关键词: Apoptosis Inflammation Keratoconus Literature mining Pathogenesis

Mesh : Keratoconus / genetics metabolism diagnosis Humans Computational Biology / methods Data Mining / methods Gene Regulatory Networks Protein Interaction Maps / genetics Gene Expression Profiling / methods RNA / genetics Gene Expression Regulation Gene Ontology Databases, Genetic

来  源:   DOI:10.1007/s10792-024-03071-3

Abstract:
OBJECTIVE: Keratoconus (KC) is a condition characterized by progressive corneal steepening and thinning. However, its pathophysiological mechanism remains vague. We mainly performed literature mining to extract bioinformatic and related data on KC at the RNA level. The objective of this study was to explore the potential pathological mechanisms of KC by identifying hub genes and key molecular pathways at the RNA level.
METHODS: We performed an exhaustive search of the PubMed database and identified studies that pertained to gene transcripts derived from diverse corneal layers in patients with KC. The identified differentially expressed genes were intersected, and overlapping genes were extracted for further analyses. Significantly enriched genes were screened using \"Gene Ontology\" (GO) and \"Kyoto Encyclopedia of Genes and Genomes\" (KEGG) analysis with the \"Database for Annotation, Visualization, and Integrated Discovery\" (DAVID) database. A protein-protein interaction (PPI) network was constructed for the significantly enriched genes using the STRING database. The PPI network was visualized using the Cytoscape software, and hub genes were screened via betweenness centrality values. Pathways that play a critical role in the pathophysiology of KC were discovered using the GO and KEGG analyses of the hub genes.
RESULTS: 68 overlapping genes were obtained. Fifty genes were significantly enriched in 67 biological processes, and 16 genes were identified in 7 KEGG pathways. Moreover, 14 nodes and 32 edges were identified via the PPI network constructed using the STRING database. Multiple analyses identified 4 hub genes, 12 enriched biological processes, and 6 KEGG pathways. GO enrichment analysis showed that the hub genes are mainly involved in the positive regulation of apoptotic process, and KEGG analysis showed that the hub genes are primarily associated with the interleukin-17 (IL-17) and tumor necrosis factor (TNF) pathways. Overall, the matrix metalloproteinase 9, IL-6, estrogen receptor 1, and prostaglandin-endoperoxide synthase 2 were the potential important genes associated with KC.
CONCLUSIONS: Four genes, matrix metalloproteinase 9, IL-6, estrogen receptor 1, and prostaglandin endoperoxide synthase 2, as well as IL-17 and TNF pathways, are critical in the development of KC. Inflammation and apoptosis may contribute to the pathogenesis of KC.
摘要:
目的:圆锥角膜(KC)是一种以进行性角膜陡峭化和变薄为特征的疾病。然而,其病理生理机制仍不明确。我们主要进行文献挖掘,以在RNA水平上提取KC的生物信息学和相关数据。这项研究的目的是通过在RNA水平上识别hub基因和关键分子途径来探索KC的潜在病理机制。
方法:我们对PubMed数据库进行了详尽的搜索,并确定了与KC患者不同角膜层基因转录相关的研究。鉴定的差异表达基因相交,并提取重叠基因进行进一步分析。使用“基因本体论”(GO)和“京都基因和基因组百科全书”(KEGG)分析以及“注释数据库”,筛选了显着富集的基因,可视化,和集成发现(DAVID)数据库。使用STRING数据库为显着富集的基因构建了蛋白质-蛋白质相互作用(PPI)网络。PPI网络是使用Cytoscape软件可视化的,和集线器基因通过中间性中心值进行筛选。使用集线器基因的GO和KEGG分析发现了在KC的病理生理学中起关键作用的途径。
结果:获得了68个重叠基因。50个基因在67个生物过程中显著富集,在7条KEGG通路中鉴定出16个基因。此外,通过使用STRING数据库构建的PPI网络识别出14个节点和32条边。多重分析确定了4个hub基因,12个丰富的生物过程,和6个KEGG途径。GO富集分析表明,hub基因主要参与细胞凋亡过程的正向调控,和KEGG分析表明,hub基因主要与白介素17(IL-17)和肿瘤坏死因子(TNF)途径相关。总的来说,基质金属蛋白酶9,IL-6,雌激素受体1和前列腺素-内过氧化物合酶2是与KC相关的潜在重要基因。
结论:四个基因,基质金属蛋白酶9,IL-6,雌激素受体1,和前列腺素内过氧化物合酶2,以及IL-17和TNF途径,对KC的发展至关重要。炎症和细胞凋亡可能与KC的发病有关。
公众号