Unraveling the mechanisms of bisphenol A-Induced lupus nephritis through network toxicology and machine learning approaches.
This study aimed to identify the potential toxic targets and molecular mechanisms underlying bisphenol A (BPA) exposure-induced lupus nephritis (LN) using network toxicology and machine learning. By leveraging the online databases SwissTargetPrediction, ChEMBL, STITCH, GeneCards, and OMIM, we identi...
| Published in: | International Journal of Environmental Health Research Vol. 36; no. 5; pp. 864 - 877 |
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| Main Authors: | , , , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Taylor & Francis Ltd
May2026
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=193489432&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 193489432 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09603123 57L jtl: International Journal of Environmental Health Research issn: 09603123 maglogo: Y pubinfo: dt: May2026 vid: 36 iid: 5 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 193489432 187446945 193489432 193489432 10.1080/09603123.2025.2547853 193489432 ppf: 864 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Unraveling the mechanisms of bisphenol A-Induced lupus nephritis through network toxicology and machine learning approaches. aug: au: Tang, Zhongfu Li, Ming Cheng, Lili Chen, Junjie Huang, Chuanbing affil: Department of Rheumatology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China sug: subj: Endocrine Disruptors Adverse Effects Lupus Nephritis Chemically Induced Toxicology Machine Learning Utilization Network Pharmacology Utilization Human Signal Transduction Apoptosis Mitogen-Activated Protein Kinases Toll-Like Receptors NF-kappa B Algorithms Regression Random Forest Molecular Docking Simulation Funding Source Molecular Structure Toxicity Tests ab: This study aimed to identify the potential toxic targets and molecular mechanisms underlying bisphenol A (BPA) exposure-induced lupus nephritis (LN) using network toxicology and machine learning. By leveraging the online databases SwissTargetPrediction, ChEMBL, STITCH, GeneCards, and OMIM, we identified 94 potential targets associated with BPA and LN. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, conducted using the Metascape database, revealed that the core targets associated with BPA's effects on lupus nephritis were significantly enriched in several key pathways, including apoptosis, MAPK signaling, toll-like receptor signaling, estrogen signaling, and NF-κB signaling. In addition, three machine learning algorithms, LASSO regression, SVM-RFE, and random forest (RF), were used for cross-validation and screening of core genes, and five key target genes were identified, including JUN, CYP3A4, PLAU, PTGS2, and NOTCH1. Molecular docking experiments using AutoDock confirmed the potential interactions between BPA and these core targets. In conclusion, these findings suggest that BPA may induce lupus nephritis by modulating key pathways, including apoptosis, MAPK signaling, Toll-like receptor signaling, estrogen signaling, and NF-κB signaling. This study demonstrates that BPA exposure can act as an environmental trigger in the development of LN. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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