Authors: Sattibabu Merugu, Karolina Jagiello, Agnieszka Gajewicz‐Skretna, Sabina Halappanavar, Andrew Willliams, Ulla Vogel, Tomasz Puzyn
Published: 2025-03-11
Source: Full article
AbstractIn this study, a previously developed approach for creating a quantitative structure‐activity relationship model anchored in an Adverse Outcome Pathway framework (AOP‐anchored Nano‐QSAR) is employed to develop a novel model capable of predicting transcriptomic responses triggered by the inhalation of multiwalled carbon nanotubes (MWCNTs). The acute phase response (AR) signaling pathway, which plays a crucial role in neutrophil influx and initiates the acute immune response is focused. This process involves recruiting pro‐inflammatory cells into the lungs and can lead to lung fibrosis, as outlined in AOP33, or atherosclerosis, as per AOP237. To establish the relationship between the structural properties of a set of MWCNTs and the transcriptional benchmark dose level (BMDLAR) response of genes associated with the acute phase response signaling pathway, the locally weighted kernel linear regression algorithm is used. These findings emphasize the critical role of the aspect ratio and specific surface area of MWCNTs in initiating acute inflammation and, subsequently, lung pathologies and atherosclerosis through the inflammatory and acute phase response signaling pathways. This newly developed data‐driven model extends the repertoire of transcriptomic‐based, AOP‐informed Nano‐QSAR models, potentially serving as an in silico new approach methodology (NAM) to support the MWCNTs’ safety assessment based on the weight of evidence.