Expanding adverse outcome pathways towards one health models for nanosafety

Front Toxicol. 2023 Aug 25:5:1176745. doi: 10.3389/ftox.2023.1176745. eCollection 2023.

Abstract

The ever-growing production of nano-enabled products has generated the need for dedicated risk assessment strategies that ensure safety for humans and the environment. Transdisciplinary approaches are needed to support the development of new technologies while respecting environmental limits, as also highlighted by the EU Green Deal Chemicals Strategy for Sustainability and its safe and sustainable by design (SSbD) framework. The One Health concept offers a holistic multiscale approach for the assessment of nanosafety. However, toxicology is not yet capable of explaining the interaction between chemicals and biological systems at the multiscale level and in the context of the One Health framework. Furthermore, there is a disconnect between chemical safety assessment, epidemiology, and other fields of biology that, if unified, would enable the adoption of the One Health model. The development of mechanistic toxicology and the generation of omics data has provided important biological knowledge of the response of individual biological systems to nanomaterials (NMs). On the other hand, epigenetic data have the potential to inform on interspecies mechanisms of adaptation. These data types, however, need to be linked to concepts that support their intuitive interpretation. Adverse Outcome Pathways (AOPs) represent an evolving framework to anchor existing knowledge to chemical risk assessment. In this perspective, we discuss the possibility of integrating multi-level toxicogenomics data, including toxicoepigenetic insights, into the AOP framework. We anticipate that this new direction of toxicogenomics can support the development of One Health models applicable to groups of chemicals and to multiple species in the tree of life.

Keywords: adverse outcome pathways; nanosafety; one health; safe and sustainable by design; toxicoepigenomics.

Grants and funding

This study was supported by the Academy of Finland project UNICAST NANO (322761), European Research Council (ERC) programme, Consolidator project ARCHIMEDES (101043848), EU Horizon 2020 project NanoSolveIT (814572) and NanoInformaTIX (814426).