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. 2020 Oct 21:2020:8876565.
doi: 10.1155/2020/8876565. eCollection 2020.

Identification of Differential Intestinal Mucosa Transcriptomic Biomarkers for Ulcerative Colitis by Bioinformatics Analysis

Affiliations

Identification of Differential Intestinal Mucosa Transcriptomic Biomarkers for Ulcerative Colitis by Bioinformatics Analysis

Fang Cheng et al. Dis Markers. .

Abstract

Background: Ulcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affect mucosal homeostasis and triggers inappropriate immune response. The purpose of the study was to identify significant biomarkers with potential therapeutic targets and the underlying mechanisms.

Methods: The gene expression profiles of GSE48958, GSE73661, and GSE59071 are from the GEO database. Differentially expressed genes (DEGs) were screened by the GEO2R tool. Next, the Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Then, protein-protein interaction (PPI) was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING).

Results: There were a total of 128 common DEGs genes, including 86 upregulated genes enriched in extracellular space, regulation of inflammatory response, chemokine-mediated signaling pathway, response to lipopolysaccharide, and cell proliferation, while 42 downregulated genes enriched in the integral component of the membrane, the integral component of the plasma membrane, apical plasma membrane, symporter activity, and chloride channel activity. The KEGG pathway analysis results demonstrated that DEGs were particularly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, chemokine signaling pathway, pertussis, and rheumatoid arthritis. 18 central modules of the PPI networks were selected with Cytotype MCODE. Furthermore, 18 genes were found to significantly enrich in the extracellular space, inflammatory response, chemokine-mediated signaling pathway, TNF signaling pathway, regulation of cell proliferation, and immune response via reanalysis of DAVID.

Conclusion: The study identified DEGs, key target genes, functional pathways, and pathway analysis of UC, which may provide potential molecular targets and diagnostic biomarkers for UC.

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Conflict of interest statement

All authors report no conflicts of interest.

Figures

Figure 1
Figure 1
Volcanic plots of GSE59071, GSE48958, and GSE73661 differential genes: (a) GSE59071; (b) GSE48958; (c) GSE73661. Data points in red represent upregulated and in green represent downregulated genes. Genes without any significant difference are in black.
Figure 2
Figure 2
Authentication of 128 common DEGs in the three datasets through the Venn diagram software: (a) upregulated genes; (b) downregulated genes.
Figure 3
Figure 3
GO analysis of the common DEGs: (a) upregulated genes; (b) downregulated genes.
Figure 4
Figure 4
KEGG pathway functional enrichment analysis of the common DEGs.
Figure 5
Figure 5
Common DEGs PPI network constructed by the STRING online database and module analysis. (a) PPI network complex. The nodes meant proteins. (b) Module analysis via the Cytoscape software.
Figure 6
Figure 6
GO and KEGG pathway functional enrichment analysis of the 18 hub genes: (a) GO analysis; (b) KEGG pathway functional enrichment analysis.

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