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

ARTICLE HIGHLIGHTS

Research background

Ulcerative colitis (UC) is an inflammatory bowel disease that affects the mucosal and submucosal layers of the colon and rectum. With advancements in the diagnosis and treatment of UC, the prospect of rapidly increasing the number of drugs with new targets is anticipated. However, despite progress in the biological understanding, information regarding the pathogenesis of UC remains limited. Therefore, exploring the molecular mechanisms of UC is of paramount importance for formulating appropriate therapeutic strategies and diagnosing the disease.

Research motivation

The primary focus of the research is to construct a competing endogenous RNA (ceRNA) network in UC and elucidate the mechanistic role of this network in the pathogenesis of UC. Additionally, using circular RNA (circRNA) as characteristic parameters, a diagnostic model for UC has been developed. Future endeavors involve expanding clinical UC sample data, applying the research methodology and approach outlined in this study, and conducting experimental validation. The goal is to further identify a more comprehensive ceRNA network and circRNAs with enhanced clinical diagnostic value.

Research objectives

The primary objective of this study is to construct a ceRNA network in UC and identify circRNAs serving as diagnostic biomarkers for UC. Ultimately, we successfully built a circRNA-miRNA-mRNA network in UC, identifying two circRNAs with clinical diagnostic value. Further exploration in this direction is anticipated to contribute to the innovation of diagnostic biomarkers for UC and provide additional insights into the crucial significance of non-coding RNA networks in UC.

Research methods

Three GSE datasets related to UC were obtained from the Gene Expression Omnibus database. Difference analysis was performed on the three GSE data sets, and differences in circRNA, miRNA and mRNA were identified. Difference analysis was performed on the three GSE data sets, and differences in circRNA, miRNA and mRNA were identified. A circRNA-miRNA-mRNA regulatory network was constructed, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed on the differential mRNAs. A circRNA-miRNA-mRNA regulatory network was constructed, and GO and KEGG analyses were performed on the differential mRNAs. circRNA predictors in UC models were screened and a model was established and validated.

Research results

We have successfully constructed a ceRNA regulatory network originating from intestinal mucosa associated with circRNAs, providing insights into the interactions among various RNA transcripts in UC. Utilizing circRNA characteristic parameters, we developed a promising nomogram model for UC disease risk diagnosis, highlighting the involvement of biomarkers and subsequent molecular mechanisms. This model and the ceRNA network can aid in predicting the onset and treatment of the disease. Further experimental verification in clinical UC samples is needed in the future.

Research conclusions

This study introduces the theoretical framework of circRNA as a diagnostic biomarker for clinical identification of UC. The novel approach proposed involves the circRNA-miRNA-mRNA network as a mechanistic pathway for subsequent therapeutic interventions in UC.

Research perspectives

The future research direction will focus on observing the significance of circRNAs as diagnostic biomarkers for UC within a clinical context.