Abstract:
Hirschsprung\'s disease (HSCR) is a rare developmental disorder in which enteric ganglia are missing along a portion of the intestine. HSCR has a complex inheritance, with RET as the major disease-causing gene. However, the pathogenesis of HSCR is still not completely understood. Therefore, we applied a computational approach based on multi-omics network characterization and clustering analysis for HSCR-related gene/miRNA identification and biomarker discovery. Protein-protein interaction (PPI) and miRNA-target interaction (MTI) networks were analyzed by DPClusO and BiClusO, respectively, and finally, the biomarker potential of miRNAs was computationally screened by miRNA-BD. In this study, a total of 55 significant gene-disease modules were identified, allowing us to propose 178 new HSCR candidate genes and two biological pathways. Moreover, we identified 12 key miRNAs with biomarker potential among 137 predicted HSCR-associated miRNAs. Functional analysis of new candidates showed that enrichment terms related to gene ontology (GO) and pathways were associated with HSCR. In conclusion, this approach has allowed us to decipher new clues of the etiopathogenesis of HSCR, although molecular experiments are further needed for clinical validations.
摘要:
Hirschsprung病(HSCR)是一种罕见的发育障碍,其中肠神经节沿着肠道的一部分缺失。HSCR具有复杂的继承,以RET为主要致病基因。然而,HSCR的发病机制尚不完全清楚。因此,我们应用了一种基于多组学网络表征和聚类分析的计算方法,用于HSCR相关基因/miRNA的鉴定和生物标志物的发现。通过DPClusO和BiClusO分析蛋白质-蛋白质相互作用(PPI)和miRNA-靶相互作用(MTI)网络,分别,最后,通过miRNA-BD计算筛选miRNA的生物标志物潜力。在这项研究中,总共鉴定了55个重要的基因-疾病模块,允许我们提出178个新的HSCR候选基因和两个生物学途径。此外,我们在137个预测的HSCR相关miRNA中鉴定了12个具有生物标志物潜力的关键miRNA.对新候选物的功能分析表明,与基因本体论(GO)和途径相关的富集术语与HSCR相关。总之,这种方法使我们能够破译HSCR病因的新线索,尽管临床验证还需要进一步的分子实验。