The Exposome - a New Approach for Risk Assessment
The Exposome - a New Approach for Risk Assessment
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DOI：
10.14573/altex.2001051
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发表时间：
2020-01-01
影响因子：
5.6
通讯作者：
Hartung, Thomas
中科院分区：
文献类型：
--
作者：
Sille, Fenna C. M.;Karakitsios, Spyros;Hartung, Thomas
用基因组补充人类基因组反映了环境暴露对人类健康日益明显的影响，这种影响远远超过了遗传学的作用。考虑到暴露的复杂性，以及身体对暴露的反应-即，这是一个难题-颠覆了传统的暴露科学，在传统的暴露科学中，对单一或少量暴露的精确测量与特定的健康或环境影响有关。要完整地描述一个人的烦恼是不可能的;更不可能描述一个群体的烦恼。然而，我们可以通过放弃一些严格的评估和丰富数据集的统计能力来弥补，从而撒下更大的网。组学技术的出现使得对物质的生物效应，特别是在组织和生物流体中的生物效应的描述相对便宜，内容丰富。它们可以与许多其他丰富的数据流相结合，创建曝光和效果的大数据。计算方法越来越多地允许数据整合，从噪音中辨别信号，并制定假设的安全性-效果关系。这些可以有针对性地跟进。随着风险方程中更好的暴露元素，风险评估领域的新成员--风险组学--有望确定新的暴露（相互作用）和健康/环境影响关联。这也可能创造机会，将更相关的化学品列为风险评估的优先事项，从而以一种以风险为导向的办法减轻危害评估的负担。技术发展和方法之间的协同作用，质量保证（最终作为良好的暴露体实践），以及机械思维的整合将推动这一方法。
Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way.With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an exposure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.