环境化学
多环芳烃
化学
炎症性肠病
疾病
医学
内科学
作者
Yufang Hou,Yuexia Che,Tiegang Li,Yan Zheng,Wenyi Zhao,Silin Lv,Fang Zhang,Mingxuan Zhou,Y. Zhou,Zhaohui Zhu,Xinyi Ren,Siying Huang,Min Yang
标识
DOI:10.1016/j.ecoenv.2025.119153
摘要
Oxygenated polycyclic aromatic hydrocarbons (OPAHs), emerging contaminants in the environment, demonstrate heightened toxicity versus their parent compounds, creating substantial health hazards. Inflammatory bowel disease (IBD) encompasses chronic conditions marked by severe inflammation in the digestive tract. Environmental factors contribute to the development of both types of IBD. However, the toxicological mechanisms underlying OPAHs-induced IBD remain poorly understood. This investigation methodically examined the potential connection between OPAHs and IBD, identifying key genes involved in OPAHs-induced IBD. Using a network toxicology approach, 324 overlapping genes were identified between disease targets and five representative OPAHs effectors. These genes were further refined to 15 potential targets through analysis with STRING and Cytoscape. GO and KEGG pathway enrichment analyses indicated these targets primarily participate in oxidative stress responses, cell death, chemical stress reactions, inflammatory processes, and immune pathways. Subsequent analysis with machine learning algorithms highlighted three core targets: AKT1, ALB, and APP. Immune landscape analysis and single-cell RNA sequencing demonstrated strong associations between these hub genes and immune cell infiltration and immune responses. Molecular docking revealed high binding affinities between OPAHs and these hub proteins. In vitro experiments confirmed that OPAHs significantly elevated reactive oxygen species levels and induced intestinal epithelial barrier dysfunction. This study elucidates the molecular mechanisms through which OPAHs influence IBD development, offering valuable insights into the health risks posed by environmental pollutants and identifying potential targets for therapeutic development.
科研通智能强力驱动
Strongly Powered by AbleSci AI