Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC.
Department of Psychology, University of Texas at Austin, Austin, TX.
Neurotoxicol Teratol. 2020 Mar-Apr;78:106865. doi: 10.1016/j.ntt.2020.106865. Epub 2020 Feb 14.
A key challenge in systematically incorporating mechanistic data into human health assessments is that, compared to studies of apical health endpoints, these data are both more abundant (mechanistic studies routinely outnumber other studies by several orders of magnitude) and more heterogeneous (e.g. different species, test system, tissue, cell type, exposure paradigm, or specific assays performed). A structured decision-making process for organizing, integrating, and weighing mechanistic DNT data for use in human health risk assessments will improve the consistency and efficiency of such evaluations. At the Developmental Neurotoxicology Society (DNTS) 2016 annual meeting, a symposium was held to address the application of existing organizing principles and frameworks for evaluation of mechanistic data relevant to interpreting neurotoxicology data. Speakers identified considerations with potential to advance the use of mechanistic DNT data in risk assessment, including considering the context of each exposure, since epigenetics, tissue type, sex, stress, nutrition and other factors can modify toxicity responses in organisms. It was also suggested that, because behavior is a manifestation of complex nervous system function, the presence and absence of behavioral change itself could be used to organize the interpretation of multiple complex simultaneous mechanistic changes. Several challenges were identified with frameworks and their implementation, and ongoing research to develop these approaches represents an early step toward full evaluation of mechanistic DNT data for assessments.
将机制数据系统地纳入人类健康评估的一个主要挑战是，与针对顶端健康终点的研究相比，这些数据不仅更为丰富（机制研究的数量通常比其他研究多几个数量级），而且更加多样化（例如不同的物种、测试系统、组织、细胞类型、暴露模式或进行的特定检测）。为了在人类健康风险评估中组织、整合和权衡机制性非遗传毒性数据并加以利用，需要采用结构化决策过程，这将提高此类评估的一致性和效率。在 2016 年发育神经毒理学学会（DNTS）年会上举办了一次专题研讨会，旨在讨论应用现有的组织原则和框架，评估与解释神经毒理学数据相关的机制数据。演讲者确定了一些具有推动将机制性非遗传毒性数据用于风险评估的潜力的考虑因素，包括考虑到每种暴露的情况，因为表观遗传学、组织类型、性别、压力、营养和其他因素可以改变生物体的毒性反应。还有人建议，由于行为是复杂神经系统功能的表现，行为改变的出现和缺失本身就可以用来组织对多种复杂的同时发生的机制变化的解释。演讲者还确定了框架及其实施所面临的一些挑战，目前正在开展相关研究，以期充分评估用于评估的机制性非遗传毒性数据，这是全面评估的早期步骤。
