On Aging: Analyses of Long-Term Fine Particulate Air Pollution Exposure, Genetic Variants, and Blood DNA Methylation Age in the Elderly

Abstract

Human aging is often accompanied by the development of chronic disease. Research has identified molecular processes that are shared by aging-related diseases, and it is widely believed that pre-clinical changes in these aging-related molecular processes (i.e. measures of “biological age”) may be more informative of morbidity and mortality risks than simple chronological age. DNA methylation age (DNAm-age) is a DNA methylation based predictor of chronological age and a novel measure of biological age. Studies have demonstrated associations of DNAm-age with a host of aging-related health outcomes including all-cause mortality, frailty, cancer, and Parkinson’s disease. However, very few studies have examined DNAm-age relationships with aging risk factors. Fine particulate air pollution (PM2.5) is a well-documented aging risk factor and is considered the world’s largest singular environmental health risk. This body of work utilized multivariate linear mixed effects models and a well-established aging cohort, the United States Veterans Affairs Normative Aging Study (NAS), to examine the relationship of long-term PM2.5 exposure levels with DNAm-age. After determining the direct relationship of PM2.5 with DNAm-age in the NAS, we determined which of five major PM2.5 component species (ammonium, elemental carbon, organic carbon, sulfate, and nitrate) were most associated with DNAm-age. Finally, we examined if normal genetic variation in aging-related physiological processes (endothelial function, metal processing, oxidative stress, mitochondrial genome physiology, and microRNA processing) impacted the relationships of PM2.5 and its component species with DNAm-age. We found that PM2.5 was significantly, positively associated with DNAm-age and that sulfate and ammonium were the component species most associated with DNAm-age. Moreover, endothelial function, mitochondrial genome, and microRNA processing variants significantly modified the association of PM2.5 with DNAm-age. DNAm-age was also significantly associated with a number of serum measures related to these effect modifiers including mitochondrial DNA copy number, intercellular adhesion molecule (ICAM), and vascular cell adhesion molecule (VCAM). In all, our studies demonstrate a novel association of PM2.5 with DNAm-age. Our studies also suggest that DNAm-age has robust relationships with endothelial function, mitochondrial physiology, and miRNA processing – all of which are processes known to play a role in aging-related diseases. Still, future studies will be necessary to further understand what DNAm-age represents and how it can best be used as a biomarker.