From molecules to outcome: A network toxicology analysis and adverse outcome pathway for 6-PPDQ-induced metabolic dysfunction-associated fatty liver disease

6-PPDQ readily accumulates in the liver, disrupting hepatic glucose and lipid homeostasis and precipitating liver injury. Whether it can also trigger the chronic metabolic disease metabolic dysfunction-associated fatty liver disease (MAFLD) remains unknown. Here we integrate network toxicology with molecular docking to explore the possibility that 6-PPDQ induces MAFLD and the underlying toxicity targets and molecular mechanisms. By mining public toxicological and disease databases we identified 45 target genes associated with 6-PPDQ and MAFLD. STRING and Cytoscape analyses pinpointed four hub genes— TNF , IL1B , IL6 and TP53 . In addition, GEO datasets GSE63067 and GSE89632 were used to define the key phenotypes involved. Construction of a 6-PPDQ-genes-phenotypes-MAFLD network revealed the potential core targets, biological processes and pathways. Single gene GSEA indicated that these hubs modulate downstream hypoxia, inflammation, apoptosis and fatty acid metabolism, thereby influencing MAFLD progression, while molecular docking confirmed stable binding between the hubs and 6-PPDQ. Finally, we assembled an adverse outcome pathway (AOP) framework from 6-PPDQ to MAFLD. Our findings not only deepen understanding of 6-PPDQ toxicity but also provide a methodological template for assessing adverse health outcomes of emerging environmental pollutants. • Network toxicology reveals 45 genes associated with 6-PPDQ and metabolic dysfunction-associated fatty liver disease . • TNF, IL1B, IL6 and TP53 may be core targets in 6-PPDQ inducing MAFLD. • Network analysis suggested that 6-PPDQ may induce MAFLD by triggering key events such as oxidative stress, inflammation, and apoptosis. • A 6-PPDQ-gene-phenotype-MAFLD network was converted into a predictive adverse outcome pathway.