Linking acute exposure to future risk: an omics-to-AOP new approach method for next-generation risk assessment in a human in vitro lung air-liquid interface model.

Authors

Jack Morikka, Ada Taubert, Hanna-Kaarina Juppi, Giorgia Migliaccio, Zeyad Al-Abdulraheem, Lena Möbus, Sanna Peltola, Noora Perho, Maaret Vaani, Antonio Federico, Dario Greco

Published in

Archives of toxicology. Sep 27, 2026. Epub Sep 27, 2026.

Abstract

New approach methodologies (NAMs) are transforming chemical safety assessment by shifting focus from apical toxicity endpoints toward mechanistic, human-relevant prediction of adverse outcomes. Here, we present a human lung air-liquid interface (ALI) alveolar epithelial model coupled to an omics-to-adverse outcome pathway (AOP) analysis, linking acute sublethal exposure to potential long-term toxicity outcomes. A non-tumorigenic, monoclonal lung alveolar epithelial cell line (Arlo), capable of forming a tight monolayer barrier, was basolaterally exposed to sublethal concentrations (0, 20, 60, 100 µg/mL) of the profibrotic compound bleomycin. Dose-dependent modelling of transcriptomic signatures recapitulated known mechanisms of bleomycin-induced epithelial injury, consistent with early key events in fibrotic AOPs, enabling prediction of downstream adverse outcomes. The transcriptomic signature was overlayed on a network-based representation of human pulmonary fibrosis patient biopsies. When compared to a bleomycin exposed mouse lung model, the in vitro Arlo NAM performed comparably, especially for observing effects on extracellular matrix (ECM) restructuring in an acute exposure setting. Epigenomic profiling identified methylation changes associated with epithelial-mesenchymal transition (EMT), suggesting potential long-term gene expression regulation through epigenetic control. By linking functional endpoints with dose-response transcriptomic and epigenetic signatures, this work provides a reproducible schema for omics-to-AOP next-generation safety assessment and demonstrates that acute exposures can be modelled with a resource and time efficient NAM centred on toxicogenomics, informing on longer-term consequences.

PMID:
42800837
Bibliographic data and abstract were imported from PubMed on 27 Sep 2026.

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