Dataset Information

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM_2.5 concentrations.

ABSTRACT:

Background

DNA methylation is associated with cancer, metabolic, neurological, and autoimmune disorders. Hypomethylation of aryl hydrocarbon receptor repressor (AHRR) especially at cg05575921 is associated with smoking and lung cancer. Studies on the association between AHRR methylation at cg05575921 and sources of polycyclic aromatic hydrocarbon (PAH) other than smoking are limited. The aim of our study was to assess the pattern of blood DNA methylation at cg05575921 in non-smoking Taiwanese adults living in areas with different PM_2.5 levels.

Methods

Data on blood DNA methylation, smoking, and residence were retrieved from the Taiwan Biobank dataset (2008-2015). Current and former smokers, as well as individuals with incomplete information were excluded from the current study. The final analysis included 708 participants (279 men and 429 women) aged 30-70?years. PM_2.5 levels have been shown to increase as one moves from the northern through central towards southern Taiwan. Based on this trend, the study areas were categorized into northern, north-central, central, and southern regions.

Results

Living in PM_2.5 areas was associated with lower methylation levels: compared with the northern area (reference area), living in north-central, central, and southern areas was associated with lower methylation levels at cg05575921. However, only methylation levels in those living in central and southern areas were significant (? = -?0.01003, P = 0.009 and ? = -?0.01480, P < 0.001, respectively. Even though methylation levels in those living in the north-central area were not statistically significant, the test for linear trend was significant (P < 0.001). When PM_2.5 was included in the regression model, a unit increase in PM_2.5 was associated with 0.00115 (P < 0.001) lower cg05575921 methylation levels.

Conclusion

Living in PM_2.5 areas was inversely associated with blood AHRR methylation levels at cg05575921. The methylation levels were lowest in participants residing in southern followed by central and north-central areas. Moreover, when PM_2.5 was included in the regression model, it was inversely associated with methylation levels at cg05575921. Blood methylation at cg05575921 (AHRR) in non-smokers might indicate different exposures to PM_2.5 and lung cancer which is a PM_2.5-related disease.

SUBMITTER: Tantoh DM

PROVIDER: S-EPMC6503351 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM<sub>2.5</sub> concentrations.

Tantoh Disline Manli DM Lee Kuan-Jung KJ Nfor Oswald Ndi ON Liaw Yi-Chia YC Lin Chin C Chu Hou-Wei HW Chen Pei-Hsin PH Hsu Shu-Yi SY Liu Wen-Hsiu WH Ho Chen-Chang CC Lung Chia-Chi CC Wu Ming-Fang MF Liaw Yi-Ching YC Debnath Tonmoy T Liaw Yung-Po YP

Clinical epigenetics 20190506 1

<h4>Background</h4>DNA methylation is associated with cancer, metabolic, neurological, and autoimmune disorders. Hypomethylation of aryl hydrocarbon receptor repressor (AHRR) especially at cg05575921 is associated with smoking and lung cancer. Studies on the association between AHRR methylation at cg05575921 and sources of polycyclic aromatic hydrocarbon (PAH) other than smoking are limited. The aim of our study was to assess the pattern of blood DNA methylation at cg05575921 in non-smoking Taiw ...[more]

PMID: 31060609

Similar Datasets

Project description:BackgroundPolycyclic 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.MethodsDNA 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).ResultsSmoking 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).ConclusionSmoking 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.

Project description:Fine particulate matter is considered to be the most significant ambient air pollutant in terms of potential health impacts. Therefore, it is important that regulators are able to accurately assess the exposure of populations to PM10 and PM2.5 across municipal areas. We report on the practicalities of using a laser light scattering portable particulate monitor (Turnkey Instruments DustMate), in combination with a GPS, to map PM10 and PM2.5 concentrations on city-wide scales in Newcastle upon Tyne/Gateshead (UK), during a series of walking surveys. A heated inlet is necessary to remove moisture droplets from the sampled air prior to analysis by the instrument, though this also results in the loss of volatile particulate components, particularly from the PM2.5 fraction. A co-location calibration study was carried out with a reference urban background Tapered Element Oscillating Micro-Balance/Filter Dynamics Measuring System (TEOM-FDMS) system in Newcastle that is part of the UK's Automatic Urban and Rural Network (AURN) of air quality monitoring stations. For PM10, orthogonal regression of the DustMate against TEOM-FDMS data gave a slope and intercept of 1.02 ± 0.06 and -3.7 ± 1.2, respectively (R2 = 0.73), whereas for PM2.5, the respective values were 0.78 ± 0.06 and -0.63 ± 0.55 (R2 = 0.79). These parameters are comparable to literature calibration studies using this technology. There was good agreement between simultaneous samples taken using two DustMate instruments: for PM10, a slope and intercept of 1.05 ± 0.03 and 0.36 ± 0.5, respectively (R2 = 0.73), were obtained, whereas for the PM2.5, the respective values were 0.79 ± 0.01 and 0.19 ± 0.06 (R2 = 0.86). Correction factors based on the slope and intercepts obtained from the calibration exercise were applied to raw data collected from the DustMate. An annually-normalised correction procedure was then used to account for different background particulate concentrations on different sampling days. These corrected PM10 and PM2.5 concentrations and corresponding GPS coordinates were displayed on a base map using Google Fusion Tables and Google Earth Professional. Almost all areas surveyed in Newcastle/Gateshead were well below the EU Air Quality Standards for PM10 and PM2.5.

Project description:BackgroundCigarette smoking and particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) are major preventable cardiovascular mortality and morbidity promoters. Their joint role in metabolic syndrome (MS) pathogenesis is unknown. We determined the risk of MS based on PM2.5 and cigarette smoking in Taiwanese adults.MethodsThe study included 126,366 Taiwanese between 30 and 70 years old with no personal history of cancer. The Taiwan Biobank (TWB) contained information on MS, cigarette smoking, and covariates, while the Environmental Protection Administration (EPA), Taiwan, contained the PM2.5 information. Individuals were categorized as current, former, and nonsmokers. PM2.5 levels were categorized into quartiles: PM2.5 ≤ Q1, Q1 < PM2.5 ≤ Q2, Q2 < PM2.5 ≤ Q3, and PM2.5 > Q3, corresponding to PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3.ResultsThe prevalence of MS was significantly different according to PM2.5 exposure (p-value = 0.0280) and cigarette smoking (p-value < 0.0001). Higher PM2.5 levels were significantly associated with a higher risk of MS: odds ratio (OR); 95% confidence interval (CI) = 1.058; 1.014-1.104, 1.185; 1.134-1.238, and 1.149; 1.101-1.200 for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. The risk of MS was significantly higher among former and current smokers with OR; 95% CI = 1.062; 1.008-1.118 and 1.531; 1.450-1.616, respectively, and a dose-dependent p-value < 0.0001. The interaction between both exposures regarding MS was significant (p-value = 0.0157). Stratification by cigarette smoking revealed a significant risk of MS due to PM2.5 exposure among nonsmokers: OR (95% CI) = 1.074 (1.022-1.128), 1.226 (1.166-1.290), and 1.187 (1.129-1.247) for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. According to PM2.5 quartiles, current smokers had a higher risk of MS, regardless of PM2.5 levels (OR); 95% CI = 1.605; 1.444-1.785, 1.561; 1.409-1.728, 1.359; 1.211-1.524, and 1.585; 1.418-1.772 for PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. After combining both exposures, the group, current smokers; PM2.5 > 38.205 μg/m3 had the highest odds (1.801; 95% CI =1.625-1.995).ConclusionPM2.5 and cigarette smoking were independently and jointly associated with a higher risk of MS. Stratified analyses revealed that cigarette smoking might have a much higher effect on MS than PM2.5. Nonetheless, exposure to both PM2.5 and cigarette smoking could compound the risk of MS.

Dataset Information

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM_2.5 concentrations.

Background

Methods

Results

Conclusion

Publications

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM<sub>2.5</sub> concentrations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM2.5 concentrations.

Background

Methods

Results

Conclusion

Publications

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM<sub>2.5</sub> concentrations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM_2.5 concentrations.