Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec;9(12):1529-1542.
doi: 10.2217/epi-2017-0094. Epub 2017 Nov 6.

miRNA Processing Gene Polymorphisms, Blood DNA Methylation Age and Long-Term Ambient PM 2.5 Exposure in Elderly Men

Affiliations
Free PMC article

miRNA Processing Gene Polymorphisms, Blood DNA Methylation Age and Long-Term Ambient PM 2.5 Exposure in Elderly Men

Jamaji C Nwanaji-Enwerem et al. Epigenomics. .
Free PMC article

Abstract

Aim: We tested whether genetic variation in miRNA processing genes modified the association of PM2.5 with DNA methylation (DNAm) age.

Patients & methods: We conducted a repeated measures study based on 552 participants from the Normative Aging Study with multiple visits between 2000 and 2011 (n = 940 visits). Address-level 1-year PM2.5 exposures were estimated using the GEOS-chem model. DNAm-age and a panel of 14 SNPs in miRNA processing genes were measured from participant blood samples.

Results & conclusion: In fully adjusted linear mixed-effects models, having at least one copy of the minor rs4961280 [AGO2] allele was associated with a lower DNAm-age (β = -1.13; 95% CI: -2.26 to -0.002). However, the association of PM2.5 with DNAm-age was significantly (Pinteraction = 0.01) weaker in homozygous carriers of the major rs4961280 [AGO2] allele (β = 0.38; 95% CI: -0.20 to 0.96) when compared with all other participants (β = 1.58; 95% CI: 0.76 to 2.39). Our results suggest that miRNA processing impacts DNAm-age relationships. Graphical abstract: miRNA processing AGO2 polymorphism (rs4961280) modifies the association of long-term ambient fine particle exposure with blood DNA methylation age [Formula: see text] The graph depicts lines from a fully adjusted linear regression model with fine particle exposure levels ranging from the tenth to the ninetieth percentile, all other continuous variables held constant at their means, and all other categorical variables held at their most frequent level.

Keywords: AGO2; PM2.5; SNPs; air pollution; epigenetic aging; miRNA.

Conflict of interest statement

Financial & competing interests disclosure

This work was supported by grants from the National Institute of Environmental Health Sciences (NIEHS) (R01ES021733 and R01ES025225). Other support comes from NIEHS grants (ES015172, ES014663, ES020010, P30ES009089 and P30ES000002); Environmental Protection Agency grants (RD832416 and RD83587201); and a National Heart, Lung, and Blood Institute grant (2T32HL007118-41). Additional support was provided by the US Department of Agriculture, Agricultural Research Service (contract 53-K06–510). The US Department of Veterans Affairs Normative Aging Study is supported by the Cooperative Studies Program/ERIC, US Department of Veterans Affairs, and is a research component of the Massachusetts Veterans Epidemiology Research and Information Center. The views expressed in this paper are those of the authors and do not necessarily represent the views of the US Department of Veterans Affairs. JC Nwanaji-Enwerem is also supported by an NIH/NIA Ruth L Kirschstein National Research Service Award (1 F31AG056124–01A1). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Figures

<b>Figure 1.</b>
Figure 1.. Difference in DNA methylation age for one interquartile range increase in 1-year particle exposure levels comparing participants with and without a homozygous major variant genotype for AGO2, DROSHA, GEMIN4 and TARBP2 in fully adjusted linear mixed-effects models.
<b>Figure 2.</b>
Figure 2.. Difference in DNA methylation age for one interquartile range increase in 1-year particle exposure (ammonium and sulfate) levels comparing participants with and without a homozygous major variant genotype for AGO2 and DROSHA in fully adjusted linear mixed-effects models.
<b>Figure 3.</b>
Figure 3.. Difference in DNA methylation age for one interquartile range increase in 1-year particle exposure (PM2.5 and ammonium) levels comparing participants of homozygous major variant (n = 526), heterozygous (n = 257) and homozygous minor variant genotypes (n = 25) for AGO2 in fully adjusted linear mixed-effects models.
*p-value for the test of linear trend across genotypes was based on a linear mixed-effects regression model where the three AGO2 genotypes were fit as a continuous measure.
<b>Figure 4.</b>
Figure 4.. Curated network map depicting relationships of AGO2, DROSHA, GEMIN4 and TARBP2 with genes that contribute component CpG methylation to DNA methylation age.
Each of the elastic net-selected genes is surrounded by a circle of related genes that contribute CpG methylation to the DNAm-age metric. Solid lines that connect genes represent co-expression. Dashed lines that connect genes represent physical interactions. Squiggly lines that connect genes represent genetic interactions.

Similar articles

See all similar articles

Cited by 7 articles

See all "Cited by" articles

Publication types

LinkOut - more resources

Feedback