Children's Hospital of Chongqing Medical University, China.
University-Town of Chongqing Medical University, China.
Comput Math Methods Med. 2022 Jun 21;2022:9108804. doi: 10.1155/2022/9108804. eCollection 2022.
Biliary atresia (BA) is an uncommon illness that causes the bile ducts outside and within the liver to become clogged in babies. If left untreated, the cholestasis causes increasing conjugated hyperbilirubinemia, cirrhosis, and hepatic failure. BA has a complicated aetiology, and the mechanisms that drive its development are unknown. The objective of this study was to show the role of probable critical genes involved in the pathophysiology of biliary atresia.
We utilised the public Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE46960 to find differentially expressed genes (DEGs) in 64 biliary atresia newborns, 14 infants with various causes of intrahepatic cholestasis, and 7 deceased-donor children as control subjects in our study. The relevant information was looked into. The important modules were identified after functional enrichment, GO and KEGG pathway analyses, protein-protein interaction (PPI) network analyses, and GSEA analysis.
The differential expression analysis revealed a total of 22 elevated genes. To further understand the biological activities of the DEGs, we run functional enrichment analyses on them. Meanwhile, KEGG analysis has revealed significant enrichment of pathways involved in activating cross-talking with inflammation and fibrosis in BA. SERPINE1, THBS1, CCL2, MMP7, CXCL8, EPCAM, VCAN, ITGA2, AREG, and HAS2, which may play a significant regulatory role in the pathogenesis of BA, were identified by PPI studies.
Our findings suggested 10 hub genes and probable mechanisms of BA in the current study through bioinformatic analysis.
先天性胆道闭锁（BA）是一种罕见的疾病，可导致婴儿肝脏内外的胆管堵塞。如果不进行治疗，胆汁淤积会导致结合胆红素持续升高，进而发展为肝硬化和肝衰竭。BA 的病因复杂，其发病机制尚不清楚。本研究旨在探讨可能参与胆道闭锁病理生理学的关键基因的作用。
我们利用公共基因表达综合数据库（GEO）微阵列表达谱数据集 GSE46960，在本研究中发现了 64 例先天性胆道闭锁新生儿、14 例因各种原因导致肝内胆汁淤积的婴儿和 7 例已故供体儿童的差异表达基因（DEGs）。并对相关信息进行了查询。经过功能富集、GO 和 KEGG 通路分析、蛋白质-蛋白质相互作用（PPI）网络分析和 GSEA 分析，确定了重要的模块。
差异表达分析共发现了 22 个上调基因。为了进一步了解 DEGs 的生物学活性，我们对其进行了功能富集分析。同时，KEGG 分析显示，BA 中与炎症和纤维化相互作用的途径显著富集。通过 PPI 研究发现，SERPINE1、THBS1、CCL2、MMP7、CXCL8、EPCAM、VCAN、ITGA2、AREG 和 HAS2 可能在 BA 的发病机制中发挥重要的调节作用。
通过生物信息学分析，本研究提出了 10 个与 BA 相关的枢纽基因及其可能的发病机制。
