ArticleWorld journal of pediatrics : WJP2017
Identifying key genes associated with Hirschsprung's disease based on bioinformatics analysis of RNA-sequencing data.
Article in World journal of pediatrics : WJP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 14 citations in OpenAlex.
- Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease.Biomolecules · 2024Article
- mRNA sequencing provides new insights into the pathogenesis of Hirschsprung's disease in mice.Pediatric surgery international · 2023Article
- Identification and validation of the common pathogenesis and hub biomarkers in Hirschsprung disease complicated with Crohn's disease.Frontiers in immunology · 2022Article
- Analysis of PICC Based on Dysfunction Module Personalized Nursing Treatment in Chemotherapy of Advanced Esophageal Cancer.Journal of healthcare engineering · 2021Article
- Prdx1 Reduces Intracerebral Hemorrhage-Induced Brain Injury via Targeting Inflammation- and Apoptosis-Related mRNA Stability.Frontiers in neuroscience · 2020Article
- Preliminary identification of key miRNAs, signaling pathways, and genes associated with Hirschsprung's disease by analysis of tissue microRNA expression profiles.World journal of pediatrics : WJP · 2017Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHirschsprung's disease (HSCR) is a type of megacolon induced by deficiency or dysfunction of ganglion cells in the distal intestine and is associated with developmental disorders of the enteric nervous system. To explore the mechanisms of HSCR, we analyzed the RNA-sequencing data of the expansion and the narrow segments of colon tissues separated from children with HSCR.
methodsRNA-sequencing of the expansion segments and the narrow segments of colon tissues isolated from children with HSCR was performed. After differentially expressed genes (DEGs) were identified using the edgeR package in R, functional and pathway enrichment analyses of DEGs were carried out using DAVID software. To further screen the key genes, protein-protein interaction (PPI) network and module analyses were conducted separately using Cytoscape software.
resultsA total of 117 DEGs were identified in the expansion segment samples, including 47 up-regulated and 70 down-regulated genes. Functional enrichment analysis suggested that FOS and DUSP1 were implicated in response to endogenous stimulus. In the PPI network analysis, FOS (degree=20), EGR1 (degree=16), ATF3 (degree=9), NOS1 (degree=8), CCL5 (degree=8), DUSP1 (degree=7), CXCL3 (degree=6), VIP (degree=6), FOSB (degree=5), and NOS2 (degree=4) had higher degrees, which could interact with other genes. In addition, two significant modules (module 1 and module 2) were identified from the PPI network.
conclusionsSeveral genes (including FOS, EGR1, ATF3, NOS1, CCL5, DUSP1, CXCL3, VIP, FOSB, and NOS2) might be involved in the development of HSCR through their effect on the nervous system.
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