Identifying potential relationships between air pollutants and neutrophil extracellular traps formation in metabolic dysfunction-associated fatty liver disease by integrating computational toxicology and multi-omics data

Metabolic dysfunction-associated fatty liver disease (MASLD) is a highly prevalent liver condition with a complex etiology increasingly linked to air pollution. However, the molecular mechanisms through which air pollutants exacerbate MASLD remain poorly understood. In this study, we integrated computational toxicology, multi-omics analyses, and machine learning to identify critical molecular targets of hepatotoxicity-related air pollutants (HTRAPs). This integrated approach identified ozone (O₃) and carbon monoxide (CO) as HTRAPs based on their hepatotoxic potential. Using integrative machine learning, we pinpointed Cathepsin G (CTSG), Dipeptidyl Peptidase 7 (DPP7), and Apolipoprotein B mRNA Editing Enzyme Catalytic Subunit 3G (APOBEC3G) as key MASLD-related targets. To validate these findings, we measured the dysregulated expression of critical genes in MASLD-simulating cells treated with O₃ using quantitative Real-Time PCR (qRT-PCR). Molecular docking and dynamics simulations indicated a high-affinity, potential binding mode between O₃ and the CTSG protein. High CTSG expression correlated with neutrophil infiltration and neutrophil extracellular traps (NETs) formation. Interestingly, a significant positive correlation was observed between NETs formation and the enrichment of regulatory B cells. This study proposes a novel hypothesis that O₃ may facilitate NETs formation by interacting with CTSG. These findings highlight CTSG as a potential therapeutic target and underscore the role of air pollution in MASLD progression.