AHRR cg05575921 methylation in relation to smoking and PM2.5 exposure among Taiwanese men and women

Background Polycyclic aromatic hydrocarbon (PAH)-rich substances like cigarette smoke and PM2.5 induce aryl hydrocarbon receptor (AHR)-mediated aryl hydrocarbon receptor repressor (AHRR) methylation. AHRR cg05575921 and coagulation factor II (thrombin) receptor-like 3 (F2RL3) cg03636183 methylation patterns are well-established biomarkers for smoking. Even though AHRR cg05575921 methylation has recently been associated with PM2.5, the interaction between smoking and PM2.5 on AHRR methylation is yet to be fully explored. We evaluated AHRR and F2RL3 CpG sites to identify potential significant markers in relation to PM2.5 and smoking in Taiwanese adults. Methods DNA methylation and smoking data of 948 participants aged 30–70 years were obtained from the Taiwan Biobank Database (2008–2015), while PM2.5 data were obtained from the Air Quality Monitoring Database (2006–2011). Results Smoking and PM2.5 were independently associated with hypomethylation (lower levels) of AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2LR3 cg21911711 after multiple-comparison correction (Bonferroni P < 0.00028409). Cg05575921 was the most hypomethylated AHRR CpG site, while cg03636183 was the most hypomethylated F2RL3 CpG site. Overall, cg05575921 was the most hypomethylated CpG site: β = − 0.03909, P < 0.0001; − 0.17536, P < 0.0001 for former and current smoking, respectively (P-trendsmoking < 0.0001) and − 0.00141, P < 0.0001 for PM2.5. After adjusting for F2RL3 cg03636183, smoking and PM2.5 remained significantly associated with cg05575921 hypomethylation: β − 0.02221, P < 0.0001; − 0.11578, P < 0.0001 for former and current smoking, respectively (P-trendsmoking < 0.0001) and − 0.0070, P = 0.0120 for PM2.5. After stratification by sex, smoking and PM2.5 remained associated (P < 0.05) with cg05575921 hypomethylation in both men (β = − 0.04274, − 0.17700, and − 0.00163 for former smoking, current smoking, and PM2.5, respectively) and women (β = − 0.01937, − 0.17255, and − 0.00105 for former smoking, current smoking, and PM2.5, respectively). After stratification by residential area, former and current smoking remained associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.03918 and − 0.17536, respectively (P-trendsmoking < 0.0001). Living in the central and southern areas was also associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.01356 and − 0.01970, respectively (P-trendarea < 0.0001). Conclusion Smoking and PM2.5 were independently associated with hypomethylation of cg05575921, cg23576855, cg03636183, and cg21911711. The most hypomethylated CpG site was cg05575921 and its association with smoking and PM2.5 was dose-dependent.

(Continued from previous page) respectively (P-trend smoking < 0.0001). Living in the central and southern areas was also associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.01356 and − 0.01970, respectively (P-trend area < 0.0001). Conclusion: Smoking and PM 2.5 were independently associated with hypomethylation of cg05575921, cg23576855, cg03636183, and cg21911711. The most hypomethylated CpG site was cg05575921 and its association with smoking and PM 2.5 was dose-dependent.
DNA methylation is a remarkable and stable covalent process that occurs during early tumorigenesis [12]. This epigenetic process is reversible and thus, is a potential diagnostic tool and therapeutic target for diseases especially lung cancer [12,13]. Lung cancer is a major cause of cancer-related mortality in Taiwan [14,15] and the world [13,14,16,17]. Air pollution and cigarette smoking are two important environmental factors that independently enhance lung cancer development and mortality [16][17][18][19][20][21][22][23][24]. In 2015, approximately 8.9 and 6·4 million global deaths were attributable to PM 2.5 and smoking, respectively [25,26]. Significant joint effects of PM 2.5 and smoking on lung cancer and cardiovascular disease mortality have been reported [27][28][29].
To our knowledge, no study has focused on the relationship of AHRR cg05575921 methylation with both PM 2.5 and cigarette smoking. Hence, it is yet to be fully known whether PM 2.5 and cigarette smoking have a joint effect on AHRR cg05575921 methylation. Therefore, the interaction between PM 2.5 and smoking on AHRR cg05575921 methylation and other methylation markers for smoking merits more studies. In view of this, we evaluated AHRR and F2RL3 CpG sites to identify potential significant markers in relation to PM 2.5 and smoking in Taiwanese men and women.

Results
The association of AHRR and F2LR3 CpG sites with smoking and PM 2.5 is shown in Supplementary Table 1. Four CpG sites (AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2RL3 cg21911711) had significant inverse associations with smoking and PM 2.5 after multiplecomparison correction (Bonferroni P value < 0.00028409). That is, AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2RL3 cg21911711 were significantly hypomethylated in relation to smoking and PM 2.5 . Noteworthy, cg05575921 was the most hypomethylated AHRR CpG site, while cg03636183 was the most hypomethylated F2RL3 CpG site. In general, cg05575921 was the most hypomethylated CpG site (Supplementary Table 1) and further analysis was focused on this specific CpG site.
The clinical and demographic characteristics of 488 male and 460 female participants are illustrated in Table 1. The mean ± standard error (SE) AHRR cg05575921 methylation levels (beta-values) in men and women were 0.7832 ± 0.0042 and 0.8376 ± 0.0023, respectively. There were significant differences (P < 0.0001) between men and women with respect to cg05575921 methylation, smoking, alcohol drinking, and body mass index (BMI). The mean annual concentrations of PM 2.5 from 2006 to 2011 were 26.53, 30.06, 36.91, and 40.68 μg/m 3 for the northern, north-central, central, and southern area, respectively (Table 1). Table 2 shows the association of smoking and PM 2.5 with cg05575921 methylation in the study participants. Compared to never smoking, former and current smoking were significantly associated with lower levels of cg05575921: β = − 0.03909, P < 0.0001 and − 0.17536, P < 0.0001 for former and current smoking, respectively. Moreover, the test for linear trend was significant: Ptrend smoking < 0.0001 (Table 2). In addition to smoking, PM 2.5 , sex, and age were significantly associated with lower levels of cg05575921 methylation: β = − 0.00141 (P < 0.0001), − 0.01870 (P < 0.0001), and − 0.00044 (P = 0.0145) for PM 2.5 , male sex, and age, respectively (Table 2, model 1). Inclusion of F2RL3 cg03636183 into the model did not significantly affect the association of AHRR cg05575921 with smoking and PM 2.5 : β − 0.02221, P < 0.0001 and, − 0.11578, P < 0.0001 for former and current smoking, respectively (P-trend smoking < 0.0001) and − 0.0070, P = 0.0120 for PM 2.5 (Table 2, model 2). The interaction between PM 2.5 and smoking on cg05575921 methylation was not significant.
After stratification by sex (Table 3), smoking and PM 2.5 remained significantly associated with lower levels of cg05575921 methylation in both men: β = 0.04274, P < 0.0001 for former smoking; − 0.17700, P < 0.0001 for current smoking (P-trend smoking < 0.0001); and − 0.00163, P = 0.0017 for PM 2.5 and women: β = − 0.01937, P = 0.0417 for former smoking; − 0.17255, P < 0.0001 for current smoking (P-trend smoking < 0.0001); and − 0.00105, P = 0.0015 for PM 2.5 (Table 3). Table 4 shows the association of smoking and living in PM 2.5 areas with cg05575921 methylation. With never smoking as the reference variable, significant lower levels of AHRR cg05575921 methylation were observed in both former and current smokers: β = − 0.03918, P < 0.0001 and − 0.17536, P < 0.0001, respectively (P-trend smoking < 0.0001). Living in areas with higher PM 2.5 pollution was associated with lower levels of cg05575921 methylation: β = − 0.00267, P = 0.6230 for the north-central; − 0.01356, P = 0.0074 for the central; and − 0.01970, P < 0.0001 for the southern area. Despite the absence of an association between living in the north-central area and cg05575921 methylation, the test for trend was significant (P-trend area < 0.0001).

Discussion
In the current study, smoking and PM 2.5 were significantly associated with hypomethylation of AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2LR3 cg21911711 after multiple-comparison correction (Bonferroni correction). Cg05575921 was the most hypomethylated AHRR CpG site, while cg03636183 was the most hypomethylated F2RL3 CpG site. Noteworthy, cg05575921 was the overall top significant CpG site and its relation with smoking and PM 2.5 was dose-dependent. Adjusting for F2RL3 cg03636183 did not affect the association of smoking and PM 2.5 with cg05575921. However, there was no significant interaction between smoking and PM 2.5 on cg05575921 methylation. To the best of our knowledge, no study has assessed both the independent and joint association of smoking and PM 2.5 with AHRR cg05575921 methylation.
Cigarette smoke contains toxic components capable of directly altering the epigenetic profiles of white blood cells in the bloodstream [39]. For instance, PAH in cigarette smoke induces AHR-mediated AHRR expression and methylation [1,2,5,47,48]. In light of this, we focused on  the association of smoking and PM 2.5 with a specific AHRR methylation marker, cg05575921. Our focus on this particular CpG site was because it has recently been associated with PM 2.5 exposure in non-smokers [46]. Besides, it has consistently shown dose-response relationships with smoking [17,[31][32][33][34][35][36][37][38][39][40]49] and has also shown high sensitivity and specificity in predicting smoking status [33,50,51]. Moreover, it has been the most significant hypomethylated smoking-related CpG site in many epigenome-wide association studies (EWAS) [45]. Findings from the current study are in concordance with those stated above.
In addition to being a predictor of smoking habits [52], AHRR cg05575921 methylation from whole blood or saliva DNA is a validated predictor of smokingrelated morbidity and mortality [35,49]. For instance, AHRR cg05575921 hypomethylation has been associated with enhanced carcinogenesis especially in the lungs [10,31,35,38]. The mechanism underlying the relationship between AHRR cg05575921 methylation and lung cancer is unclear. However, cigarette smoke-induced AHRR hypomethylation and the associated increase in the expression of the AHRR gene could compromise the metabolizing ability of the body. This impairs the removal of deleterious environmental pollutants thereby increasing the risk of cancer [53]. Moreover, it is believed that cigarette smoke triggers vascular endothelial dysfunction by disrupting the structure of the airway epithelial barrier [54,55]. This eases the entry, deposition, and retention of particles into the arterial wall [56,57]. Cigarette smoke may also impair the clearance of fine particles in the alveoli thereby aggravating subsequent deleterious effects [56,57].
Toxic components adsorbed on the surface of PM 2.5 like PAHs have been associated with DNA methylation changes [58,59]. Like PM 2.5 , cigarette smoke also contains PAHs which are capable of inducing AHR-mediated AHRR methylation [1,2,5,47,48]. Since both cigarette smoke and PM 2.5 are inhalable carcinogens rich in PAH, PM 2.5 -induced AHRR methylation might also explain the pathophysiological mechanism of lung cancer. While the relationship of AHRR cg05575921 methylation with smoking is well-documented [17,[31][32][33][34][35][36][37][38][39][40]49], PM 2.5 -related AHRR cg05575921 methylation on the other hand still deserves more attention. It has been suggested that air pollution could be the driving force behind the AHRR cg05575921 hypomethylation-associated impaired lung function in never smokers [60]. In our previous study,   [46]. In the current study, PM 2.5 was also inversely associated with AHRR cg05575921 methylation in both smoking and non-smoking Taiwanese adults.
In the current study, PM 2.5 and smoking were also significantly associated with hypomethylation of F2RL3 cg03636183, another prominent smoking-related methylation site. The smoking-related F2RL3 cg03636183 hypomethylation observed in this study is in line with findings from previous studies [31,41,42,45,[61][62][63]. Note should be taken that AHRR cg05575921 remained the top significant hypomethylated CpG site in the current study. Moreover, its association with smoking and PM 2.5 remained significant even after adjusting for F2RL3 cg03636183.
Significant interactions between smoking and PM 2.5 on lung cancer and cardiovascular mortality [27][28][29] have been reported. However, we found no significant interactions between smoking and PM 2.5 on cg05575921 AHRR methylation. The smoking-related cg05575921 methylation levels were lower compared to the PM 2.5 -related levels. Despite this, the association of PM 2.5 with cg05575921 methylation cannot be neglected because exposure to air pollution is involuntary and affects everyone, unlike smoking which is individual behavior that can be modified [64]. To our knowledge, there are no available publications on the interaction of PM 2.5 with smoking on cg05575921 methylation. In view of this, we recommend further research in this area.
The relatively large sample size in addition to the adjusting for secondhand smoke exposure constitute the strengths of this study. However, the study is limited in that there was no available data to evaluate the functional correlation between mRNA gene expression and AHRR cg05575921 methylation. Moreover, all eligible Taiwan Biobank participants are individuals who have no personal history of cancer. Therefore, our results may not truly depict the pattern of cg05575921 methylation in individuals with cancer. Furthermore, since validated tools for individual exposure estimates are not available, the actual concentrations of PM 2.5 in individuals could not be determined. The use of nearby monitoring stations to estimate exposure to PM 2.5 might have resulted in exposure classification error. Smoking was self-reported and the possibility of recall bias cannot be ruled out. However, our findings were consistent with several previous findings on smoking and cg05575921 methylation [17,[31][32][33][34][35][36][37][38][39][40]49].

Conclusion
Smoking and PM 2.5 were independently associated with lower levels of AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2RL3 cg21911711 after multiple-comparison correction. The most hypomethylated CpG site was cg05575921 and its association with smoking and PM 2.5 was in a dose-dependent manner. Even though both smoking and PM 2.5 were inversely associated with cg05575921 methylation, the smokingrelated methylation levels were relatively low. Despite this, PM 2.5 -related methylation cannot be ignored because exposure to air pollution is involuntary and could affect everyone while smoking is a modifiable individual behavior. Our findings suggest that smoking and PM 2.5 may independently but not jointly affect AHRR cg05575921 methylation. Considering the remarkable harmful impact of PM 2.5 , smoking, and cg05575921 hypomethylation on cardiovascular and pulmonary health, measures should be put in place to reduce PM 2.5 pollution and individuals should be sensitized on the harmful effects of smoking.

Study participants and data sources
A total of 948 individuals (488 men and 460 women) were included in the current study. Genomic and demographic data including DNA methylation, smoking, residence, exercise, age, BMI, alcohol drinking, and secondhand smoke were obtained from the Taiwan Biobank Database The Taiwan Biobank project is a community-based cohort study aimed at collecting genetic and lifestyle data, alongside tracking the health of more than 200,000 ethnic Taiwanese adults for at least 10 years [65,66]. This national health resource contains 29 recruitment centers that are distributed all over the island [65]. Only Taiwanese adults aged 30-70 years who have no personal history of cancer are eligible for recruitment [65]. Relevant guidelines and regulations are followed during the recruitment process. All eligible participants signed a letter of consent before the data collection process.
Long-term and well-maintained air quality monitoring systems are a major basis of effective air quality protection and control. Air quality monitoring in Taiwan began in 1993 and is run by the Taiwan Air Quality Monitoring Network (TAQMN) of the Environmental Protection Administration (EPA) [67,68]. More information about this TAQMN has been described elsewhere [69]. Currently, there are about 77 fully automated air quality monitoring stations distributed throughout Taiwan which provide daily levels of air pollutants [68,70]. The TAQM N began providing regular daily mean measures of PM 2.5 since 2006 [70].

DNA Methylation determination
DNA methylation experiments and analyses were performed by the Health GeneTech Corporation in Taiwan. In brief, sodium bisulfite treatment of DNA extracted from whole blood was done using the EZ DNA Methylation Kit (Zymo Research, CA, USA). Methylation levels were measured using the Illumina Infinium MethylationEPIC BeadChip (Illumina Inc., San Diego, CA, USA) which detects over 850,000 CpG sites within the human genome [71,72]. Methylation levels were represented by β values which range from 0 (no methylation) to 1 (full methylation). To ensure good quality control, probes with poor detection (P > 0.05) and bead count < 3 were excluded, while background signals were subtracted. In addition, dye-bias across batches was corrected by normalization and outliers were removed using the median absolute deviation method. Finally, cell-type heterogeneity was corrected using the Reference-Free Adjustment for Cell-Type composition (ReFACTor) method [73].

Exposure and covariate assessment
We estimated exposure to PM 2.5 using participants' residential addresses which were grouped into 4 (northern, north-central, central, and southern area) as previously described [22,46]. Annual average concentrations of PM 2.5 from 2006 to 2011 were used in the final analysis.
Smoking habits were self-reported and participants were classified as current, former, or non-smokers. Covariates included exercise, sex, age, BMI, alcohol drinking habits (current, former and non-drinking), and secondhand smoke exposure. Smoking habits and covariates were defined using the same criteria described by Tantoh and colleagues [46].

Statistical analysis
Data management and statistical analyses were performed using the SAS 9.3 software (SAS Institute, Cary, NC). Continuous data were analyzed using the t test and expressed as mean ± standard error (SE), while categorical data were analyzed using the chi-square test and expressed as percentages (%). Multivariate linear regression models were used to determine the association of smoking and PM 2.5 with AHRR and F2RL3 CpG sites. The most significant Bonferroni-corrected CpG site was used for further analysis. Adjustments were made for covariates including exercise, sex, age, BMI, alcohol drinking, and secondhand smoke exposure.
Additional file 1: Table S1. AHRR and F2LR3 CpG sites and their association with smoking and PM 2.5 . Table S2. Multiple linear regression analysis showing the association of smoking and PM 2.5 with F2RL3 cg03636183 methylation in the study participants. Table S3. Multiple linear regression analysis showing the association of smoking and PM 2.5 with F2RL3 cg03636183 methylation in the study participants stratified by sex. Table S4. Multiple linear regression analysis showing the association of smoking and living in PM 2.5 areas with F2RL3 cg03636183 methylation in the study participants. Table S5. Multiple linear regression analysis showing the association of smoking and living in PM 2.5 areas and F2RL3 cg03636183 methylation in the study participants stratified by sex.

Availability of data and materials
The data that support the findings of this study are available from Taiwan Biobank but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Taiwan Biobank.