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DOI 10.3389/fped.2026.1810586

Медицинская библиотека · Frontiers in pediatrics · 2026

Exploring the impact of DEP on pediatric Crohn's disease using machine learning and molecular docking methods.

Zhang Lei, Ji Xingyu, Ma Su, Chen Huimin

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Аннотация

BACKGROUND

Diethyl phthalate (DEP) is a prevalent plasticizer with multiple toxic effects and high bioavailability in humans, especially children. Pediatric Crohn's disease (PCD) is a severe chronic intestinal inflammatory disorder with a rising incidence worldwide. To date, the potential associative relationship between DEP exposure and PCD pathogenesis remains inadequately clarified, lacking systematic transcriptomic and experimental exploration.

METHODS

In this study, bioinformatics analysis was performed based on 682 PCD samples and 127 normal samples retrieved from multiple GEO datasets. A series of analytical strategies including differential expression analysis, weighted gene co-expression network analysis (WGCNA), compound target prediction, functional enrichment analysis, machine learning modeling, and molecular docking simulation were comprehensively utilized, followed by preliminary animal validation. All analyses in this study focused on exploring statistical correlation rather than causal relationships, given the absence of individual DEP exposure data and inherent methodological limitations.

RESULTS

Through differential analysis and WGCNA, 24 differentially expressed genes and 194 chemical targets from ChEMBL were obtained, among which 14 overlapping genes were identified. GO and KEGG analyses indicated that DEP may contribute to PCD toxicity by regulating nucleotide synthesis and amino acid metabolism. Five core genes were screened via machine learning and SHAP analysis. Animal experiments verified that PLAU protein expression in DEP, TNBS, and DEP + TNBS groups was notably higher than in the control colon tissue.

CONCLUSION

This study systematically explores the potential associative links between DEP-related molecular dysregulation and PCD pathological alterations at the transcriptomic and tissue levels. The findings provide preliminary scientific references for understanding DEP-associated pediatric intestinal health risks and developing targeted preventive strategies for children's environmental health protection.

Для цитирования: Zhang Lei, Ji Xingyu, Ma Su, Chen Huimin. Exploring the impact of DEP on pediatric Crohn's disease using machine learning and molecular docking methods.. Frontiers in pediatrics. 2026. DOI: 10.3389/fped.2026.1810586.
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