Computational and mathematical methods in medicine · 2022
Hub Gene Screening Associated with Early Glaucoma: An Integrated Bioinformatics Analysis.
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Tian Rui, Li Fuqiang, Che Songtian, Song Meijiao, Liu Lu, Guo Rong, Li Zhuoya, Hu Xiaomin, Zhang Hui
Аннотация
BACKGROUND: Primary open-angle glaucoma (POAG) is the most common type of glaucoma. The potential influence of some DEGs on the progression of POAG was still incomplete. In this study, we integrated transcriptome data with clinical data to investigate the relationship between them in POAG patients.
METHODS: The gene expression profile (GSE27276) from Gene Expression Omnibus (GEO) was used to identify DEGs. The LIMMA package of R was used to identify the DEGs (Diboun et al., 2006). The adjusted P values (adj P value) were calculated instead to avoid the appearance of false-positive results. Genes with |log2 fold change (FC)| larger than 1 and adj P value < 0.01 were taken as DEGs between PH and PC samples. GO (Gene Ontology) function and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of the DEGs were performed. Protein-protein interactions (PPIs) of the DEGs were constructed.
RESULTS: A total of 182 DEGs were identified through our analysis, of which 119 genes were upregulated and 63 genes were downregulated. GO enrichment analysis illustrated that these DEGs were mostly enriched into haptoglobin binding, antioxidant activity, and organic acid binding. KEGG enrichment analysis illustrated that these DEGs were mostly enriched into Staphylococcus aureus infection. The most significant module was identified by MCODE consists of 8 DEGs, and BCL11A is the seeded gene. The second most significant module consists of 5 DEGs, and IL1RN is the seeded gene.
CONCLUSION: Our results demonstrate the potential influence of some DEGs on the progression of POAG, providing a comprehensive bioinformatics analysis of the pathogenesis, which may contribute to future investigation into the molecular mechanisms and biomarkers.
METHODS: The gene expression profile (GSE27276) from Gene Expression Omnibus (GEO) was used to identify DEGs. The LIMMA package of R was used to identify the DEGs (Diboun et al., 2006). The adjusted P values (adj P value) were calculated instead to avoid the appearance of false-positive results. Genes with |log2 fold change (FC)| larger than 1 and adj P value < 0.01 were taken as DEGs between PH and PC samples. GO (Gene Ontology) function and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of the DEGs were performed. Protein-protein interactions (PPIs) of the DEGs were constructed.
RESULTS: A total of 182 DEGs were identified through our analysis, of which 119 genes were upregulated and 63 genes were downregulated. GO enrichment analysis illustrated that these DEGs were mostly enriched into haptoglobin binding, antioxidant activity, and organic acid binding. KEGG enrichment analysis illustrated that these DEGs were mostly enriched into Staphylococcus aureus infection. The most significant module was identified by MCODE consists of 8 DEGs, and BCL11A is the seeded gene. The second most significant module consists of 5 DEGs, and IL1RN is the seeded gene.
CONCLUSION: Our results demonstrate the potential influence of some DEGs on the progression of POAG, providing a comprehensive bioinformatics analysis of the pathogenesis, which may contribute to future investigation into the molecular mechanisms and biomarkers.