Exploring the mechanisms of diethyl phthalate-induced diabetic nephropathy through integrated network toxicology, machine learning, and experimental validation

作者
Changyan Li,Le Zhang,LuYao Shi,JingYuan Ma,WenXing Fan
出处
期刊:Ecotoxicology and Environmental Safety [Elsevier BV]
卷期号:316: 120136-120136 被引量:1
标识
DOI:10.1016/j.ecoenv.2026.120136
摘要

Phthalate plasticizers, especially diethyl phthalate (DEP), are linked to metabolic disorders, while their precise role and mechanism in diabetic nephropathy (DN) pathogenesis remain unclear. Here, we integrated transcriptomic bioinformatics, machine learning, molecular docking, and in vitro validation to decipher the nephrotoxic effect of DEP and its primary metabolite monoethyl phthalate (MEP) on DN. We found that common phthalate targets were significantly enriched in unsaturated fatty acid metabolism, prostaglandin synthesis, and prolactin signaling pathways. Fourteen core genes were screened, among which lymphocyte-specific protein tyrosine kinase (LCK) and hematopoietic prostaglandin D synthase (HPGDS) showed robust diagnostic potential for DN. Molecular docking revealed stable binding of phthalates to signal transducer and activator of transcription 3 (STAT3). In HK-2 renal tubular epithelial cells, DEP/MEP exposure reduced cell viability in a dose-dependent manner, activated the STAT3/transforming growth factor-beta 1 (TGF-β1) axis, and induced apoptosis, which were partially reversed by STAT3 inhibition. Collectively, environmental phthalate exposure exacerbates DN progression via disrupting lipid metabolism, activating inflammatory signaling, and promoting renal cell apoptosis, with LCK and HPGDS as promising diagnostic biomarkers for DN. Our study delves into the impact of phthalate plasticizers on DN. We sourced their 2D structures from PubChem and predicted potential targets using bioinformatics tools. By analyzing DN-related transcriptome data from GEO datasets, we pinpointed differentially expressed genes linked to DN. Through PPI network and Venn diagram analysis, we identified overlapping target genes associated with these plasticizers and DN. Employing advanced analytical techniques like SVM-RFE, Lasso, ROC, and CIBERSORT, coupled with experimental validation, we explored the potential effects of these plasticizers on DN progression. Our findings underscore the role of the STAT3/TGF-β1 pathway in DEP-induced renal tubular epithelial cell apoptosis and highlight LCK and HPGDS as potential diagnostic biomarkers for DN. This research enhances our understanding of how environmental plasticizers may influence metabolic diseases and opens avenues for developing targeted therapeutic strategies. • Integrative bioinformatics and machine learning reveal enriched phthalate targets in DN. • Molecular docking and in vitro experiments confirm that DEP/MEP induce renal tubular epithelial injury via the STAT3/TGF-β1 axis. • Environmental phthalate exposure exacerbates DN progression through STAT3 signaling modulation
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