Abstract
Background
The objective of this study was to determine the causal relationship between habitual alcohol consumption with meals and lung cancer.
Methods
Public genetic summary data from two large consortia [the Neale Lab and the International Lung Cancer Consortium (ILCCO)] were used for analysis. As the instrumental variables of habitual alcohol consumption with meals, data on genetic variants were retrieved from Neale Lab. Additionally, genetic data from other consortia [Global Lipid Genetics Consortium (GLGC), Tobacco, Alcohol and Genetics (TAG), Genetic Investigation of Anthropocentric Traits (GIANT)] were utilized to determine whether alcohol could causally alter some general risk factors for lung cancer. The primary outcome was the risk of lung cancer (11,348 cases and 15,861 controls in the ILCCO). The R package TwoSampleMR was used for analysis.
Results
Based on the inverse variance weighted method, the results of the two-sample Mendelian randomization (MR) analyses indicated that commonly consuming alcohol with meals was a protective factor, reducing lung cancer risk [odds ratio (OR) 0.175, 95% confidence interval (CI): 0.045–0.682, P=0.012]. The heterogeneity analysis revealed that the causal relationship analyses of different types of lung cancer all had low heterogeneity (P>0.05). The horizontal pleiotropic study showed that major bias was unlikely. The MR assumptions did not seem to be violated. The causal relationship analyses between habitual alcohol consumption with meals and some risk factors for cancers showed that this alcohol consumption habit was a beneficial factor for reducing body mass index (BMI) and the number of cigarettes smoked per day.
Conclusions
Habitual appropriate alcohol consumption with meals is a protective factor for the development of lung cancer.
Keywords: Mendelian randomization, alcohol, lung cancer
Introduction
Conventionally, alcohol consumption has been thought to cause many risk factors towards various diseases, such as obesity; however, a study conducted by Arif et al. (1) indicated that an appropriate alcohol consumption habit (fewer than 5 drinks per week) could decrease the incidence of obesity. Furthermore, for various diseases, several studies have shown that appropriate alcohol consumption (light-to-moderate, less than 30 g/d) is beneficial for patients’ health and can not only reduce the risk of type 2 diabetes (2), arterial hypertension (3), and cardiovascular diseases (4) but can also decrease patient mortality (5).
It is estimated that lung cancer, as the first leading cause of cancer death in the USA, will result in more than 130 thousand patient deaths in 2020 (6), with a total 5-year survival rate of 19% (6). It is crucial to clarify modifiable risk factors and beneficial factors to improve the prevention of lung cancer because of the increasing burden (7). Regarding risk factors, smoking has been identified as the most frequent cause of lung cancer (8), and because of tobacco control policies, lung cancer mortality has significantly decreased (6,9,10). In addition, regarding beneficial factors, the study by Zhou et al. (11) showed that education was one of the protective factors for lung cancer, which was proposed by Mendelian randomization (MR).
Worldwide interest in MR has greatly increased over the last 10 years; this method uses genome-wide association study (GWAS) data to demonstrate the exact causal relationship between A and B (using instrumental variable analysis with genetic instruments), which can avoid the influences of other exposure factors on the outcomes (12). Previously, several observational studies have shown that appropriate alcohol consumption (amount per day and frequency per week) could prevent lung cancer (13,14). Among these studies, the study by Brenner et al. (13) demonstrated that alcohol intake of less than 20 g/d was a beneficial factor for the prevention of lung cancer. Moreover, Li et al. (14) indicated that occasionally consuming alcohol throughout the week was a favorable factor for the survival of Chinese men with lung cancer. Therefore, we conducted an MR study to confirm the causal relationship between the habitual consumption of alcohol with meals and lung cancer. We present the following article in accordance with the STROBE reporting checklist (available at http://dx.doi.org/10.21037/atm-20-3063).
Methods
Genetic variants associated with lung cancer
The exposure factor data (habitual alcohol consumption with meals) in this study were based on the Neale Lab. The outcome data (incidence of lung cancer, lung adenocarcinoma, and lung squamous cell cancer) were retrieved from the International Lung Cancer Consortium (ILCCO) (15), and the data for small cell lung cancer were obtained from the UK BioBank. In terms of other risk factors, the data of triglycerides and total cholesterol were obtained from the Global Lipid Genetics Consortium (GLGC) (16); the data of smoking habits (including cigarettes smoked per day, former vs. current smoker, age of smoking initiation, and ever vs. never smoker) were obtained from the Tobacco, Alcohol and Genetics (TAG) consortium (17); and the data of obesity class 1–3, waist circumference (adjusted by body mass index, BMI), hip circumference (adjusted by BMI), and waist-to-hip ratio (adjusted by BMI) were retrieved from the Genetic Investigation of Anthropocentric Traits (GIANT) (18,19). (Table 1).
Table 1. Details of studies included in Mendelian randomization analyses.
| Variable | Consortium | PMID | Population | Gender |
|---|---|---|---|---|
| Lung cancer | ILCCO | 24880342 | 11,348 | European |
| Habitual consumption of alcohol with meals | Neale Lab | UK BioBank | – | – |
| Obesity 1–3 (waist circumference, hip circumference, waist-to-hip ratio) | GIANT | 23563607, 25673412; | European (for obesity 1–3); mixed (waist circumference, hip circumference, waist-to-hip ratio) | Mixed |
| Triglycerides, total cholesterol | GLGC | 24097068 | Mixed | Mixed |
| Cigarettes smoking | TAG | 20418890 | European | Mixed |
ILCCO, International Lung Cancer Consortium; TAG, Tobacco, Alcohol and Genetics; GLGC, Global Lipids Genetics Consortium; GIANT, Genetic Investigation of Anthropocentric Traits.
Statistical analyses
To determine MR estimates of habitual alcohol consumption with meals for lung cancer, we used several MR approaches. In our study, habitual consumption of alcohol meant appropriate alcohol consumption habit (light-to-moderate, less than 30 g/d). We conducted a random effect inverse variance weighted (IVW) meta-analysis of the Wald ratio for individual single nucleotide polymorphisms (SNPs). Other statistical tests (the weighted median and MR-Egger regression methods) were used to estimate the effects. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs).
Three assumptions were the basis of the MR method: (I) the instrumental variables are strongly associated with the habitual consumption of alcohol with meals; (II) the instrumental variables influence lung cancer only through their effect on habitual alcohol consumption with meals; and (III) the instrumental variables are independent of any confounder (20). We assessed the directional pleiotropy based on the intercept obtained from the MR-Egger analysis (21).
The common risk factors for lung cancer were identified in previous studies (22,23). Analyses were performed by using the package TwoSampleMR (version 0.3.4) in R (version 3.4.2).
The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).
Results
Causal relationships between appropriate alcohol consumption and lung cancer
The IVW analysis results indicated that habitual appropriate alcohol consumption with meals was a protective factor for lung cancer (OR 0.175, 95% CI: 0.045–0.682, P=0.012) and lung squamous cell cancer (OR 0.075, 95% CI: 0.013–0.429, P=0.004). However, the two-sample MR results of habitual appropriate alcohol consumption with meals and lung adenocarcinoma (OR 1.000, 95% CI: 0.999–1.001, P=0.900), as well as small cell lung cancer (OR 0.247, 95% CI: 0.052–1.169, P=0.078), did not show causal relationships (Table 2, Figures 1-5).
Table 2. Results from two sample MR.
| Cancer | Method | Numbers of SNPs | P value | OR | 95% CI |
|---|---|---|---|---|---|
| Lung cancer | MR-Egger | 14 | 0.375 | 0.002 | 2.01E−09 to 1,355.308 |
| Weighted median | 14 | 0.034* | 0.201 | 0.046–0.885 | |
| Inverse variance weighted | 14 | 0.012* | 0.175 | 0.045–0.682 | |
| Small cell lung cancer | MR-Egger | 14 | 0.777 | 0.998 | 0.985–1.012 |
| Weighted median | 14 | 0.796 | 1.000 | 0.998–1.002 | |
| Inverse variance weighted | 14 | 0.900 | 1.000 | 0.999–1.001 | |
| Lung adenocarcinoma | MR-Egger | 14 | 0.887 | 3.108 | 7.18E−07 to 13,449,061.81 |
| Weighted median | 14 | 0.059 | 0.139 | 0.018–1.079 | |
| Inverse variance weighted | 14 | 0.078 | 0.247 | 0.052–1.169 | |
| Squamous cell lung cancer | MR-Egger | 14 | 0.149 | 2.36E−06 | 1.64E−13 to 33.966 |
| Weighted median | 14 | 0.016* | 0.065 | 0.007–0.605 | |
| Inverse variance weighted | 14 | 0.004* | 0.075 | 0.013–0.429 |
*, P value <0.05. MR, Mendelian randomization; SNPs, single nucleotide polymorphisms; OR, odds ratio; CI, confidential index.
Figure 1.
Forest plot of the causal effects of alcohol usually taken with meals-associated single nucleotide polymorphisms on lung cancer. MR, Mendelian randomization.
Figure 2.
Forest plot of the causal effects of alcohol usually taken with meals-associated single nucleotide polymorphisms on lung squamous cell cancer. MR, Mendelian randomization.
Figure 3.
Forest plot of the causal effects of alcohol usually taken with meals-associated single nucleotide polymorphisms on lung adenocarcinoma. MR, Mendelian randomization.
Figure 4.
Forest plot of the causal effects of alcohol usually taken with meals-associated single nucleotide polymorphisms on small cell lung cancer. MR, Mendelian randomization.
Figure 5.
Scatter plots of genetic associations with alcohol usually taken with meals against the genetic associations with lung cancer. MR, Mendelian randomization; SNP, single nucleotide polymorphism.
The heterogeneity study showed that the heterogeneity in the causal relationship analysis between habitual appropriate alcohol consumption with meals and the incidence of lung cancer was high (P=0.033 for Egger, P=0.039 for IVW); however, the heterogeneities in different types of lung cancer were low (P>0.05 for MR-Egger, and IVW) (Table 3). The horizontal pleiotropy study showed that habitual appropriate alcohol consumption with meals did not have multiple effects on other factors of lung cancer (P>0.05) (Table 4). The direction of the causal relationship of all MR analyses showed forward causal relationships (P<0.05) (Table 5).
Table 3. Heterogeneity tests.
| Cancer | Method | Q | Q_df | P value |
|---|---|---|---|---|
| Lung cancer | MR-Egger | 22.379 | 12 | 0.033* |
| Inverse variance weighted | 23.229 | 13 | 0.039* | |
| Small cell lung cancer | MR-Egger | 10.322 | 12 | 0.588 |
| Inverse variance weighted | 10.414 | 13 | 0.660 | |
| Lung adenocarcinoma | MR-Egger | 12.042 | 12 | 0.442 |
| Inverse variance weighted | 12.148 | 13 | 0.516 | |
| Squamous cell lung cancer | MR-Egger | 14.548 | 12 | 0.267 |
| Inverse variance weighted | 16.411 | 13 | 0.228 |
*, P value <0.05. MR, Mendelian randomization.
Table 4. Test for directional horizontal pleiotropy.
| Cancer | Egger_intercept | SE | P value |
|---|---|---|---|
| Lung cancer | 0.047 | 0.070 | 0.512 |
| Small cell lung cancer | 2.10E−05 | 6.91E−05 | 0.766 |
| Lung adenocarcinoma | −0.025 | 0.078 | 0.750 |
| Squamous cell lung cancer | 0.105 | 0.084 | 0.239 |
*, P value <0.05. SE, standard error.
Table 5. Test that the exposure is upstream of the outcome.
| Cancer | Snp_r2. exposure | Snp_r2. outcome | Correct_causal_direction | Steiger_P value |
|---|---|---|---|---|
| Lung cancer | 0.003 | 0.001 | True | 0.007* |
| Small cell lung cancer | 0.003 | 2.31E−05 | True | <0.001* |
| Lung adenocarcinoma | 0.003 | 0.001 | True | 0.001* |
| Squamous cell lung cancer | 0.003 | 0.001 | True | 0.026* |
*, P value <0.05. SNPs, single nucleotide polymorphisms.
Causal relationship between appropriate alcohol consumption and risk factors
The MR analyses between habitual appropriate alcohol consumption with meals and other risk factors for lung cancers showed that the former was a protective factor associated with reduce BMI (OR 0.701, 95% CI: 0.577–0.852, P<0.001) and fewer cigarettes smoked per day (OR 0.002, 95% CI: 3.500E−06 to 0.901, P=0.046). However, other risk factors, including age of smoking initiation (OR 1.140, 95% CI: 0.961–1.354, P=0.133), former vs. current smoker (OR 1.778, 95% CI: 0.532–5.949, P=0.350), total cholesterol (OR 0.707, 95% CI: 0.420–1.189, P=0.192), and triglycerides (OR 0.762, 95% CI: 0.542–1.072, P=0.119), did not show significant causal relationships with habitual appropriate alcohol consumption with meals (Table 6).
Table 6. Two sample MR of alcohol consumption and risk factors.
| Risk factors | Numbers of SNPs | P value | OR | 95% CI |
|---|---|---|---|---|
| Age of smoking initiation | 8 | 0.133 | 1.140 | 0.961–1.354 |
| BMI | 14 | <0.001* | 0.701 | 0.577–0.852 |
| Total cholesterol | 8 | 0.192 | 0.707 | 0.420–1.189 |
| Triglycerides | 8 | 0.119 | 0.762 | 0.542–1.072 |
| Cigarettes smoked per day | 8 | 0.046* | 0.002 | 3.50E−06 to 0.901 |
| Former vs. current smoker | 8 | 0.350 | 1.778 | 0.532–5.949 |
*, P value <0.05. MR, Mendelian randomization; SNPs, single nucleotide polymorphisms; OR, odds ratio; CI, confidential index; BMI, body mass index.
Discussion
The results of our MR study verified the causal relationship between habitual appropriate alcohol consumption with meals and lung cancer. Several studies have supported the idea that light-to-moderate alcohol consumption could not only decrease the incidence of lung cancer (13,24), but could also benefit lung cancer patients’ prognosis. Additionally, light-to-moderate alcohol consumption showed benefits in the studies of many different diseases, including type 2 diabetes (2), arterial hypertension (3), and cardiovascular diseases (4). In this case, we are inclined to conclude that appropriate alcohol consumption is important for health (13,25).
The MR analyses between habitual alcohol consumption with meals and some risk factors for lung cancer demonstrated that this causal relationship probably resulted from the phenomenon that people with this habit care more about their health by avoiding some risk factors, such as smoking (fewer cigarettes smoked per day) and so on. On the one hand, the deduced effect above seems reasonable when patients are smokers. On the other hand, for non-smoking lung cancer patients, the study conducted by Fehringer et al. (26) indicated that light-to-moderate alcohol consumers (less than 20 g per day) had lower lung cancer risk than non-drinkers. Furthermore, Garcia Lavandeira et al. (27) suggested that the consumption of almost all kinds of alcohol, except spirits, posed no risk to lung cancer patient survival.
To explore the mechanism, we hypothesized that flavonoids found in wine may reduce the risk of some cancers. Support for a beneficial role of flavonoids is provided by several studies where higher dietary intake of flavonoids (including flavonols, flavanones and quercetin) was inversely associated with lung cancer risk (28).
For these SNPs included in our MR study, rs4130609 reflected single nucleotide variation in SOX5 gene, which reduced expression by alcohol exposure (29). Moreover, rs113905912 represented single nucleotide variation in KMT2E gene, and the mutation of this gene was associated with various diseases, such as some intellectual disability disorders (30), leukemia (31), and vasculopathy (32). Besides, rs62247171 meant Single nucleotide variation in FOXP1 gene, which could be also related to multiple sclerosis (33), and ischemic stroke (33).
The MR results showed that habitual alcohol consumption with meals had an inverse effect on BMI. The study conducted by Arif et al. (1) also demonstrated that compared with nondrinkers, subjects with moderate alcohol consumption (fewer than 5 drinks per week) had a lower BMI. One interesting MR study (34) indicated that regular light-to-moderate alcohol consumption could increase high-density lipoprotein and reduce total glycerides, total cholesterol, and low-density lipoprotein, and according to previous studies, these lipid indicators were associated with lung cancer (35,36).
Randomized controlled trials (RCTs) are widely accepted to verify causality, but they are associated with a high cost. Because of the consistently long latency between the exposures and the occurrence of diseases, it is impractical and impossible to investigate all these causal associations through RCTs. However, in MR, genetic markers are used as variables of exposure instead of the exposure itself to facilitate causal inference (37). This method is rarely affected by confounding, reverse causality, and measurement error (38). Additionally, we can implement MR design by using two-sample MR analysis based on published summary data from large-scale GWASs, which greatly increases the scope and statistical power of MR studies (39,40).
Our study is the first MR study about alcohol consumption habits (alcohol habitually consumed with meals) and lung cancer. Participants were grouped based on their randomly allocated genotype, mimicking an RCT. However, limitations still exist in our study. First, all the participants included in our study were of European origin. Thus, whether the results can be generalized to other populations still needs to be studied and verified. Moreover, the summary data we used for two-sample MR did not allow for stratified analyses by covariates of interests, such as age and smoking status.
Conclusions
Habitual alcohol consumption with meals has a causal relationship with lung cancer. Furthermore, more work is needed to elucidate the potential mechanisms that mediate the associations between habitual alcohol consumption with meals and lung cancer.
Supplementary
The article’s supplementary files as
Acknowledgments
Funding: This work was supported by the funds from the Medical Research Fund of Guangdong Province (No. A2018237). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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).
Footnotes
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at http://dx.doi.org/10.21037/atm-20-3063
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at: http://dx.doi.org/10.21037/atm-20-3063). The authors have no conflicts of interest to declare.
References
- 1.Arif AA, Rohrer JE. Patterns of alcohol drinking and its association with obesity: data from the Third National Health and Nutrition Examination Survey, 1988-1994. BMC Public Health 2005;5:126. 10.1186/1471-2458-5-126 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Knott C, Bell S, Britton A. Alcohol Consumption and the Risk of Type 2 Diabetes: A Systematic Review and Dose-Response Meta-analysis of More Than 1.9 Million Individuals From 38 Observational Studies. Diabetes Care 2015;38:1804-12. 10.2337/dc15-0710 [DOI] [PubMed] [Google Scholar]
- 3.Briasoulis A, Agarwal V, Messerli FH. Alcohol consumption and the risk of hypertension in men and women: a systematic review and meta-analysis. J Clin Hypertens (Greenwich) 2012;14:792-8. 10.1111/jch.12008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Di Castelnuovo A, Rotondo S, Iacoviello L, et al. Meta-analysis of wine and beer consumption in relation to vascular risk. Circulation 2002;105:2836-44. 10.1161/01.CIR.0000018653.19696.01 [DOI] [PubMed] [Google Scholar]
- 5.Gronbaek M, Johansen D, Becker U, et al. Changes in alcohol intake and mortality: a longitudinal population-based study. Epidemiology 2004;15:222-8. 10.1097/01.ede.0000112219.01955.56 [DOI] [PubMed] [Google Scholar]
- 6.Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin 2020;70:7-30. 10.3322/caac.21590 [DOI] [PubMed] [Google Scholar]
- 7.Chen C. Analysis of Cell Division Cycle Associated genes expression and its prognostic significance in human lung carcinoma: a review of literature databases. Biomed Research International 2020. doi: . 10.1155/2020/6412593 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Volk RJ, Mendoza TR, Hoover DS, et al. Reliability of self-reported smoking history and its implications for lung cancer screening. Prev Med Rep 2020;17:101037. 10.1016/j.pmedr.2019.101037 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018;68:7-30. 10.3322/caac.21442 [DOI] [PubMed] [Google Scholar]
- 10.Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin 2016;66:7-30. 10.3322/caac.21332 [DOI] [PubMed] [Google Scholar]
- 11.Zhou H, Zhang Y, Liu J, et al. Education and lung cancer: a Mendelian randomization study. Int J Epidemiol 2019;48:743-50. 10.1093/ije/dyz121 [DOI] [PubMed] [Google Scholar]
- 12.Zeng P, Zhou X. Causal Association Between Birth Weight and Adult Diseases: Evidence From a Mendelian Randomization Analysis. Front Genet 2019;10:618. 10.3389/fgene.2019.00618 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Brenner DR, Fehringer G, Zhang ZF, et al. Alcohol consumption and lung cancer risk: A pooled analysis from the International Lung Cancer Consortium and the SYNERGY study. Cancer Epidemiol 2019;58:25-32. 10.1016/j.canep.2018.10.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Li W, Tse LA, Au JS, et al. Prognostic value of alcohol consumption and some other dietary habits for survival in a cohort of Chinese men with lung cancer. Chin J Cancer 2017;36:21. 10.1186/s40880-017-0188-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Wang Y, McKay JD, Rafnar T, et al. Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer. Nat Genet 2014;46:736-41. 10.1038/ng.3002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Willer CJ, Schmidt EM, Sengupta S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet 2013;45:1274-83. 10.1038/ng.2797 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat Genet 2010;42:441-7. 10.1038/ng.571 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Berndt SI, Gustafsson S, Magi R, et al. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet 2013;45:501-12. 10.1038/ng.2606 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Shungin D, Winkler TW, Croteau-Chonka DC, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature 2015;518:187-96. 10.1038/nature14132 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.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. 10.1093/ije/dyv071 [DOI] [PubMed] [Google Scholar]
- 21.Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol 2017;32:377-89. 10.1007/s10654-017-0255-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Brennan P, McKay J, Moore L, et al. Obesity and cancer: Mendelian randomization approach utilizing the FTO genotype. Int J Epidemiol 2009;38:971-5. 10.1093/ije/dyp162 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Gao C, Patel CJ, Michailidou K, et al. Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer. Int J Epidemiol 2016;45:896-908. 10.1093/ije/dyw129 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Alvarez-Avellon SM, Fernandez-Somoano A, Navarrete-Munoz EM, et al. Effect of alcohol and its metabolites in lung cancer: CAPUA study. Med Clin (Barc) 2017;148:531-8. [DOI] [PubMed] [Google Scholar]
- 25.Kakino K, Kiyohara C, Horiuchi T, et al. CYP2E1 rs2031920, COMT rs4680 Polymorphisms, Cigarette Smoking, Alcohol Use and Lung Cancer Risk in a Japanese Population. Asian Pac J Cancer Prev 2016;17:4063-70. [PubMed] [Google Scholar]
- 26.Fehringer G, Brenner DR, Zhang ZF, et al. Alcohol and lung cancer risk among never smokers: A pooled analysis from the international lung cancer consortium and the SYNERGY study. Int J Cancer 2017;140:1976-84. 10.1002/ijc.30618 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Garcia Lavandeira JA, Ruano-Ravina A, Kelsey KT, et al. Alcohol consumption and lung cancer risk in never smokers: a pooled analysis of case-control studies. Eur J Public Health 2018;28:521-7. 10.1093/eurpub/ckx196 [DOI] [PubMed] [Google Scholar]
- 28.Lam TK, Rotunno M, Lubin JH, et al. Dietary quercetin, quercetin-gene interaction, metabolic gene expression in lung tissue and lung cancer risk. Carcinogenesis 2010;31:634-42. 10.1093/carcin/bgp334 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Zhou FC, Zhao Q, Liu Y, et al. Alteration of gene expression by alcohol exposure at early neurulation. BMC Genomics 2011;12:124. 10.1186/1471-2164-12-124 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Conforti R, Iovine S, Santangelo G, et al. ODLURO syndrome: personal experience and review of the literature. Radiol Med 2020. [Epub ahead of print]. doi: . 10.1007/s11547-020-01255-2 [DOI] [PubMed] [Google Scholar]
- 31.Liquori A, Ibañez M, Sargas C, et al. Acute Promyelocytic Leukemia: A Constellation of Molecular Events around a Single PML-RARA Fusion Gene. Cancers (Basel) 2020;12:624. 10.3390/cancers12030624 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Fan Q, Cheung CMG, Chen LJ, et al. Shared genetic variants for polypoidal choroidal vasculopathy and typical neovascular age-related macular degeneration in East Asians. J Hum Genet 2017;62:1049-55. 10.1038/jhg.2017.83 [DOI] [PubMed] [Google Scholar]
- 33.Tian Z, Song Y, Yao Y, et al. Genetic Etiology Shared by Multiple Sclerosis and Ischemic Stroke. Front Genet 2020;11:646. 10.3389/fgene.2020.00646 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Vu KN, Ballantyne CM, Hoogeveen RC, et al. Causal Role of Alcohol Consumption in an Improved Lipid Profile: The Atherosclerosis Risk in Communities (ARIC) Study. PLoS One 2016;11:e0148765. 10.1371/journal.pone.0148765 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Şahin F, Aslan AF. Relationship between Inflammatory and Biological Markers and Lung Cancer. J Clin Med 2018;7:160. 10.3390/jcm7070160 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Lyu Z, Li N, Wang G, et al. Independent and joint associations of blood lipids and lipoproteins with lung cancer risk in Chinese males: A prospective cohort study. Int J Cancer 2019;144:2972-84. 10.1002/ijc.32051 [DOI] [PubMed] [Google Scholar]
- 37.Smith GD, Ebrahim S. 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 2003;32:1-22. 10.1093/ije/dyg070 [DOI] [PubMed] [Google Scholar]
- 38.Scosyrev E. Identification of causal effects using instrumental variables in randomized trials with stochastic compliance. Biom J 2013;55:97-113. 10.1002/bimj.201200104 [DOI] [PubMed] [Google Scholar]
- 39.Pierce BL, Burgess S. Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. Am J Epidemiol 2013;178:1177-84. 10.1093/aje/kwt084 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.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. 10.1007/s10654-015-0011-z [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
The article’s supplementary files as