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bioRxiv · 10.1101/2022.07.27.501664

Identification of hub genes and key pathways in pediatric Crohn's disease using next generation sequencing and bioinformatics analysis

Vastrad, B. M.·Vastrad, C. M.
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Abstract

Pediatric Crohn Disease (CD) also known as inflammatory bowel diseases, affects millions of people all over the world. The aim of this investigation is to identify the key genes in CD and uncover their potential functions. We downloaded the next generation sequencing (NGS) dataset GSE101794 from the Gene Expression Omnibus (GEO) database. The NGS dataset GSE101794 was used to screen differentially expressed genes (DEGs) between samples from patients with CD and healthy controls. Gene ontology (GO) and REACTOME pathway enrichment analyses were applied for the DEGs. Subsequently, a protein - protein interaction (PPI) network, modules, miRNA- hub gene regulatory network and TF - hub gene regulatory network were constructed to identify hub genes, miRNAs and TFs. Receiver operating characteristic curve (ROC) analysis was applied to validate the hub genes. A total of 957 DEGs were identified, including 478 up regulated genes and 479 down regulated genes. GO and REACTOME results suggested that several Go terms and pathways are involved in response to stimulus, extracellular region, signaling receptor binding, small molecule metabolic process, membrane, transporter activity, immune system and biological oxidations. The top centrality hub genes MDFI, MNDA, FBXO6, TFRC, STAT1, DPP4, MME, SLC39A4, APOA1 and TMEM25 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. This investigation identified key genes and signal pathways, which might help us improve our understanding of the molecular mechanisms of CD and identify some novel therapeutic targets for CD.

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Vastrad, B. M., Vastrad, C. M.. 2022-07-28. Identification of hub genes and key pathways in pediatric Crohn's disease using next generation sequencing and bioinformatics analysis. https://doi.org/10.1101/2022.07.27.501664

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