiological studies (31,32) have shown that sleep traits are risk factors for cancer, affecting tumor development. Haus et al. (33) found that reduced sleep quality may lead to reduced melatonin production. Melatonin is a human hormone produced by the pineal gland and has many functions, such as regulating circadian rhythms and increasing immunity. Hohor et al. (34) found that the levels of melatonin and its metabolites decline gradually when shift workers are exposed to light at night. As an anticancer agent, melatonin plays a crucial role in inhibiting malignant tumors, including tumor proliferation, metastasis, and angiogenesis (35,36).

Sleep is a key mechanism for maintaining optimal immune (37), cellular (38), metabolic (39), and endocrine (40) functions, with each neurophysiological dysfunction being associated with carcinogenic pathways. Moreover, sleep and rest disorders may affect innate and acquired immune capacity, increase reactive oxygen species, induce DNA damage, and disrupt metabolic function, consequently leading to the occurrence of tumors (34). In addition, people with some common carcinogenic factors, such as smoking, obesity, and a sedentary lifestyle, are more likely to develop sleep disorders, which also explains the higher incidence of tumors in this population (41).

Sleep traits also affect the occurrence of specific tumors through diverse mechanisms. For instance, repeated sleep disruption leads to an increase in the overall estrogen level in females (42), and heightened estrogen stimulation increases the risk of breast cancer. Males with sleep disorders tend to experience lower urinary tract symptoms (43), which can potentially promote the development of prostate cancer. Disorder in sleep rhythm leads to the downregulation of circadian genes, and disruption of the circadian rhythm of liver cells will impair the control of the central pacemaker, thereby facilitating the selective survival of cancer cells (44).

Our study indicates that ease of awakening in the morning is a protective factor against CRC, especially colon cancer. People who can easily get up early have better dietary habits. They tend to eat more fruits, whole grains, and other healthy foods for breakfast rather than indulging in sleeping late and immediately consuming greasy processed meat, beer, and coffee upon waking up (45). In addition, people who can easily get up early have a lower abundance of Alistipes and a higher abundance of Lachnospira in their intestinal flora (46). These enterobacteria hinder the development of CRC (47,48). Moreover, people who can easily get up early are more willing to exercise, and their incidence of obesity is lower (49). We also found that optimal sleep duration is a protective factor against CRC compared to sleep that is too short (<7 hours) or too long (>9 hours), which aligns with previous research (16,50). Adequate sleep can increase the adaptive immune response, while sleep disorders may induce immunosuppression, thereby favoring the dominance of cancer-stimulating cytokines in the body (51). Conversely, excessively long sleep duration is often indicative of frailty and may exacerbate inflammatory responses, increasing the risk of CRC (52). Furthermore, our MR analysis identified snoring as a risk factor for CRC, consistent with the findings of Zhang et al. (18). This association may be related to obstructive sleep apnoea syndrome, characterized by repeated sleep disruptions and intermittent hypoxemia. Intermittent hypoxemia can promote tumor cell growth cell proliferation by releasing pro-angiogenic mediators (53,54).

Our study found that insomnia symptoms are a protective factor against rectal cancer. Yoon et al.’s (55) large cohort study also reached the same conclusion, which may be attributed to the fact that patients with insomnia participate more in CRC screening (56). Early screening can be used to treat precancerous lesions in advance, thereby reducing the occurrence of rectal cancer. However, the genetic causes need to be explored further. Nevertheless, Chen et al. (17) came to a different conclusion, suggesting that insomnia increases the risk of CRC by 14%. This may be related to differences in the population composition, and the causal relationship may differ across age groups. Currently, there are a few studies on the causal relationship between insomnia and CRC (55,56), and further exploration of the causal relationship and influencing mechanisms is needed.

There are some limitations in this study. First, it relied on the European GWAS database of the UK Biobank, which may limit the generalizability of the findings to other ethnic groups, necessitating further validation. Second, this study utilized a pooled database of GWAS data, lacking original individual-level statistics, which may limit the analysis to genetic data only and not accounting for individual characteristics. Moreover, the causal relationship between sleep traits and CRC differs across age groups and sexes, and the study was unable to determine whether there is a dose-response relationship between sleep traits and CRC. Last, while several sleep traits showed significant associations with the risk of CRC, the OR values were small. Therefore, further large-scale MR analyses and basic biological experiments are warranted to verify the reliability of the results and elucidate their specific biological pathways.

Conclusions

Our study indicates that ease of awakening in the morning and appropriate sleep duration may serve as protective factors against CRC, especially in the context of colon cancer, while snoring may be an adverse factor for colon cancer. The findings from our MR analysis underscore the significance of healthy sleep in mitigating the risk of CRC. Future studies should further investigate the causal relationships between sleep traits and CRC across diverse populations and explore potential dose-response relationships. Additionally, examining specific biological pathways underlying these associations through large-scale analyses and biological experiments is warranted.

Acknowledgments

Genetic association estimates for exposures and outcomes were obtained from the UK Biobank study. The authors thank all investigators for sharing these data and Editage (https://www.editage.com/) for English language editing.

Funding: This research was supported by the Health Appropriate Technology Promotion Project of 2023 Chongqing (No. 2023jstg023).

Footnote

Reporting Checklist: The authors have completed the STROBE-MR reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-11/rc

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-11/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-11/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021;71:209-49. [Crossref] [PubMed]
2. The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 2022;400:563-91. [Crossref] [PubMed]
3. Gallagher EJ, LeRoith D. Obesity and Diabetes: The Increased Risk of Cancer and Cancer-Related Mortality. Physiol Rev 2015;95:727-48. [Crossref] [PubMed]
4. Alexandrov LB, Ju YS, Haase K, et al. Mutational signatures associated with tobacco smoking in human cancer. Science 2016;354:618-22. [Crossref] [PubMed]
5. Howell D, Oliver TK, Keller-Olaman S, et al. Sleep disturbance in adults with cancer: a systematic review of evidence for best practices in assessment and management for clinical practice. Ann Oncol 2014;25:791-800. [Crossref] [PubMed]
6. Bagnardi V, Rota M, Botteri E, et al. Light alcohol drinking and cancer: a meta-analysis. Ann Oncol 2013;24:301-8. [Crossref] [PubMed]
7. Wang Q, Zhou W. Roles and molecular mechanisms of physical exercise in cancer prevention and treatment. J Sport Health Sci 2021;10:201-10. [Crossref] [PubMed]
8. Caraballo C, Mahajan S, Valero-Elizondo J, et al. Evaluation of Temporal Trends in Racial and Ethnic Disparities in Sleep Duration Among US Adults, 2004-2018. JAMA Netw Open 2022;5:e226385. [Crossref] [PubMed]
9. Schermer EE, Engelfriet PM, Blokstra A, et al. Healthy lifestyle over the life course: Population trends and individual changes over 30 years of the Doetinchem Cohort Study. Front Public Health 2022;10:966155. [Crossref] [PubMed]
10. Daghlas I, Dashti HS, Lane J, et al. Sleep Duration and Myocardial Infarction. J Am Coll Cardiol 2019;74:1304-14. [Crossref] [PubMed]
11. Zhang Z, Wang M, Gill D, et al. Genetically Predicted Sleep Traits and Functional Outcome After Ischemic Stroke: A Mendelian Randomization Study. Neurology 2023;100:e1159-65. [Crossref] [PubMed]
12. Chen Y, Gao Y, Sun X, et al. Association between Sleep Factors and Parkinson's Disease: A Prospective Study Based on 409,923 UK Biobank Participants. Neuroepidemiology 2023;57:293-303. [Crossref] [PubMed]
13. Richmond RC, Anderson EL, Dashti HS, et al. Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study. BMJ 2019;365:l2327. [Crossref] [PubMed]
14. Yang X, Wang J, Wang H. Association between sleep traits and primary liver cancer: A Mendelian randomization analysis. Eur J Clin Invest 2023;53:e14002. [Crossref] [PubMed]
15. Sigurdardottir LG, Markt SC, Rider JR, et al. Urinary melatonin levels, sleep disruption, and risk of prostate cancer in elderly men. Eur Urol 2015;67:191-4. [Crossref] [PubMed]
16. Jiao L, Duan Z, Sangi-Haghpeykar H, et al. Sleep duration and incidence of colorectal cancer in postmenopausal women. Br J Cancer 2013;108:213-21. [Crossref] [PubMed]
17. Chen J, Chen N, Huang T, et al. Sleep pattern, healthy lifestyle and colorectal cancer incidence. Sci Rep 2022;12:18317. [Crossref] [PubMed]
18. Zhang X, Giovannucci EL, Wu K, et al. Associations of self-reported sleep duration and snoring with colorectal cancer risk in men and women. Sleep 2013;36:681-8. [Crossref] [PubMed]
19. Sekula P, Del Greco M F, Pattaro C, et al. Mendelian Randomization as an Approach to Assess Causality Using Observational Data. J Am Soc Nephrol 2016;27:3253-65. [Crossref] [PubMed]
20. Glymour MM, Tchetgen Tchetgen EJ, Robins JM. Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions. Am J Epidemiol 2012;175:332-9. [Crossref] [PubMed]
21. Li H, Boakye D, Chen X, et al. Associations of Body Mass Index at Different Ages With Early-Onset Colorectal Cancer. Gastroenterology 2022;162:1088-1097.e3. [Crossref] [PubMed]
22. Inokuchi M, Tanioka T, Nakagawa M, et al. Laparoscopic Distal Gastrectomy is Feasible in Very Elderly Patients as Compared with Open Distal Gastrectomy. J Invest Surg 2018;31:539-45. [Crossref] [PubMed]
23. Clarke L, Zheng-Bradley X, Smith R, et al. The 1000 Genomes Project: data management and community access. Nat Methods 2012;9:459-62. [Crossref] [PubMed]
24. Boef AG, Dekkers OM, le Cessie S. Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int J Epidemiol 2015;44:496-511. [Crossref] [PubMed]
25. Burgess S, Thompson SGCRP CHD Genetics Collaboration. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 2011;40:755-64. [Crossref] [PubMed]
26. Burgess S, Scott RA, Timpson NJ, et al. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol 2015;30:543-52. [Crossref] [PubMed]
27. Sanderson E, Glymour MM, Holmes MV, et al. Mendelian randomization. Nat Rev Methods Primers 2022;2:6. [Crossref] [PubMed]
28. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 2015;44:512-25. [Crossref] [PubMed]
29. Hemani G, Zheng J, Elsworth B, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife 2018;7:e34408. [Crossref] [PubMed]
30. Greco M FD, Minelli C, Sheehan NA, et al. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med 2015;34:2926-40. [Crossref] [PubMed]
31. Verbanck M, Chen CY, Neale B, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 2018;50:693-8. [Crossref] [PubMed]
32. Zhou T, Yuan Y, Xue Q, et al. Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. J Intern Med 2022;291:64-71. [Crossref] [PubMed]
33. Haus EL, Smolensky MH. Shift work and cancer risk: potential mechanistic roles of circadian disruption, light at night, and sleep deprivation. Sleep Med Rev 2013;17:273-84. [Crossref] [PubMed]
34. Hohor S, Mandanach C, Maftei A, et al. Impaired Melatonin Secretion, Oxidative Stress and Metabolic Syndrome in Night Shift Work. Antioxidants (Basel) 2023;12:959. [Crossref] [PubMed]
35. Reiter RJ, Rosales-Corral SA, Tan DX, et al. Melatonin, a Full Service Anti-Cancer Agent: Inhibition of Initiation, Progression and Metastasis. Int J Mol Sci 2017;18:843. [Crossref] [PubMed]
36. Farhood B, Goradel NH, Mortezaee K, et al. Melatonin and cancer: From the promotion of genomic stability to use in cancer treatment. J Cell Physiol 2019;234:5613-27. [Crossref] [PubMed]
37. Lange T, Luebber F, Grasshoff H, et al. The contribution of sleep to the neuroendocrine regulation of rhythms in human leukocyte traffic. Semin Immunopathol 2022;44:239-54. [Crossref] [PubMed]
38. Lendner JD, Niethard N, Mander BA, et al. Human REM sleep recalibrates neural activity in support of memory formation. Sci Adv 2023;9:eadj1895.
39. Schmid SM, Hallschmid M, Schultes B. The metabolic burden of sleep loss. Lancet Diabetes Endocrinol 2015;3:52-62. [Crossref] [PubMed]
40. Leproult R, Van Cauter E. Role of sleep and sleep loss in hormonal release and metabolism. Endocr Dev 2010;17:11-21. [Crossref] [PubMed]
41. Stewart BW. Priorities for cancer prevention: lifestyle choices versus unavoidable exposures. Lancet Oncol 2012;13:e126-33. [Crossref] [PubMed]
42. Samuelsson LB, Bovbjerg DH, Roecklein KA, et al. Sleep and circadian disruption and incident breast cancer risk: An evidence-based and theoretical review. Neurosci Biobehav Rev 2018;84:35-48. [Crossref] [PubMed]
43. Branche BL, Howard LE, Moreira DM, et al. Sleep Problems are Associated with Development and Progression of Lower Urinary Tract Symptoms: Results from REDUCE. J Urol 2018;199:536-42. [Crossref] [PubMed]
44. Qu M, Zhang G, Qu H, et al. Circadian regulator BMAL1::CLOCK promotes cell proliferation in hepatocellular carcinoma by controlling apoptosis and cell cycle. Proc Natl Acad Sci U S A 2023;120:e2214829120. [Crossref] [PubMed]
45. Dashti HS, Chen A, Daghlas I, et al. Morning diurnal preference and food intake: a Mendelian randomization study. Am J Clin Nutr 2020;112:1348-57. [Crossref] [PubMed]
46. Carasso S, Fishman B, Lask LS, et al. Metagenomic analysis reveals the signature of gut microbiota associated with human chronotypes. FASEB J 2021;35:e22011. [Crossref] [PubMed]
47. Feng Q, Liang S, Jia H, et al. Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat Commun 2015;6:6528. [Crossref] [PubMed]
48. Liu Y, Baba Y, Ishimoto T, et al. Gut microbiome in gastrointestinal cancer: a friend or foe? Int J Biol Sci 2022;18:4101-17. [Crossref] [PubMed]
49. Muscogiuri G, Barrea L, Aprano S, et al. Chronotype and Adherence to the Mediterranean Diet in Obesity: Results from the Opera Prevention Project. Nutrients 2020;12:1354. [Crossref] [PubMed]
50. Lee S, Ma C, Shi Q, et al. Sleep and cancer recurrence and survival in patients with resected Stage III colon cancer: findings from CALGB/SWOG 80702 (Alliance). Br J Cancer 2023;129:283-90. [Crossref] [PubMed]
51. Liu X, Chen B, Huang Z, et al. Effects of poor sleep on the immune cell landscape as assessed by single-cell analysis. Commun Biol 2021;4:1325. [Crossref] [PubMed]
52. Irwin MR, Olmstead R, Carroll JE. Sleep Disturbance, Sleep Duration, and Inflammation: A Systematic Review and Meta-Analysis of Cohort Studies and Experimental Sleep Deprivation. Biol Psychiatry 2016;80:40-52. [Crossref] [PubMed]
53. Bader SB, Dewhirst MW, Hammond EM. Cyclic Hypoxia: An Update on Its Characteristics, Methods to Measure It and Biological Implications in Cancer. Cancers (Basel) 2020;13:23. [Crossref] [PubMed]
54. Gallego-Martin T, Farré R, Almendros I, et al. Chronic intermittent hypoxia mimicking sleep apnoea increases spontaneous tumorigenesis in mice. Eur Respir J 2017;49:1602111. [Crossref] [PubMed]
55. Yoon K, Shin CM, Han K, et al. Risk of cancer in patients with insomnia: Nationwide retrospective cohort study (2009-2018). PLoS One 2023;18:e0284494. [Crossref] [PubMed]
56. Owusu D, Quinn M, Wang KS. Alcohol Consumption, Depression, Insomnia and Colorectal Cancer Screening: Racial Differences. Int J High Risk Behav Addict 2015;4:e23424. [Crossref] [PubMed]