Liver fibrosis in biliary atresia: identification of the key gene EDIL3 via integrated bioinformatics

作者：Meng Kong, Jinhua Jia, Chuanyang Liu, Hongzhen Liu, Shisong Zhang · 发表于：Frontiers in Medicine · 年份：2026 · DOI：10.3389/fmed.2025.1726141 · 被引用次数：3 · 研究领域：Pediatric Hepatobiliary Diseases and Treatments、Pancreatitis Pathology and Treatment、Gallbladder and Bile Duct Disorders

Background: Biliary atresia (BA) is one of the most destructive liver and biliary diseases in neonates and is characterized by progressive fibrous inflammatory obstruction of the intrahepatic and extrahepatic bile ducts, ultimately leading to liver fibrosis and liver failure. This study aimed to use integrated bioinformatics methods to identify differentially expressed genes (DEGs) in BA liver tissue, identify key genes, and explore their mechanisms in liver fibrosis. Methods: We obtained data from the gene expression omnibus (GEO) dataset GSE122340 [171 BA patients and 7 normal controls (NCs)]. DEGs were screened via the limma package, followed by gene ontology (GO)/kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. A protein-protein interaction (PPI) network was constructed via STRING and Cytoscape, and core genes were selected via the maximum clique centrality (MCC), maximum neighborhood component (MNC), and degree algorithms from the CytoHubba plugin. Further focus was placed on the key gene EGF-like repeats and discoidin I-like domains 3 (EDIL3) through gene set enrichment analysis (GSEA), expression validation, subcellular localization analysis, and clinical tissue sample validation. To minimize batch effects, we performed ComBat correction on the combined gene expression data of GSE122340 and the validation dataset GSE46960 before interdataset comparison. Results: We identified a total of 3706 DEGs, including 2774 upregulated DEGs and 932 downregulated...