Sherryl A. Taylor

Supplementary Table S5 shows regression coefficients that denote the difference in average DNA methylation level, as derived from the mean methylation ratios across all estimated CpG sites in the F2RL3 gene, and their associated 95%CI relative to the reference group. Multivariable models included adjustment for age, sex (not for stratified models), phase of blood sampling, education level, ethnicity, and smoking (CSI - cumulative smoking index). FWI of 0 was used to classify those as never exposed, >0-population median value as ‘Low exposure’ and ≥population median value as ‘High exposure.’

Supplementary Figure S2 shows, for each graph, the effect estimate and the 95% CI plotted across all 7 CpG sites in the F2RL3 gene. The dotted black line represents the null. For CSI, the interpretation of the effect estimate is the change in DNA methylation levels per standard deviation increase in CSI For smoking status (i.e., former and current smokers). Multivariable models included adjustment for age, sex, phase of blood sampling, education level, and ethnicity. The interpretation of the effect estimate is the difference in mean methylation level relative to never smokers (reference group). * denotes a p-value < 0.05.

Supplementary Figure S2 shows, for each graph, the effect estimate and the 95% CI plotted across all 7 CpG sites in the F2RL3 gene. The dotted black line represents the null. For CSI, the interpretation of the effect estimate is the change in DNA methylation levels per standard deviation increase in CSI For smoking status (i.e., former and current smokers). Multivariable models included adjustment for age, sex, phase of blood sampling, education level, and ethnicity. The interpretation of the effect estimate is the difference in mean methylation level relative to never smokers (reference group). * denotes a p-value < 0.05.

Supplementary Table S1 shows regression coefficients that denote the difference in average DNA methylation level, as derived from the mean methylation ratios across all estimated CpG sites in the AHRR gene, and their associated 95%CI relative to the reference group. Multivariable models included adjustment for age, sex (not for stratified models), phase of blood sampling, education level, ethnicity, and smoking (CSI - cumulative smoking index). A probability of exposure of 0% was categorized as unexposed; “Possibly exposed” if the probability of exposure was >0% and <25% and “Exposed” to a given agent if the probability of exposure was ≥25%.

Supplementary Figure S3 shows, for each graph, the effect estimate and the 95% CI plotted across all 33 CpG sites in the AHRR gene. Multivariable models included adjustment for age, phase of blood sampling, education level, ethnicity, and smoking (CSI - cumulative smoking index). The interpretation of the effect estimate is the difference in mean methylation level relative to those never exposed to each agent (reference group). Categorization of occupational exposures was based on the FWI as never exposed (FWI=0, reference group), Low exposure (>0 and lower than the population median, in blue square) and High exposure (≥population median, in red triangle). * Denotes a p-value < 0.05.

Supplementary Table S5 shows regression coefficients that denote the difference in average DNA methylation level, as derived from the mean methylation ratios across all estimated CpG sites in the F2RL3 gene, and their associated 95%CI relative to the reference group. Multivariable models included adjustment for age, sex (not for stratified models), phase of blood sampling, education level, ethnicity, and smoking (CSI - cumulative smoking index). FWI of 0 was used to classify those as never exposed, >0-population median value as ‘Low exposure’ and ≥population median value as ‘High exposure.’

Supplementary Table S2 shows regression coefficients that denote the difference in average DNA methylation level, as derived from the mean methylation ratios across all estimated CpG sites in the F2RL3 gene, and their associated 95%CI relative to the reference group. Multivariable models included adjustment for age, sex (not for stratified models), phase of blood sampling, education level, ethnicity, and smoking (CSI - cumulative smoking index). A probability of exposure of 0% was categorized as unexposed; “Possibly exposed” if the probability of exposure was >0% and <25% and; “Exposed” to a given agent if the probability of exposure was ≥25%.

Background:AHRR and F2RL3 hypomethylation has been associated with lung cancer. In this study, we investigated the cross-sectional association between smoking and occupational exposures, and AHRR and F2RL3 methylation.Methods:A case–control study was nested in CARTaGENE to examine the association between AHRR and F2RL3 methylation and lung cancer risk (200 cases; 400 controls). A secondary analysis was conducted using the data collected from this nested study; namely, baseline information on participants’ smoking behavior and longest-held job was obtained. A cumulative smoking index summarized information on the number of cigarettes smoked, duration of smoking, and time since cessation. Exposure to 13 occupational agents was estimated using the Canadian Job Exposure Matrix. In baseline blood samples, methylation ratios of 40 CpG sites in the AHRR and F2RL3 genes were measured using Sequenom EpiTYPER. Separate least squares regression models were used to estimate the associations between smoking and occupational exposures, and average AHRR and F2RL3 methylation levels, while adjusting for confounders identified from directed acyclic graphs.Results:In both genes, smoking was associated with lower average methylation levels. Occupational exposure to aromatic amines, cadmium, and formaldehyde were associated with lower AHRR methylation while, only benzene was associated with F2RL3 hypomethylation; these associations were stronger among ever smokers.Conclusions:Our findings support that smoking and occupational exposures to some agents are associated with AHRR and F2RL3 hypomethylation.Impact:Our results inform on mechanisms underlying environmental exposures in lung cancer etiology; future studies should prioritize studying joint exposures.

Supplementary Figure S1 shows, for each graph, the effect estimate and the 95% CI plotted across all 33 CpG sites in the AHRR gene. The dotted black line represents the null. For CSI, the interpretation of the effect estimate is the change in DNA methylation levels per standard deviation increase in CSI. For smoking status (i.e., former and current smokers), the interpretation of the effect estimate is the difference in mean methylation level relative to never smokers (reference group). Multivariable models included adjustment for age, sex, phase of blood sampling, education level, and ethnicity. * denotes a p-value < 0.05.

Supplementary Table S3 shows for the continuous representation of smoking (CSI), regression coefficients that denote the difference in average DNA methylation levels, as derived from the mean methylation ratios across all estimated CpG sites, per standard deviation increase in CSI, and their associated 95%CI relative to the reference group. For categorical representations of smoking (i.e., former and current smokers), regression coefficients denote the difference in average DNA methylation level, as derived from the mean methylation ratios across all estimated CpG sites, and their associated 95%CI relative to the reference group. Multivariable models included adjustment for age, sex, phase of blood sampling, education level, and ethnicity.