Treffer: A Systems Biology and Drug Repositioning Approach for the Analysis of Mutual Genes Between Celiac Disease and Irritable Bowel Syndrome.

Celiac disease (CD) and irritable bowel syndrome (IBS) are two disorders that share common features, such as similar symptoms and autoimmune involvement. However, the molecular genetic mechanisms underlying their pathogenesis remain unclear. An in silico systems biology approach was performed to analyze the RNA‐seq (GSE146190 and GSE166869) and microarray data (GSE164883 and GSE63379) of both diseases. Gene ontology was first identified, followed by transcriptional factors and miRNAs that regulate the mutual genes by Enrichr platform. Moreover, a protein–protein interaction network of the shared genes was constructed, and the hub genes were identified using Network Analyst and Cytoscape. Finally, the tertiary structure of the most significant hub gene product was downloaded and screened against approved drugs using DrupRep server for drug repurposing. Four hundred thirty‐nine shared genes between CD and IBS were revealed, which were mainly involved in response to stimulus, proliferation regulation, metabolism of small molecules, and apoptosis. RARG, NFE2L2, VDR, NCOA1, and RXRA were the top five transcription factors that regulated these genes, whereas hsa‐miR‐4632‐3p, hsa‐miR‐598‐5p, hsa‐miR‐7108‐3p, and hsa‐miR‐29b‐3p were the top five miRNAs. SRC, STAT1, CCNB1, CDK1, CD44, RRM2, ERBB2, BUB1B, KIF11, and TOP2A were ranked as the Top 10 hub genes by the PPI network analysis. Temoporfin, rimegepant, and eltrombopag were suggested as the top three lead candidates by the virtual screening against SRC with binding affinities of −11.1, 10.9, and −10.8 kcal/mol, respectively. These drugs are potential SRC inhibitors that warrant further experimental validation. Novel insights into the molecular genetic mechanisms of CD and IBS and new therapeutic avenues for these disorders were provided by this study. [ABSTRACT FROM AUTHOR]

Copyright of BioMed Research International is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)