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. 2022 Sep 10:2022:9835524.
doi: 10.1155/2022/9835524. eCollection 2022.

Exploration of Hub Genes in Retinopathy of Prematurity Based on Bioinformatics Analysis of the Oxygen-Induced Retinopathy Model

Qi Xiong  1 , Zhiliang Li  2 , Jing Zhang  1 , Lin Yang  1 , Xiaomin Chen  1 , Yan Gong  3 , Xiaojun Cai  1 , Min Ke  1
Affiliations

Exploration of Hub Genes in Retinopathy of Prematurity Based on Bioinformatics Analysis of the Oxygen-Induced Retinopathy Model

Qi Xiong et al. J Ophthalmol. .

Abstract

Retinopathy of prematurity (ROP) is a major blindness-causing disease that is characterized by an arrest of normal vascular development and neovascularization of the retina. Previous studies have shown that genetic factors may be associated with the development and severity of ROP. However, the genes and mechanisms underlying ROP remain unclear. We aimed to identify hub genes in ROP and drugs related to these genes by integrative analysis. The expression profiles of GSE158799 and GSE135844 were acquired from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. Then, an integrative analysis was performed including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), protein-protein interaction (PPI) network, transcription factor (TF)-gene, and miRNA-gene networks analysis. Moreover, we verified hub genes and identified potential drugs. 225 common DEGs were identified. Biological function analysis indicated that angiogenesis, cell surface, cell adhesion, extracellular matrix, and focal adhesion genes were enriched among DEGs. The PI3K/Akt signalingpathway, focal adhesion, and extracellular matrix (ECM)-receptor interaction were markedly enriched in the KEGG pathway analysis. Finally, 5 hub genes related to the nosogenesis of ROP were identified and found to be targeted by VEGFA inhibitors, TLR4 antagonists, and sunitinib. The present study showed that VEGFA, ACTA2, MKI67, CD68, and TLR4 are potential hub genes involved in the pathogenesis of ROP. Moreover, TLR4 antagonists and sunitinib may be new candidate drugs for ROP therapy, in addition to VEGFA inhibitors.

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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Figure 1
Figure 1
The flowchart of the research process. GO, Gene Ontology; GSEA, gene set enrichment analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; PPI, protein-protein interaction.
Figure 2
Figure 2
Heatmap of differentially expressed genes identified in (a) GSE158799 and (b) GSE135844. Legend on the top right indicates the log fold change of the genes; volcano plots of differentially expressed genes. (c) GSE158799 and (d) GSE135844. Data points in red represent upregulated, and data points in green represent downregulated genes. The differences are set as |log FC|>0.585. Venn diagram of common differentially expressed genes from the two datasets. (e) 0 DEG was downregulated in the two datasets, and (F) 225 DEGs were upregulated in the two datasets.
Figure 3
Figure 3
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed genes (DEGs). The advanced bubble chart shows enrichment significance items of DEGs: (a) molecular function (MF), (b) biological processes (BP), (c) cell composition (CC), and (d) KEGG. The x-axis label represents the gene ratio, and the y-axis label represents GO or KEGG terms. The chord plot shows the distribution of DEGs in different (e) GO-enriched functions and (f) KEGG-enriched pathways. The size of the circle indicates the number of enriched genes.
Figure 4
Figure 4
GSEA plots showing the most enriched gene sets of all detected genes in the ROP group and the control group in the GSE158799 dataset. The top 3 most significant upregulated enriched gene sets in the ROP group: (a) positive regulation of vasculature development, (b) establishment of endothelial barrier, and (c) blood vessel endothelial cell migration. The top 3 most significant upregulated enriched gene sets in the control group: (d) sensory perception of chemical stimulus, (e) sensory perception of smell, and (f) olfactory receptor activity.
Figure 5
Figure 5
(a) PPI network of DEGs created by STRING. Circles represent genes, and lines represent PPIs. (b) The most significant module identified by MCODE (score = 13.773). (c) The second significant module identified by MCODE (score = 9.400). (d) The third significant module identified by MCODE (score = 7.556). DEG, differentially expressed gene; PPI, protein-protein interaction.
Figure 6
Figure 6
Identified 7 hub genes from the Comparative Toxicogenomics database.
Figure 7
Figure 7
Differential expression of mRNAs in peripheral blood between ROP and control was validated by qRT-PCR. (a) VEGFA, (b) PECAM1, (c) ACTA2, (d) MKI67, (e) TLR4, (f) CD68, and (g) CDH5, ns (no significant difference, P > 0.05),  ∗P < 0.05,  ∗ ∗P < 0.01, and  ∗ ∗ ∗ ∗P < 0.0001.
Figure 8
Figure 8
The networks of (a) miRNA-gene and (b) TF-gene. The red circle nodes are the genes, the blue square nodes are the miRNAs, and the green diamond nodes are the TFs.
Figure 9
Figure 9
The drug-gene interaction network. The blue diamond nodes are the genes, and the red diamond nodes are the drugs.
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