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