Division of Environmental Health Sciences, School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, Berkeley, CA, 94720, USA.
Graduate Group in Biostatistics, University of California, Berkeley, Berkeley, CA, USA.
Environ Health. 2021 Jul 9;20(1):79. doi: 10.1186/s12940-021-00754-7.
Arsenic (As) exposure through drinking water is a global public health concern. Epigenetic dysregulation including changes in DNA methylation (DNAm), may be involved in arsenic toxicity. Epigenome-wide association studies (EWAS) of arsenic exposure have been restricted to single populations and comparison across EWAS has been limited by methodological differences. Leveraging data from epidemiological studies conducted in Chile and Bangladesh, we use a harmonized data processing and analysis pipeline and meta-analysis to combine results from four EWAS.
DNAm was measured among adults in Chile with and without prenatal and early-life As exposure in PBMCs and buccal cells (N = 40, 850K array) and among men in Bangladesh with high and low As exposure in PBMCs (N = 32, 850K array; N = 48, 450K array). Linear models were used to identify differentially methylated positions (DMPs) and differentially variable positions (DVPs) adjusting for age, smoking, cell type, and sex in the Chile cohort. Probes common across EWAS were meta-analyzed using METAL, and differentially methylated and variable regions (DMRs and DVRs, respectively) were identified using comb-p. KEGG pathway analysis was used to understand biological functions of DMPs and DVPs.
In a meta-analysis restricted to PBMCs, we identified one DMP and 23 DVPs associated with arsenic exposure; including buccal cells, we identified 3 DMPs and 19 DVPs (FDR < 0.05). Using meta-analyzed results, we identified 11 DMRs and 11 DVRs in PBMC samples, and 16 DMRs and 19 DVRs in PBMC and buccal cell samples. One region annotated to LRRC27 was identified as a DMR and DVR. Arsenic-associated KEGG pathways included lysosome, autophagy, and mTOR signaling, AMPK signaling, and one carbon pool by folate.
Using a two-step process of (1) harmonized data processing and analysis and (2) meta-analysis, we leverage four DNAm datasets from two continents of individuals exposed to high levels of As prenatally and during adulthood to identify DMPs and DVPs associated with arsenic exposure. Our approach suggests that standardizing analytical pipelines can aid in identifying biological meaningful signals.
通过饮用水摄入砷是一个全球性的公共卫生问题。表观遗传失调，包括 DNA 甲基化（DNAm）的改变，可能与砷毒性有关。砷暴露的全基因组关联研究（EWAS）仅限于单一人群，并且由于方法学差异，EWAS 之间的比较受到限制。本研究利用在智利和孟加拉国进行的流行病学研究的数据，我们使用了一个协调的数据处理和分析管道，并进行荟萃分析来合并来自四个 EWAS 的结果。
在智利，我们在有和没有产前和生命早期砷暴露的成年人的 PBMC 和口腔细胞（N=40，850K 阵列）中测量 DNAm，在孟加拉国，我们在有和没有高砷暴露的男性的 PBMC（N=32，850K 阵列；N=48，450K 阵列）中测量 DNAm。在智利队列中，我们使用线性模型调整年龄、吸烟、细胞类型和性别，以识别差异甲基化位置（DMP）和差异可变位置（DVP）。使用 METAL 对 EWAS 中常见的探针进行荟萃分析，并使用 comb-p 识别差异甲基化和可变区域（DMR 和 DVR，分别）。KEGG 途径分析用于了解 DMP 和 DVP 的生物学功能。
在一个仅限于 PBMC 的荟萃分析中，我们确定了一个与砷暴露相关的 DMP 和 23 个 DVP；包括口腔细胞，我们确定了 3 个 DMP 和 19 个 DVP（FDR<0.05）。使用荟萃分析的结果，我们在 PBMC 样本中确定了 11 个 DMR 和 11 个 DVR，在 PBMC 和口腔细胞样本中确定了 16 个 DMR 和 19 个 DVR。一个注释为 LRRC27 的区域被确定为 DMR 和 DVR。与砷相关的 KEGG 途径包括溶酶体、自噬和 mTOR 信号、AMPK 信号以及叶酸的一碳池。
本研究使用两步法（1）协调的数据处理和分析，（2）荟萃分析，利用来自两个大洲的四个 DNAm 数据集，这些数据集来自于产前和成年期暴露于高水平砷的个体，以确定与砷暴露相关的 DMP 和 DVP。我们的方法表明，标准化分析管道可以帮助识别有生物学意义的信号。
