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. 2022 Aug 31:13:950136.
doi: 10.3389/fgene.2022.950136. eCollection 2022.

Identifying hub genes and miRNAs in Crohn's disease by bioinformatics analysis

Yuxin Sun  1 , Daxing Cai  1 , Weitao Hu  2 , Taiyong Fang  1
Affiliations

Identifying hub genes and miRNAs in Crohn's disease by bioinformatics analysis

Yuxin Sun et al. Front Genet. .

Abstract

Introduction: Crohn's disease (CD) is a disease that manifests mainly as chronic inflammation of the gastrointestinal tract, which is still not well understood in terms of its pathogenesis. The aim of this study was to use bioinformatics analysis to identify differentially expressed genes (DEGs) and miRNAs with diagnostic and therapeutic potential in CD. Materials and methods: Three CD datasets (GSE179285, GSE102133, GSE75214) were downloaded from the Gene Expression Omnibus (GEO) database. DEGs between normal and CD tissues were identified using the GEO2R online tool. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were conducted using the clusterProfiler function in the R package. Protein-protein interaction network (PPI) analysis and visualization were performed with STRING and Cytoscape. Ten hub genes were identified using cytoHubba's MCC algorithm and validated with datasets GSE6731 and GSE52746. Finally, the miRNA gene regulatory network was constructed by Cytoscape and NetworkAnalyst to predict potential microRNAs (miRNAs) associated with DEGs. Results: A total of 97 DEGs were identified, consisting of 88 downregulated genes and 9 upregulated genes. The enriched functions and pathways of the DEGs include immune system process, response to stress, response to cytokine and extracellular region. KEGG pathway analysis indicates that the genes were significantly enriched in Cytokine-cytokine receptor interaction, IL-17 signaling pathway, Rheumatoid arthritis and TNF signaling pathway. In combination with the results of the protein-protein interaction (PPI) network and CytoHubba, 10 hub genes including IL1B, CXCL8, CXCL10, CXCL1, CXCL2, CXCL5, ICAM1, IL1RN, TIMP1 and MMP3 were selected. Based on the DEG-miRNAs network construction, 5 miRNAs including hsa-mir-21-5p, hsa-mir-93-5p, hsa-mir-98-5p, hsa-mir-1-3p and hsa-mir-335-5p were identified as potential critical miRNAs. Conclusion: In conclusion, a total of 97 DEGs, 10 hub genes and 5 miRNAs that may be involved in the progression or occurrence of CD were identified in this study, which could be regarded as biomarkers of CD.

Keywords: Crohn’s disease; MicroRNAs; bioinformatics analysis; differentially expressed genes; hub genes.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Volcano plots indicating differentially expressed genes (DEGs) among the control and CD groups. (A–C) DEGs of the GSE179285, GSE102133 and GSE75214 datasets are shown, separately. Red data points represent upregulated genes and blue ones represent downregulated genes. Genes without any significant differences are in black.
FIGURE 2
FIGURE 2
Venn diagrams showing the differentially expressed genes (DEGs) that overlapped among the 3 datasets retrieved from Gene Expression Omnibus (GEO). (A,B) Indicate the overlap of upregulated and downregulated genes in the GSE179285, GSE102133 and GSE75214 datasets, separately.
FIGURE 3
FIGURE 3
Function enrichment analysis of DEGs related to CD. (A) Bubble plot of enriched GO terms showing upregulated DEGs. (B) Bubble plot of enriched GO terms showing downregulated DEGs. A darker color and a larger bubble denote a more significant difference. (C) KEGG enrichment analysis of DEGs related to CD; The genes are linked to their assigned pathway terms via colored ribbons and are ordered according to the observed log10 p-value, which is displayed in descending intensity of red-green squares next to the selected genes.
FIGURE 4
FIGURE 4
PPI networks of 88 upregulated genes and 9 downregulated genes by Cytoscape. The network consists of 97 nodes and 376 edges. 2 edges between nodes represent the interactions between genes. Each gene corresponding to the node is sized and colored according to the degree of interaction. The color grade indicates the change in the degree of each gene from high (blue) to low (white). The nearer the blue node, the higher the connection between the 2 nodes (A). The densest connected region in the PPI network (13 nodes, 75 edges) was identified using MCODE (B). Using the MCC algorithm in cytoHubba, 10 hub genes were identified in the densest connected regions. The scores are shown in red color. A darker color means a higher score (C).
FIGURE 5
FIGURE 5
Analysis of functional enrichment for hub genes. (A) Bubble plot of enriched GO terms showing hub genes. (B) Bubble plot of enriched KEGG showing hub genes.
FIGURE 6
FIGURE 6
Validation of the expressions of hub genes in CD. (A,B) DEGs of the GSE52746 and GSE6731 datasets are shown, separately. Red data points represent upregulated genes and blue ones represent downregulated genes. Genes without any significant differences are in black.
FIGURE 7
FIGURE 7
Top 9 hub genes in the integrated miRNA-DEGs network. The pink diamond shape indicates the 9 hub genes. The grey circles indicate miRNAs with low connective properties to the hub genes. Green hexagons indicate miRNAs with high connective properties to the hub genes.
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