Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework

Abstract

Adverse Outcome Pathways (AOP) provide structured frameworks for the systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, virology and medical research. The COVID-19 pandemic engages a great number of scientists world-wide and data is increasing with exponential speed. Diligent data management strategies are employed but approaches for systematically organizing the data-derived information and knowledge are lacking. We believe AOPs can play an important role in improving interpretation and efficient application of scientific understanding of COVID-19. Here, we outline a newly initiated effort, the CIAO project (https://www.ciao-covid.net/), to streamline collaboration between scientists across the world toward development of AOPs for COVID-19, and describe the overarching aims of the effort, as well as the expected outcomes and research support that they will provide.

Keywords: COVID-19; adverse outcome pathways; data integration; interdisciplinarity; mechanisms; systematic organization.

Figure 1

Diagram of (A) an adverse outcome pathway (AOP) and (B) an AOP network. (A) An AOP starts with a molecular initiating event (MIE), followed by a series of key events (KEs) on different levels of biological organization (cellular, tissue, organ) and ends with an adverse outcome (AO) in an organism. The stressor is not part of the AOP itself. The diagram provides examples of an MIE, KEs, and an AO relevant to COVID-19, that is, ACE2 binding leading to IL-6 secretion, inflammation and acute respiratory distress. (B) AOP networks depict interrelated AOPs that share KEs, referred to as hub KEs, which, for example, may support identification of mechanisms central to diverse courses of action taken by COVID-19 in different patients. Please refer to reference (9) for a preliminary overview of a detailed AOP network for COVID-19.

Figure 2

Toward an interdisciplinary workflow and infrastructure for systematic gathering and organization of data in potential future health crises. A concept demonstrating how experts join in an interdisciplinary data-driven effort supported by the Adverse Outcome Pathway (AOP) framework to increase mechanistic understanding of disease. The gained understanding supports effective (and ideally animal-free) development of treatments and diagnostics. [Figure modified from (28)].