Background: Epigenetic age, as defined by DNA methylation, may be influenced by air pollution exposure.
Objective: To evaluate the relationship between NO2, particulate matter (PM), PM components and accelerated epigenetic age.
Methods: In a sample of non-Hispanic white women living in the contiguous U.S. (n = 2747), we estimated residential exposure to PM2.5, PM10 and NO2 using a model incorporating land-use regression and kriging. Predictive k-means was used to assign participants to clusters representing different PM2.5 component profiles. We measured DNA methylation (DNAm) in blood using the Illumina's Infinium HumanMethylation450 BeadChip and calculated DNAm age using the Hannum, Horvath and Levine epigenetic clocks. Age acceleration was defined based on residuals after regressing DNAm age on chronological age. We estimated associations between interquartile range (IQR) increases in pollutants and age acceleration using linear regression. For PM2.5, we stratified by cluster membership. We examined epigenome-wide associations using robust linear regression models corrected with false discovery rate q-values.
Results: NO2 was inversely associated with age acceleration using the Hannum clock (β = -0.24, 95% CI: -0.47, -0.02). No associations were observed for PM10. For PM2.5, the association with age acceleration varied by PM2.5 component cluster. For example, with the Levine clock, an IQR increase in PM2.5 was associated with an over 6-year age acceleration in a cluster that has relatively high fractions of crustal elements relative to overall PM2.5 (β = 6.57, 95% CI: 2.68, 10.47), and an almost 2-year acceleration in a cluster characterized by relatively low sulfur fractions (β = 1.88, 95% CI: 0.51, 3.25). In a cluster distinguished by lower relative nitrate concentrations, PM2.5 was inversely associated with age acceleration (β = -1.33, 95% CI: -2.43, -0.23). Across the epigenome, NO2 was associated with methylation at 2 CpG sites.
Conclusion: Air pollution was associated with epigenetic age, a marker of mortality and disease risk, among certain PM2.5 component profiles.
Keywords: Air pollution; Breast cancer; Clustering; Mixtures; Particulate matter.
Published by Elsevier Ltd.