ArticleHereditas2022
Screening of ulcerative colitis biomarkers and potential pathways based on weighted gene co-expression network, machine learning and ceRNA hypothesis.
Article in Hereditas, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- Emerging roles of SLC6A14 in digestive system diseases: from amino acid transport to therapeutic targeting.Molecular biology reports · 2026Review
- Functions and mechanisms of miR-650 in human diseases.Frontiers in molecular biosciences · 2026Review
- Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.Journal of assisted reproduction and genetics · 2025Article
- Artificial intelligence use for precision medicine in inflammatory bowel disease: a systematic review.American journal of translational research · 2025Review
- Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning.Frontiers in molecular biosciences · 2025Article
- The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.Diagnostics (Basel, Switzerland) · 2024Review
- SLC6A14 promotes ulcerative colitis progression by facilitating NLRP3 inflammasome-mediated pyroptosis.World journal of gastroenterology · 2024Article
- Unraveling Crucial Mitochondria-Related Genes in the Transition from Ulcerative Colitis to Colorectal Cancer.Drug design, development and therapy · 2024Article
- STUDY ON THE ROLE AND MECHANISM OF MICRORNA-650/WNT1 IN THE REPAIR OF ARTICULAR CARTILAGE INJURY.Acta ortopedica brasileira · 2024Article
- iTRAQ-based proteomic analysis of imiquimod in the treatment of ulcerative colitis.American journal of translational research · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundUlcerative colitis (UC) refers to an intractable intestinal inflammatory disease. Its increasing incidence rate imposes a huge burden on patients and society. The UC etiology has not been determined, so screening potential biomarkers is critical to preventing disease progression and selecting optimal therapeutic strategies more effectively.
methodsThe microarray datasets of intestinal mucosal biopsy of UC patients were selected from the GEO database, and integrated with R language to screen differentially expressed genes and draw proteins interaction network diagrams. GO, KEGG, DO and GSEA enrichment analyses were performed to explore their biological functions. Through machine learning and WGCNA analysis, targets that can be used as UC potential biomarkers are screened out. ROC curves were drawn to verify the reliability of the results and predicted the mechanism of marker genes from the aspects of immune cell infiltration, co-expression analysis, and competitive endogenous network (ceRNA).
resultsTwo datasets GSE75214 and GSE87466 were integrated for screening, and a total of 107 differentially expressed genes were obtained. They were mainly related to biological functions such as humoral immune response and inflammatory response. Further screened out five marker genes, and found that they were associated with M0 macrophages, quiescent mast cells, M2 macrophages, and activated NK cells in terms of immune cell infiltration. The co-expression network found significant co-expression relationships between 54 miRNAs and 5 marker genes. According to the ceRNA hypothesis, NEAT1-miR-342-3p/miR-650-SLC6A14, NEAT1-miR-650-IRAK3, and XIST-miR-342-3p-IRAK3 axes were found as potential regulatory pathways in UC.
conclusionThis study screened out five biomarkers that can be used for the diagnosis and treatment of UC, namely SLC6A14, TIMP1, IRAK3, HMGCS2, and APOBEC3B. Confirmed that they play a role in the occurrence and development of UC at the level of immune infiltration, and proposed a potential RNA regulatory pathway that controls the progression of UC.
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