Nwanaji-Enwerem Jamaji C, Colicino Elena, Trevisi Letizia, Kloog Itai, Just Allan C, Shen Jincheng, Brennan Kasey, Dereix Alexandra, Hou Lifang, Vokonas Pantel, Schwartz Joel, Baccarelli Andrea A
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Environ Epigenet. 2016 Apr;2(2). doi: 10.1093/eep/dvw006. Epub 2016 Jun 12.
Ambient particles have been shown to exacerbate measures of biological aging; yet, no studies have examined their relationships with DNA methylation age (DNAm-age), an epigenome-wide DNA methylation based predictor of chronological age.
We examined the relationship of DNAm-age with fine particulate matter (PM), a measure of total inhalable particle mass, and black carbon (BC), a measure of particles from vehicular traffic.
We used validated spatiotemporal models to generate 1-year PM and BC exposure levels at the addresses of 589 older men participating in the VA Normative Aging Study with 1-3 visits between 2000 and 2011 ( = 1032 observations). Blood DNAm-age was calculated using 353 CpG sites from the Illumina HumanMethylation450 BeadChip. We estimated associations of PM and BC with DNAm-age using linear mixed effects models adjusted for age, lifestyle/environmental factors, and aging-related diseases.
After adjusting for covariates, a 1-µg/m increase in PM (95% CI: 0.30, 0.75, <0.0001) was significantly associated with a 0.52-year increase in DNAm-age. Adjusted BC models showed similar patterns of association (β = 3.02, 95% CI: 0.48, 5.57, = 0.02). Only PM (β = 0.54, 95% CI: 0.24, 0.84, = 0.0004) remained significantly associated with DNAm-age in two-particle models. Methylation levels from 20 of the 353 CpGs contributing to DNAm-age were significantly associated with PM levels in our two-particle models. Several of these CpGs mapped to genes implicated in lung pathologies including , and .
Our results support an association of long-termambient particle levels with DNAm-age and suggest that DNAm-age is a biomarker of particle-related physiological processes.
环境颗粒物已被证明会加剧生物衰老指标;然而,尚无研究考察其与DNA甲基化年龄(DNAm-age)的关系,DNAm-age是一种基于全基因组DNA甲基化的实际年龄预测指标。
我们考察了DNAm-age与细颗粒物(PM,可吸入颗粒物总量指标)以及黑碳(BC,车辆交通产生的颗粒物指标)之间的关系。
我们使用经过验证的时空模型,在参与退伍军人规范衰老研究的589名老年男性的住址处生成1年的PM和BC暴露水平,这些男性在2000年至2011年间接受了1至3次访视(n = 1032次观察)。使用Illumina HumanMethylation450 BeadChip芯片上的353个CpG位点计算血液DNAm-age。我们使用线性混合效应模型估计PM和BC与DNAm-age的关联,并对年龄、生活方式/环境因素以及与衰老相关的疾病进行了调整。
在对协变量进行调整后,PM每增加1 μg/m³(95% CI:0.30,0.75,P < 0.0001)与DNAm-age增加0.52岁显著相关。调整后的BC模型显示出类似的关联模式(β = 3.02,95% CI:0.48,5.57,P = 0.02)。在双颗粒物模型中,只有PM(β = 0.54,95% CI:0.24,0.84,P = 0.0004)与DNAm-age仍显著相关。在我们的双颗粒物模型中,构成DNAm-age的353个CpG中有20个的甲基化水平与PM水平显著相关。其中几个CpG映射到与肺部疾病相关的基因,包括[具体基因名称未给出]。
我们的结果支持长期环境颗粒物水平与DNAm-age之间存在关联,并表明DNAm-age是与颗粒物相关生理过程的生物标志物。