Journal Article

A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes

Saarimäki, Laura Aliisa, Fadeel, Bengt, Torres Maia, Marcella, del Giudice, Giusy, Pavel, Alisa, Federico, Antonio, Alenius, Harri, Greco, Dario, Fratello, Michele, Serra, Angela

2024

Overview

Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network‐based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network‐based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data‐driven approaches for the hazard assessment of nanomaterials and other advanced materials. They present a novel framework for the assessment of the mechanisms of action of chemicals that relies on network models. This approach links toxicogenomics data to adverse outcome pathways, providing insights into biological responses to chemical exposures. This eases the interpretation of omics responses, providing a robust and generalizable strategy to link molecular evidence with toxicologically relevant phenotypes.

• Publisher: John Wiley & Sons, Inc,John Wiley and Sons Inc,Wiley
• Subject: Adverse Outcome Pathways / Animals / Annotations / Chemicals / complex systems / Datasets / engineered nanomaterials / Genes / Humans / Investigations / Nanomaterials / Nanostructures - toxicity / network theory / Ontology / System theory / Systems Biology - methods / systems toxicology / Test systems / Toxicity / toxicogenomics / Toxicology / Toxicology - methods