The zip file contains supplementary data for the publication - Genome-Wide DNA Methylation in Peripheral Blood and Long-Term Exposure to Source-Specific Transportation Noise and Air Pollution: The SAPALDIA Study, accepted for publication in Environmental Health Perspectives (DOI: 10.1289/EHP6174). The description of the files are noted below: 1. Readme File for SAPALDIA Noise and Air Pollution EWAS Single Exposure.zip This zip file contains all the results of the association between source-specific transportation noise (aircraft, railway and road traffic), air pollution (NO2 and PM2.5), and genome-wide DNA methylation, derived from multi-exposure models. SAPALDIA_EWAS_SingleExposure_AircraftLden.txt contains the results for aircraft noise SAPALDIA_EWAS_SingleExposure_RailwayLden.txt contains the results for railway noise SAPALDIA_EWAS_SingleExposure_RoadtrafficLden.txt contains the results for road traffic noise SAPALDIA_EWAS_SingleExposure_NO2.txt contains the results for nitrogen dioxide SAPALDIA_EWAS_SingleExposure_PM25.txt contains the results for fine particulate matter General footnote for all files:SAPALDIA: Swiss cohort study on air pollution and lung and heart diseases in adults. CpG: Cytosine-phosphate-Guanine. CHR: chromosome. SE: standard error. Lden: day-evening-night noise level. NO2: nitrogen dioxide. PM2.5: particulate matter with aerodynamic diameter <2.5 µm. Beta coefficients represent increase or decrease in DNA methylation per 10 dB increase in aircraft, railway or road traffic Lden or 10 µg/m3 increase in NO2 or PM2.5. All estimates were from single exposure epigenome-wide linear mixed models, with random intercept at the level of participant. Each model was adjusted for age, sex, educational level, area, and neighborhood socio-economic status, greenness index, smoking status and pack years, exposure to passive smoke, consumption of fruits, vegetables and alcohol, nested study, asthma status, survey, source-specific noise truncation indicator (for Lden models) and leukocyte composition. In a preliminary step, DNA methylation β-values were regressed on the Illumina control probe-derived first 30 principal components to correct for correlation structures and technical bias, and residuals of these regressions covering 430,477 CpGs were used as the technical bias-corrected methylation level at the CpG sites. Extreme values of the residuals (lying beyond three times the interquartile range below the first quartile and above the third quartile at each CpG site) were replaced with their corresponding detection threshold value (“modified winsorization”). The “winsorized” data were then used as the dependent variables in the epigenome-wide association study. 2. Readme File for SAPALDIA Noise and Air Pollution EWAS Multi Exposure.zip This zip file contains all the results of the association between source-specific transportation noise (aircraft, railway and road traffic), air pollution (NO2 and PM2.5), and genome-wide DNA methylation, derived from multi-exposure models. SAPALDIA_EWAS_MultiExposure_AircraftLden.txt contains the results for aircraft noise SAPALDIA_EWAS_MultiExposure_RailwayLden.txt contains the results for railway noise SAPALDIA_EWAS_MultiExposure_RoadtrafficLden.txt contains the results for road traffic noise SAPALDIA_EWAS_MultiExposure_NO2.txt contains the results for nitrogen dioxide SAPALDIA_EWAS_MultiExposure_PM25.txt contains the results for fine particulate matter General table footnotes: SAPALDIA: Swiss cohort study on air pollution and lung and heart diseases in adults. CpG: Cytosine-phosphate-Guanine. CHR: chromosome. SE: standard error. Lden: day-evening-night noise level. NO2: nitrogen dioxide. PM2.5: particulate matter with aerodynamic diameter <2.5 µm. Beta coefficients represent increase or decrease in DNA methylation per 10 dB increase in aircraft, railway or road traffic Lden or 10 µg/m3 increase in NO2 or PM2.5. All estimates were from multi-exposure epigenome-wide linear mixed models, with random intercept at the level of participant, and were adjusted for age, sex, educational level, area, and neighborhood socio-economic status, greenness index, smoking status and pack years, exposure to passive smoke, consumption of fruits, vegetables and alcohol, nested study, asthma status, survey, source-specific noise truncation indicator and leukocyte composition. Multi-exposure models included all five exposures (Aircraft, railway, road traffic Lden and respective truncation indicators, NO2 and PM2.5) at the same time. In a preliminary step, DNA methylation β-values were regressed on the Illumina control probe-derived first 30 principal components to correct for correlation structures and technical bias, and residuals of these regressions covering 430,477 CpGs were used as the technical bias-corrected methylation level at the CpG sites. Extreme values of the residuals (lying beyond three times the interquartile range below the first quartile and above the third quartile at each CpG site) were replaced with their corresponding detection threshold value (“modified winsorization”). The “winsorized” data were then used as the dependent variables in the epigenome-wide association study.

This work was supported by the Swiss National Science Foundation, SNF-SAPALDIA (grants numbers 33CS30-148470/1, 33CSCO-134276/1, 33CSCO-108796, 324730_135673, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099, PMPDP3_129021/1, PMPDP3_141671/1); SNF-SiRENE (grant number CRSII3_147635); the European Commission Horizon 2020 research and innovation programme (ALEC study; grant number 633212); grant FP7 of the European Commission "Enhanced exposure 36 assessment and -omic profiling for high priority environmental exposures in Europe" (EXPOsOMICS study; grant number 308610)