Xue Wang, Tingyu Liu, Siyao Li, Dianqi Yao, Rui Ding, Bingcheng Cai, Da Wang, Yuanyuan Xu, Yi Wang
Nonylphenol (NP), an emerging environmental contaminant with neurotoxic potential, has been suggested to be associated with Alzheimer's disease (AD)-related pathological processes, although direct evidence remains limited. This study integrated network toxicology, molecular docking, and machine learning to explore mechanisms and toxicological targets potentially linking NP exposure to AD-related signaling pathways, with key findings validated via in vitro and in vivo experiments. Database screening identified 480 NP-related targets and 6,333 AD-related targets. Disease Ontology enrichment suggested that NP-associated targets were significantly involved in neurological disorders, including AD. Venn analysis yielded 324 overlapping targets that may be linked to AD-related pathological processes. GO and KEGG analyses indicated their involvement in neurological signaling pathways. Protein-protein interaction network analysis identified six hub genes (AKT1, BCL2, CASP3, EGFR, STAT3, TP53), and molecular docking revealed favorable NP-protein binding affinities. Machine learning analysis of AD datasets further identified genes that closely interact with these hubs and are associated with apoptosis, neuroinflammation, and synaptic damage. We integrated these multi-level findings to propose a conceptual model linking NP exposure-induced signaling perturbations to AD-like neurotoxic outcomes. To validate key events, male C57BL/6J mice received chronic oral NP at 0, 2, 10, or 30mg/kg/day for 3 months, and HT22 cells were exposed to 50µM NP for 24h. In vitro and in vivo experiments further confirmed that NP exposure altered the expression of these core genes and induced changes in markers related to apoptosis, neuroinflammation, and synaptic damage. Collectively, our results support a potential association between NP and AD-related pathological processes and offer mechanistic insight into NP-induced neurotoxicity.