Guoji Yanke Zazhi (Aug 2023)

Identification of key immune related genes in diabetes retinopathy based on weighted gene co-expression network

  • Lin-Hui Yuan,
  • Li-Jun Zhang,
  • Xin Liu,
  • Yuan-Yuan Qi

DOI
https://doi.org/10.3980/j.issn.1672-5123.2023.8.20
Journal volume & issue
Vol. 23, no. 8
pp. 1343 – 1351

Abstract

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AIM: To explore the key genes related to immunity and immune cell infiltration levels in diabetes retinopathy(DR)using bioinformatics.METHODS: Differential expression genes(DEGs)were obtained by “limma” R from Gene Expression Omnibus(GEO)data from September to October 2022, Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)were analyzed, and the infiltration of immune cell types in each sample was calculated based on CIBERSORT algorithm. Weighted gene co-expression network analysis(WGCNA)was used to screen for DEGs in immune-related gene modules. The protein-protein interaction(PPI)network was established by STRING online database and Cytoscape, and the hub genes were screened by MCODE and cytoHubba plug-ins.RESULTS: The results showed that 1 426 up-regulated and 206 down-regulated differential genes were screened, where 7 immune cell types, including B cell naive, Plasma cells, CD4+T cells, T cells regulatory(Tregs), Macrophages M0, Macrophages M1 and Neutrophils were significantly overexpressed(P<0.05), while others were low expressed(P<0.05). After WGCNA, a total of 820 DEGs were found in the modules most related to immunity. After constructing the PPI network, 10 key genes were screened using plug-ins, and two key genes were further screened using the expression amount of each differential gene in PPI: DLGAP5 and AURKB.CONCLUSION: This study used bioinformatics to screen the infiltration of immune cells and key genes related to immunity in patients with DR. These findings may provide evidences for future research, diagnosis, and treatment of DR.

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