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. 2023 Apr 13;13(1):6039.
doi: 10.1038/s41598-023-33292-y.

Identification of hub genes and immune infiltration in ulcerative colitis using bioinformatics

Weitao Hu  1 , Taiyong Fang  2 , Mingxuan Zhou  3 , Xiaoqing Chen  4
Affiliations

Identification of hub genes and immune infiltration in ulcerative colitis using bioinformatics

Weitao Hu et al. Sci Rep. .

Abstract

Ulcerative colitis (UC) is a chronic inflammatory disease of the intestine, whose pathogenesis is not fully understood. Given that immune infiltration plays a key role in UC progression, our study aimed to assess the level of immune cells in UC intestinal mucosal tissues and identify potential immune-related genes. The GSE65114 UC dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between healthy and UC tissues were identified using the "limma" package in R, while their Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were determined with the clusterProfiler package. Protein-protein interaction network analysis and visualization were performed with STRING and Cytoscape. Immune cell infiltration was calculated with CIBERSORT. The relationship between hub genes and immune-infiltrated cells in UC was determined by Pearson correlation. A total of 206 DEGs were identified, of which 174 were upregulated and 32 downregulated. GO and KEGG functional classification indicated DEG enrichment in immune response pathways, including Toll-like receptor signaling, IL-17 signaling, and immune system process and chemokine signaling. 13 hub genes were identified. Infiltration matrix analysis of immune cells showed abundant plasma cells, memory B cells, resting CD4 memory T cells, γδ T cells, M0 and M1 macrophages, and neutrophils in UC intestinal tissues. Correlation analysis revealed 13 hub genes associated with immune-infiltrated cells in UC. 13 hub genes associated with immune-infiltrated cells in UC were identified; they included CXCL13, CXCL10, CXCL9, CXCL8, CCL19, CTLA4, CCR1, CD69, CD163, IL7R, PECAM1, TLR8 and TLR2. These genes could potentially serve as markers for the diagnosis and treatment of UC.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Differential gene expression in colonic mucosa tissue of UC patients. (A) Heat map of DEGs. Green corresponds to lower gene expression and red to higher gene expression. (B) Volcano plot of differentially expressed genes. |Log2FC| ≥ l and P < 0.05 were chosen as filtering conditions. Blue dots represent significantly downregulated genes, red dots represent significantly upregulated genes, and black dots denote genes not showing any significant difference.
Figure 2
Figure 2
PPI network construction and module analysis. (A) PPI network of DEGs. The network consists of 206 nodes (39 isolates) and 603 edges, and network Diameter is 12, network Sparseness is 0.049, and Avg clustering coefficient is 0.424. Upregulated genes are marked in red and downregulated genes are marked in blue. The size of nodes represents the difference in expression; the larger is the size, the more significant is the P value. (B) Cytoscape-based identification of the densest connected regions (15 nodes and 87 edges) in the PPI network. (C) Hub genes identified in the densest connected regions. A darker red hue indicates a higher score.
Figure 3
Figure 3
GO enrichment analysis of DEGs related to UC. A darker color and a larger bubble denote a more significant difference.
Figure 4
Figure 4
KEGG enrichment analysis of DEGs related to UC. (A) Upregulated DEGs. (B) Downregulated DEGs. 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 squares next to the selected genes.
Figure 5
Figure 5
Infiltration of immune-associated cells in healthy and UC samples. (A) Immune cell content in each sample. (B) Relative percentage of 22 subpopulations of immune cells in 28 samples from the GSE65114 dataset.
Figure 6
Figure 6
Correlation analysis and bar plot of differences among immune cells in the UC group. (A) Correlation analysis. Red indicates a positive correlation and blue indicates a negative correlation; the higher is the absolute value, the stronger is the correlation between immune cells. (B) Bar plot showing the proportion of each immune cell type between healthy and UC samples; red corresponds to healthy samples and blue to UC samples, P < 0.05.
Figure 7
Figure 7
Correlation between hub genes and immune-infiltrated cells in UC. The darker is the red hue, the smaller is the P value.
Figure 8
Figure 8
Hub genes and immune-infiltrated cells in UC.
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