Changes in DNA methylation over the growing season differ between North Carolina farmworkers and non-farmworkers.
Changes in DNA methylation over the growing season differ between North Carolina farmworkers and non-farmworkers.
复制标题
DOI：
10.1007/s00420-016-1148-0
复制
发表时间：
2016-10
影响因子：
3
通讯作者：
Arcury TA
中科院分区：
文献类型：
--
作者：
Howard TD;Hsu FC;Chen H;Quandt SA;Talton JW;Summers P;Arcury TA
对农场工人的职业风险，特别是长期接触农药，是一个公认的环境和与工作有关的健康问题。表观遗传学最近被证明对许多复杂的疾病和特征有贡献，包括认知功能和临床前神经退行性疾病的测量。我们试图确定在农场工人和非农场工人人群之间是否存在DNA甲基化的变化，并确定最有可能参与这些变化的基因。PACE4是一个以社区为基础的参与性研究项目，比较拉丁裔移民农场工人和非农场工人体力劳动者的职业暴露情况，从中选择了83名农场工人和60名非农场工人。在2012年生长季节开始和结束时，使用Infinium HumanMethylation450头芯片进行DNA甲基化测量。使用Bonferroni调整来确定显著的发现（基于485,000个测试的甲基化位点，p=1.03 × 10−7），尽管使用不太严格的标准（即p≤1 × 10−6）来确定感兴趣的位点。使用表达数量性状位点（eQTL）数据库来帮助鉴定每个相关甲基化位点最可能的功能基因。位于72个基因或其附近的36个CpG位点的甲基化在两组之间存在差异（p≤1 × 10−6）。两组之间的差异通常是由于农场工人的甲基化增加，而非农场工人的甲基化略有减少。在几个生物学通路中观察到富集，包括参与免疫反应的通路，以及生长激素信号通路，BRCA1在DNA损伤反应中的作用，B淋巴细胞中的p70S6K信号通路和PI3K信号通路。我们确定了36个CpG位点的DNA甲基化在生长季节的显著变化，这在农场工人和非农场工人之间存在差异。主要途径包括免疫相关（HLA）过程，以及许多不同的生物系统。需要进一步的研究来确定哪些暴露或行为导致了观察到的变化，以及这些变化是否最终导致了该人群中与疾病相关的表型。
The occupational risk to farmworkers, particularly chronic exposure to pesticides, is an acknowledged environmental and work-related health problem. Epigenetics has recently been shown to contribute to a number of complex diseases and traits, including measures of cognitive function and preclinical neurodegenerative disease. We sought to determine if changes in DNA methylation existed between farmworker and non-farmworker populations, and to identify the genes most likely involved in those changes. Eighty-three farmworkers and 60 non-farmworkers were selected from PACE4, a community-based, participatory research project comparing occupational exposures between immigrant Latino farmworker and non-farmworker manual workers. Measurements of DNA methylation were performed with the Infinium HumanMethylation450 BeadChip, at the beginning and end of the 2012 growing season. Bonferroni adjustment was used to identify significant findings (p=1.03 × 10−7, based on 485,000 tested methylation sites), although less stringent criteria (i.e., p≤1 × 10−6) were used to identify sites of interest. Expression quantitative trait locus (eQTL) databases were used to help identify the most likely functional genes for each associated methylation site. Methylation at 36 CpG sites, located in or near 72 genes, differed between the two groups (p≤1 × 10−6). The difference between the two groups was generally due to an increase in methylation in the farmworkers, and a slight decrease in methylation in the non-farmworkers. Enrichment was observed in several biological pathways, including those involved in the immune response, as well as Growth Hormone Signaling, Role of BRCA1 in DNA Damage Response, p70S6K signaling, and PI3K Signaling in B Lymphocytes. We identified considerable changes in DNA methylation at 36 CpG sites over the growing season that differed between farmworkers and non-farmworkers. Dominant pathways included immune-related (HLA) processes, as well as a number of diverse biological systems. Further studies are necessary to determine which exposures or behaviors are responsible for the observed changes, and whether these changes eventually lead to disease related phenotypes in this population.
登录
查看更多内容
影响因子：
30.8
作者：
Westra, Harm-Jan;Peters, Marjolein J.;Esko, Tonu;Yaghootkar, Hanieh;Schurmann, Claudia;Kettunen, Johannes;Christiansen, Mark W.;Fairfax, Benjamin P.;Schramm, Katharina;Powell, Joseph E.;Zhernakova, Alexandra;Zhernakova, Daria V.;Veldink, Jan H.;Van den Berg, Leonard H.;Karjalainen, Juha;Withoff, Sebo;Uitterlinden, Andre G.;Hofman, Albert;Rivadeneira, Fernando;'t Hoen, Peter A. C.;Reinmaa, Eva;Fischer, Krista;Nelis, Mari;Milani, Lili;Melzer, David;Ferrucci, Luigi;Singleton, Andrew B.;Hernandez, Dena G.;Nalls, Michael A.;Homuth, Georg;Nauck, Matthias;Radke, Doerte;Voelker, Uwe;Perola, Markus;Salomaa, Veikko;Brody, Jennifer;Suchy-Dicey, Astrid;Gharib, Sina A.;Enquobahrie, Daniel A.;Lumley, Thomas;Montgomery, Grant W.;Makino, Seiko;Prokisch, Holger;Herder, Christian;Roden, Michael;Grallert, Harald;Meitinger, Thomas;Strauch, Konstantin;Li, Yang;Jansen, Ritsert C.;Visscher, Peter M.;Knight, Julian C.;Psaty, Bruce M.;Ripatti, Samuli;Teumer, Alexander;Frayling, Timothy M.;Metspalu, Andres;van Meurs, Joyce B. J.;Franke, Lude
通讯作者：
Franke, Lude
DOI：
10.1097/01.jom.0000058339.05741.0c
发表时间：
2003-03-01
影响因子：
3.2
作者：
Mills, PK;Yang, R
通讯作者：
Yang, R
影响因子：
10.4
作者：
Fenske, RA;Lu, CS;Kissel, JC
通讯作者：
Kissel, JC
影响因子：
10.4
作者：
Kamel F;Hoppin JA
通讯作者：
Hoppin JA
beta混合分位数归一化方法，用于校正Illumina Infinium 450 K DNA甲基化数据中的探针设计偏差。
DOI：
10.1093/bioinformatics/bts680
发表时间：
2013-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Teschendorff AE;Marabita F;Lechner M;Bartlett T;Tegner J;Gomez-Cabrero D;Beck S
通讯作者：
Beck S