Construction, bioinformatics analysis, and validation of competitive endogenous RNA networks in ulcerative colitis

Abstract

Background: Ulcerative colitis (UC) is a common chronic disease of the digestive system. Recently, competitive endogenous RNAs (ceRNAs) have been increasingly used to reveal key mechanisms for the pathogenesis and treatment of UC. However, the role of ceRNA in UC pathogenesis has not been fully clarified. This study aimed to explore the mechanism of the lncRNA-miRNA-mRNA ceRNA network in UC and identify potential biomarkers and therapeutic targets.Materials and Methods: An integrative analysis of mRNA, microRNA (miRNA), and long non-coding RNA (lncRNA) files downloaded from the Gene Expression Omnibus (GEO) was performed. Differentially expressed mRNA (DE-mRNAs), miRNA (DE-miRNAs), and lncRNA (DE-lncRNAs) were investigated between the normal and UC groups by the limma package. A weighted correlation network analysis (WGCNA) was used to identify the relative model for constructing the ceRNA network, and, concurrently, miRWalk and DIANA-LncBase databases were used for target prediction. Consecutively, the Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway, and Reactome pathway enrichment analyses, protein-protein interaction (PPI) network, Cytohubba, and ClueGO were performed to identify hub genes. Additionally, we examined the immune infiltration characteristics of UC and the correlation between hub genes and immune cells using the immuCellAI database. Finally, the expression of potential biomarkers of ceRNA was validated via qRT-PCR in an experimental UC model induced by dextran sulfate sodium (DSS).Result: The ceRNA network was constructed by combining four mRNAs, two miRNAs, and two lncRNAs, and the receiver operating characteristic (ROC) analysis showed that two mRNAs (CTLA4 and STAT1) had high diagnostic accuracy (area under the curve [AUC] > 0.9). Furthermore, CTLA4 up-regulation was positively correlated with the infiltration of immune cells. Finally, as a result of this DSS-induced experimental UC model, CTLA4, MIAT, and several associate genes expression were consistent with the results of previous bioinformatics analysis, which proved our hypothesis.Conclusion: The investigation of the ceRNA network in this study could provide insight into UC pathogenesis. CTLA4, which has immune-related properties, can be a potential biomarker in UC, and MIAT/miR-422a/CTLA4 ceRNA networks may play important roles in UC.

Construction of the underlying circRNA-miRNA-mRNA regulatory network and a new diagnostic model in ulcerative colitis by bioinformatics analysis

“…For instance, Xu et al [ 38 ] performed a comprehensive analysis that revealed four central genes regulated by NF-κB, ultimately constructing an lncRNA-miRNA-transcription factor (NF-κB) interaction network. Another study aimed to demonstrate the high diagnostic accuracy of two mRNAs (CTLA4 and STAT1) within the ceRNA network in UC[ 39 ]. In contrast, we focused on circRNA as a potential clinical diagnostic marker, deviating from conventional approaches, with circRNA possibly offering improved specificity.…”

Transcriptomically unique endolysosomal and homeostatic microglia populations in Alzheimer’s disease and aged human brain

“…To further characterize the ELN clusters (3, 5, and 6) we implemented this approach to get a more refined examination of the biologically linked process driven by each cluster. We employed several different approaches to perform this analysis, ultimately choosing the Cytoscape network clustering application ClueGO 70,71 , which was employed extensively in recent years for this purpose [72][73][74][75] . The advantage of this network approach is that GO term enrichment is selected based upon networks derived from kappa-score between terms based on similarity of genetic contribution to the particular term.…”

Identified S100A9 as a target for diagnosis and treatment of ulcerative colitis by bioinformatics analysis

“…Bioinformatics analysis has been widely used to search for differentially expression genes (DEGs), miRNA, and functional pathways involved in the development and progression of UC. For example, Wu et al constructed a complete lncRNA-miRNA-mRNA network through bioinformatics to determine the specific immune infiltration characteristics of UC 13 . Moreover, protein–protein interaction (PPI) can provide information about direct and indirect protein interactions for screening hub genes 14 , 15 .…”