AUTHOR=Na Zhao , Yang Hang , Chen Li , Xiao Han , Hai Bo , Li Chuanxin , Xie Xiaohui , Bai Qiang 

TITLE=Research on biliary atresia and epigenetic factors from the perspective of transcriptomics: identification of key genes and experimental validation

JOURNAL=Frontiers in Pediatrics

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2025.1624671

DOI=10.3389/fped.2025.1624671

ISSN=2296-2360

ABSTRACT=BackgroundBiliary atresia (BA) is a severe pediatric liver disease. However, the role of epigenetic factors in its pathogenesis remains poorly understood. This study aimed to identify key genes associated with BA and epigenetic factors, as well as to explore potential therapeutic drugs, thereby offering new insights into the treatment of this condition.MethodsTranscriptomic datasets (training set GSE122340 and validation set GSE46960) were analyzed. The training set was used to identify differentially expressed genes (DEGs) between BA and normal samples. Candidate genes were selected by intersecting the DEGs with epigenetic factor-related genes. A protein-protein interaction (PPI) network was constructed, and key genes displaying consistent expression patterns across both datasets were identified. Localization, correlation, and Gene Set Enrichment Analysis (GSEA) of these key genes were performed. A molecular regulatory network was constructed, and drug predictions, along with molecular docking simulations, were conducted for the key genes. Experimental validation of the bioinformatics findings was carried out.ResultsA total of 3,462 DEGs were identified, from which 62 candidate genes were selected. Five key genes (AURKA, BUB1, CDK1, RAD51, TOP2A) were highlighted, all of which exhibited strong positive correlations and were linked to essential pathways, including the cell cycle. Thirteen potential drugs were identified, with three pairs showing strong binding affinities. RT-qPCR validation confirmed that, except for CDK1, AURKA, BUB1, RAD51, and TOP2A exhibited consistent trends with the bioinformatics analysis, and were significantly upregulated in the BA group.ConclusionThis study successfully identified key genes (AURKA, BUB1, CDK1, RAD51, TOP2A) and potential therapeutic drugs for BA, providing critical insights into its pathogenesis and offering potential avenues for novel treatment strategies.