Mid-Continent Ecology Division, United States Environmental Protection Agency, Duluth, Minnesota 55804.
Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, National Wildlife Research Centre, Carleton University, Raven Road, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6 Canada.
Toxicol Sci. 2019 Apr 1;168(2):349-364. doi: 10.1093/toxsci/kfz006.
As the community of toxicological researchers, risk assessors, and risk managers adopt the adverse outcome pathway (AOP) framework for organizing toxicological knowledge, the number and diversity of AOPs in the online AOP knowledgebase (KB) continues to grow. To track and investigate this growth, AOPs in the AOP-KB were assembled into a single network. Summary measures on the current state of the AOP-KB and the overall connectivity and structural features of the resulting network were calculated. Our results show that networking the 187 user-defined AOPs currently described in the AOP-KB resulted in the emergence of 9405 unique, previously undescribed, linear AOPs (LAOPs). To investigate patterns in this emerging knowledge, we assembled the AOP-KB network retrospectively by sequentially adding each of the 187 user-defined AOPs and found that the creation of new AOPs that borrowed components from previously existing AOPs in the KB most described emergence of new LAOPs. However, the introduction of nonadjacent key event relationships and cycles among KEs also play key roles in emergent LAOPs. We provide examples of how to identify application-specific critical paths from this large number of LAOPs. Our research shows that the global AOP network may have considerable value as a source of emergent toxicological knowledge. These findings are not only helpful for understanding the nature of this emergent information but can also be used to manage and guide future development of the AOP-KB, and how to tailor this wealth of information to specific applications.
作为毒理学研究人员、风险评估人员和风险管理人员的社区，采用不良结局途径（AOP）框架来组织毒理学知识，在线 AOP 知识库（KB）中的 AOP 数量和多样性不断增加。为了跟踪和调查这种增长，将 AOP-KB 中的 AOP 组装成一个单一的网络。计算了当前 AOP-KB 的状态以及由此产生的网络的整体连通性和结构特征的摘要度量。我们的结果表明，将 AOP-KB 中当前描述的 187 个用户定义的 AOP 进行网络连接，产生了 9405 个独特的、以前未描述的线性 AOP（LAOP）。为了研究这种新兴知识的模式，我们通过依次添加 AOP-KB 中的 187 个用户定义的 AOP 来回顾性地组装 AOP-KB 网络，发现创建从 KB 中以前存在的 AOP 借用组件的新 AOP 最能描述新 LAOP 的出现。然而，在 KE 之间引入不相邻的关键事件关系和循环也在新兴 LAOP 中发挥关键作用。我们提供了从大量 LAOP 中识别特定于应用程序的关键路径的示例。我们的研究表明，全球 AOP 网络可能具有作为新兴毒理学知识的来源的巨大价值。这些发现不仅有助于理解这种新兴信息的性质，而且还可以用于管理和指导 AOP-KB 的未来发展，以及如何将这种丰富的信息应用于特定的应用程序。
