Superfund and Emergency Management Division, Region 2, U.S. Environmental Protection Agency, NY, USA.
Chemical and Pollutant Assessment Division, Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency, Cincinnati, USA.
Environ Int. 2022 Jun;164:107278. doi: 10.1016/j.envint.2022.107278. Epub 2022 May 5.
Recent efforts have posited the utility of transcriptomic-based approaches to understand chemical-related perturbations in the context of human health risk assessment. Epigenetic modification (e.g., DNA methylation) can influence gene expression changes and is known to occur as a molecular response to some chemical exposures. Characterization of these methylation events is critical to understand the molecular consequences of chemical exposures. In this context, a novel workflow was developed to interrogate publicly available epidemiological transcriptomic and methylomic data to identify relevant pathway level changes in response to chemical exposure, using inorganic arsenic as a case study. Gene Set Enrichment Analysis (GSEA) was used to identify causal methylation events that result in concomitant downstream transcriptional deregulation. This analysis demonstrated an unequal distribution of differentially methylated regions across the human genome. After mapping these events to known genes, significant enrichment of a subset of these pathways suggested that arsenic-mediated methylation may be both specific and non-specific. Parallel GSEA performed on matched transcriptomic samples determined that a substantially reduced subset of these pathways are enriched and that not all chemically-induced methylation results in a downstream alteration in gene expression. The resulting pathways were found to be representative of well-established molecular events known to occur in response to arsenic exposure. The harmonization of enriched transcriptional patterns with those identified from the methylomic platform promoted the characterization of plausibly causal molecular signaling events. The workflow described here enables significant gene and methylation-specific pathways to be identified from whole blood samples of individuals exposed to environmentally relevant chemical levels. As future efforts solidify specific causal relationships between these molecular events and relevant apical endpoints, this novel workflow could aid risk assessments by identifying molecular targets serving as biomarkers of hazard, informing mechanistic understanding, and characterizing dose ranges that promote relevant molecular/epigenetic signaling events occuring in response to chemical exposures.
最近的研究提出，基于转录组的方法可用于在人类健康风险评估的背景下了解与化学物质相关的干扰。表观遗传修饰（例如 DNA 甲基化）可以影响基因表达的变化，并且已知是某些化学物质暴露的分子反应。这些甲基化事件的特征对于了解化学物质暴露的分子后果至关重要。在这种情况下，开发了一种新的工作流程，以研究公开的流行病学转录组和甲基组数据，以识别对化学暴露的相关途径水平变化，使用无机砷作为案例研究。基因集富集分析（GSEA）用于识别导致伴随转录失调的因果性甲基化事件。该分析表明，在人类基因组中，差异甲基化区域的分布不均等。将这些事件映射到已知基因后，这些途径的子集显著富集表明，砷介导的甲基化可能是特异性和非特异性的。在匹配的转录组样本上并行进行的 GSEA 确定，这些途径的子集显著富集，并且并非所有化学诱导的甲基化都会导致下游基因表达的改变。所得途径代表了已知对砷暴露有反应的既定分子事件。与从甲基组平台识别出的转录本富集模式的协调促进了可能的因果分子信号事件的特征描述。本文描述的工作流程可从暴露于环境相关化学水平的个体的全血样本中识别出显著的基因和甲基化特异性途径。随着未来的研究确定这些分子事件与相关顶端终点之间的特定因果关系，这种新的工作流程可以通过识别作为危害生物标志物的分子靶标，为机制理解提供信息，并描述促进化学物质暴露后发生的相关分子/表观遗传信号事件的剂量范围来帮助风险评估。
