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Exploring Toxicological Mechanisms of Typical PFAS-Induced NAFLD through Integrated Computational Toxicology and AOP
Fei Li1, Jin Wang1,2, Yu Liu1,3
1CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences; Shandong Key Laboratory of Coastal Zone Environmental Processes and Ecological Security; Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China.
Abstract:
As a typical endocrine disruptor, per- and polyfluoroalkyl substances (PFASs) are closely associated with the onset and progression of non-alcoholic fatty liver disease (NAFLD). However, research on the specific mechanism remains extremely limited. In this study, a multi-methodological framework integrating network toxicology, machine learning, and molecular docking was adopted to explore the potential toxicity and molecular mechanisms of PFAS-induced NAFLD. Key molecular targets were identified by integrating transcriptomic data with toxicological databases such as CTD, ToxCast, and GeneCards. An adverse outcome pathway (AOP) was constructed using integrated PFAS-gene-phenotype evidence, and the interaction network was visualized via Cytoscape. The AOP was further validated through in vitro experiments, QWoE assessment, and clinical sample analysis. We determined that the downregulation of THBS1 serves as the molecular initiating event (MIE) in PFAS-induced NAFLD. This downregulation leads to the activation of the PI3K/AKT signaling pathway, which subsequently triggers lipid metabolic dysregulation and inflammatory responses, ultimately resulting in hepatic steatosis. HFPO-TA causes more pronounced lipid accumulation than PFOA or HFPO-DA at the same concentration, suggesting a higher adipogenic potential. It is particularly worth noting that alternative PFASs may have greater metabolic toxicity than traditional compounds like PFOA. This study clarifies the mechanistic foundation of the AOP of PFAS-induced NAFLD, thus providing support for risk assessment and the identification of potential biomarkers and therapeutic targets.
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