Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA.
Department of Environmental Medicine, University of Rochester Medical Center, Rochester, New York, USA.
Environ Health Perspect. 2024 Sep;132(9):94201. doi: 10.1289/EHP13120. Epub 2024 Sep 4.
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.
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).
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, NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by to 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.
在过去的十年中，在测量外核组的化学成分方面取得了重大进展，为探索环境因素与疾病表型之间的病因联系提供了变革性的人群规模框架。虽然分析技术随着大量数据的产生而不断发展，但有机会通过功能分析补充外核组关联研究 (ExWAS)，以推进在机体、细胞和分子水平上的病因研究。
外组学是一个跨学科领域，旨在实现基于发现的分析，以研究导致疾病的非遗传因素，包括许多环境化学应激物。虽然暴露评估的进展增强了基于人群的外核组效应和化学暴露剂的发现，但功能筛选和阐明暴露的生物学效应是朝着精准环境健康和医学迈出的下一个合乎逻辑的步骤。在这项工作中，我们专注于使用、策略和前景替代方法和模型系统，以增强当前的人类外核组框架，用于生物标志物搜索和因果理解，涵盖从基于实验室的非哺乳动物和细胞培养到计算新方法 (NAMs)。
我们探讨了功能外核组和外组学的定义，并讨论了需要利用替代模型而不是哺乳动物来描绘外核组健康效应的必要性。根据减少、替代和细化的“三个 Rs”原则，模型系统（如蛔虫、果蝇、斑马鱼和诱导多能干细胞 (iPSC)）比哺乳动物（例如，啮齿动物或高等脊椎动物）具有优势。这些模型具有成本效益，并且与哺乳动物模型相比，这些模型中的细胞特异性遗传操作更容易且更快。同时，NAM 通过在毒理学数据和病因推断之间架起桥梁来增强人类的危害识别和风险评估，这代表了从毒性数据到病因推断的外推（IVIVE）和综合测试和评估方法（IATA）下的不良结局途径（AOP）框架。总的来说，这些替代方案提供了一个强大的工具箱，支持功能外组学研究暴露-疾病关联背后的毒性和因果中介。https://doi.org/10.1289/EHP13120.
