Characterization of Potential Adverse Outcome Pathways Related to Metabolic Outcomes and Exposure to Per- and Polyfluoroalkyl Substances Using Artificial Intelligence

Andreas-Marius Kaiser; Maryam Zare Jeddi; Maria Uhl; Florence Jornod; Mariana F Fernandez; Karine Audouze

doi:10.3390/toxics10080449

Characterization of Potential Adverse Outcome Pathways Related to Metabolic Outcomes and Exposure to Per- and Polyfluoroalkyl Substances Using Artificial Intelligence

Toxics. 2022 Aug 4;10(8):449. doi: 10.3390/toxics10080449.

Authors

Andreas-Marius Kaiser¹, Maryam Zare Jeddi², Maria Uhl¹, Florence Jornod³, Mariana F Fernandez^{4

5

6}, Karine Audouze³

Affiliations

¹ Environment Agency Austria, 1090 Vienna, Austria.
² National Institute for Public Health and Environment (RIVM), 3721 MA Bilthoven, The Netherlands.
³ Université Paris Cité, T3S, Inserm UMRS 1124, F-75006 Paris, France.
⁴ Centre for Biomedical Research, E-18016 Granada, Spain.
⁵ Department of Radiology and Physical Medicine, School of Medicine, University of Granada, E-18071 Granada, Spain.
⁶ Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Instituto de Salud Carlos III, E-28029 Madrid, Spain.

Abstract

Human exposure to per- and polyfluoroalkyl substances (PFAS) has been associated with numerous adverse health effects, depending on various factors such as the conditions of exposure (dose/concentration, duration, route of exposure, etc.) and characteristics associated with the exposed target (e.g., age, sex, ethnicity, health status, and genetic predisposition). The biological mechanisms by which PFAS might affect systems are largely unknown. To support the risk assessment process, AOP-helpFinder, a new artificial intelligence tool, was used to rapidly and systematically explore all available published information in the PubMed database. The aim was to identify existing associations between PFAS and metabolic health outcomes that may be relevant to support building adverse outcome pathways (AOPs). The collected information was manually organized to investigate linkages between PFAS exposures and metabolic health outcomes, including dyslipidemia, hypertension, insulin resistance, and obesity. Links between PFAS exposure and events from the existing metabolic-related AOPs were also retrieved. In conclusion, by analyzing dispersed information from the literature, we could identify some associations between PFAS exposure and components of existing AOPs. Additionally, we identified some linkages between PFAS exposure and metabolic outcomes for which only sparse information is available or which are not yet present in the AOP-wiki database that could be addressed in future research.

Keywords: AOP-helpFinder; AOP-wiki; adverse outcome pathways; metabolic syndrome; per- and polyfluoroalkyl substances.

Grants and funding

This research was funded by the HBM4EU project, grant number No. 733032 HBM4EU, and the European Union’s Horizon 2020 Research and Innovation Programme OBERON [https://oberon-4eu.com, Grant 825712 accessed on 3 July 2022]. HBM4EU represents a joint effort of 30 countries, the European Environment Agency, and the European Commission, co-funded by Horizon 2020. The main aim of the initiative is to coordinate and advance human biomonitoring in Europe. HBM4EU provides evidence of the actual exposure of citizens to chemicals and the possible health effects to support policy making. The project involves collaboration between several Commission services, EU agencies, national representatives, stakeholders, and scientists, demonstrating how research funding can build bridges between the research and policy worlds. The study also has been co-funded by the Austrian Federal Ministry for Climate Action, Environment, Energy Mobility, Innovation, and Technology.