BACKGROUND Significant progress has been made over the past decade in measuring the chemical components of the exposome, providing transformative population-scale frameworks in probing the etiologic link between environmental factors and disease phenotypes. While the analytical technologies continue to evolve with reams of data being generated, there is an opportunity to complement exposome-wide association studies (ExWAS) with functional analyses to advance etiologic search at organismal, cellular, and molecular levels. OBJECTIVES Exposomics is a transdisciplinary field aimed at enabling discovery-based analysis of the nongenetic factors that contribute to disease, including numerous environmental chemical stressors. While advances in exposure assessment are enhancing population-based discovery of exposome-wide effects and chemical exposure agents, functional screening and elucidation of biological effects of exposures represent the next logical step toward precision environmental health and medicine. In this work, we focus on the use, strategies, and prospects of alternative approaches and model systems to enhance the current human exposomics framework in biomarker search and causal understanding, spanning from bench-based nonmammalian organisms and cell culture to computational new approach methods (NAMs). DISCUSSION We visit the definition of the functional exposome and exposomics and discuss a need to leverage alternative models as opposed to mammalian animals for delineating exposome-wide health effects. Under the "three Rs" principle of reduction, replacement, and refinement, model systems such as roundworms, fruit flies, zebrafish, and induced pluripotent stem cells (iPSCs) are advantageous over mammals (e.g., rodents or higher vertebrates). These models are cost-effective, and cell-specific genetic manipulations in these models are easier and faster, compared to mammalian models. Meanwhile, in silico NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by in vitro to in vivo extrapolation (IVIVE) and integrated approaches to testing and assessment (IATA) under the adverse outcome pathway (AOP) framework. Together, these alternatives offer a strong toolbox to support functional exposomics to study toxicity and causal mediators underpinning exposure-disease links. https://doi.org/10.1289/EHP13120.

中文翻译：

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研讨会：功能暴露组学和毒性机制——来自模型系统和 NAM 的见解。


背景过去十年来，在测量暴露组的化学成分方面取得了重大进展，为探索环境因素和疾病表型之间的病因学联系提供了变革性的群体规模框架。虽然分析技术随着大量数据的产生而不断发展，但仍有机会通过功能分析来补充全暴露组关联研究 (ExWAS)，以推进有机体、细胞和分子水平的病因学搜索。目标暴露组学是一个跨学科领域，旨在对导致疾病的非遗传因素（包括众多环境化学应激源）进行基于发现的分析。虽然暴露评估的进步正在加强基于人群的暴露组效应和化学暴露剂的发现，但暴露的生物效应的功能筛选和阐明代表了迈向精确环境健康和医学的下一个合乎逻辑的步骤。在这项工作中，我们重点关注替代方法和模型系统的使用、策略和前景，以增强当前生物标志物搜索和因果理解中的人类暴露组学框架，涵盖从基于实验台的非哺乳动物生物和细胞培养到计算新方法（ NAM）。讨论我们回顾了功能性暴露组和暴露组学的定义，并讨论了利用替代模型而不是哺乳动物来描述暴露组范围内的健康影响的必要性。在减少、替代和细化的“三R”原则下，蛔虫、果蝇、斑马鱼和诱导多能干细胞（iPSC）等模型系统比哺乳动物（例如啮齿动物或高等脊椎动物）更有优势。 与哺乳动物模型相比，这些模型具有成本效益，并且这些模型中的细胞特异性遗传操作更容易、更快。同时，计算机NAM通过弥合毒理学数据和病因学推断之间的翻译差距，增强人​​类的危害识别和风险评估，如体外到体内外推法（IVIVE）和不利条件下的综合测试和评估方法（IATA）。结果路径（AOP）框架。总之，这些替代方案提供了一个强大的工具箱来支持功能暴露组学，以研究支撑暴露与疾病联系的毒性和因果介质。 https://doi.org/10.1289/EHP13120。