Furlong Melissa A, Paul Kimberly C, Yan Qi, Chuang Yu-Hsuan, Cockburn Myles G, Bronstein Jeff M, Horvath Steve, Ritz Beate
Department of Community, Environment, and Policy, University of Arizona Mel and Enid Zuckerman College of Public Health, Tucson, AZ, USA.
Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA.
Int J Hyg Environ Health. 2020 Aug;229:113569. doi: 10.1016/j.ijheh.2020.113569. Epub 2020 Jul 14.
Pyrethroid pesticide use is increasing worldwide, although the full extent of associated health effects is unknown. An epigenome-wide association study (EWAS) with exploratory pathway analysis may help identify potential pyrethroid-related health effects.
We performed an exploratory EWAS of chronic ambient pyrethroid exposure using control participants' blood in the Parkinson's Environment and Genes Study in the Central Valley of California (N = 237). We estimated associations of living and working near agricultural pyrethroid pesticide applications in the past 5 years (binary) with site-specific differential methylation, and used a false discovery rate (FDR) cut off of 0.05 for significance. We controlled for age, sex, education, cell count, and an ancestral marker for Hispanic ethnicity. We normalized methylation values for Type I/II probe bias using Beta-Mixture Quantile (BMIQ) normalization, filtered out cross-reactive probes, and evaluated for remaining bias with Surrogate Variable Analysis (SVA). We also evaluated the effects of controlling for cell count and normalizing for Type I/II probe bias by comparing changes in effect estimates and p-values for the top hits across BMIQ and GenomeStudio normalization methods, and controlling for cell count. To facilitate broader interpretation, we annotated genes to the CpG sites and performed gene set overrepresentation analysis, using genes annotated to CpG sites that were associated with pyrethroids at a raw p < 0.05, and controlling for background representation of CpG sites on the chip. We did this for both a biological process context (Gene Ontology terms) using missMethyl, and a disease set context using WebGestalt. For these gene set overrepresentation analyses we also used an FDR cut off of 0.05 for significance of gene sets.
After controlling for cell count and applying BMIQ normalization, 4 CpG sites were differentially methylated in relation to pyrethroid exposures. When using GenomeStudio's Illumina normalization, 415 CpG sites were differentially methylated, including all four identified with the BMIQ method. In the gene set overrepresentation analyses, we identified 6 GO terms using BMIQ normalization, and 76 using Illumina normalization, including the 6 identified by BMIQ. For disease sets, we identified signals for Alzheimer's disease, leukemia and several other cancers, diabetes, birth defects, and other diseases, for both normalization methods. We identified minimal changes in effect estimates after controlling for cell count, and controlling for cell count generally weakened p-values. BMIQ normalization, however, resulted in different beta coefficients and weakened p-values.
Chronic ambient pyrethroid exposure is associated with differential methylation at CpG sites that annotate to a wide variety of disease states and biological mechanisms that align with prior research. However, this EWAS also implicates several novel diseases for future investigation, and highlights the relative importance of different background normalization methods in identifying associations.
拟除虫菊酯类农药在全球的使用量正在增加，但其相关健康影响的全部程度尚不清楚。一项进行探索性通路分析的全表观基因组关联研究（EWAS）可能有助于识别拟除虫菊酯相关的潜在健康影响。
我们在加利福尼亚中央山谷的帕金森病环境与基因研究中，使用对照参与者的血液进行了一项关于慢性环境拟除虫菊酯暴露的探索性EWAS（N = 237）。我们估计了过去5年内在农业拟除虫菊酯农药施用地点附近居住和工作（二元变量）与位点特异性差异甲基化之间的关联，并使用错误发现率（FDR）临界值0.05来确定显著性。我们对年龄、性别、教育程度、细胞计数以及西班牙裔种族的祖先标记进行了控制。我们使用β混合分位数（BMIQ）归一化方法对I/II型探针偏差的甲基化值进行了归一化，过滤掉了交叉反应探针，并通过替代变量分析（SVA）评估了剩余偏差。我们还通过比较BMIQ和GenomeStudio归一化方法以及控制细胞计数后顶级命中的效应估计值和p值的变化，评估了控制细胞计数和对I/II型探针偏差进行归一化的效果。为便于更广泛的解释，我们将基因注释到CpG位点，并进行基因集过度表达分析，使用注释到与拟除虫菊酯相关的CpG位点的基因，原始p值<0.05，并控制芯片上CpG位点的背景代表性。我们使用missMethyl在生物学过程背景（基因本体术语）下以及使用WebGestalt在疾病集背景下进行了此操作。对于这些基因集过度表达分析，我们也使用FDR临界值0.05来确定基因集的显著性。
在控制细胞计数并应用BMIQ归一化后，4个CpG位点与拟除虫菊酯暴露存在差异甲基化。使用GenomeStudio的Illumina归一化时，415个CpG位点存在差异甲基化，包括通过BMIQ方法鉴定出的所有4个位点。在基因集过度表达分析中，我们使用BMIQ归一化鉴定出6个基因本体术语，使用Illumina归一化鉴定出76个，包括通过BMIQ鉴定出的6个。对于疾病集，两种归一化方法均鉴定出了阿尔茨海默病、白血病和其他几种癌症、糖尿病、出生缺陷及其他疾病的信号。控制细胞计数后，我们发现效应估计值变化极小，且控制细胞计数通常会削弱p值。然而，BMIQ归一化导致了不同的β系数并削弱了p值。
慢性环境拟除虫菊酯暴露与CpG位点的差异甲基化有关，这些位点注释到与先前研究一致的多种疾病状态和生物学机制。然而，这项EWAS也暗示了几种未来需进一步研究的新疾病，并突出了不同背景归一化方法在识别关联中的相对重要性。
