Eur Rev Med Pharmacol Sci 2023; 27 (11): 4876-4882
DOI: 10.26355/eurrev_202306_32604

Identification of hub genes correlated with diabetic retinopathy via bioinformatics methods

J.-H. Xiong, J.-L. Chen, J.-Y. Liang, F.-F. Zhang, S.-M. Cheng

School of Chinese Medicine, Jiangxi University of Chinese Medicine, Nanchang, China. gedrg@stu.cuz.edu.cn


OBJECTIVE: The aim of this study was to identify the hub genes and uncover the molecular mechanisms of diabetic retinopathy (DR).

MATERIALS AND METHODS: We used the Gene Expression Omnibus (GEO) dataset GSE60436 in our study. After screening for differentially expressed genes (DEGs), we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. Subsequently, a protein-protein interaction (PPI) network was constructed using the Search Tool for Retrieval of Interacting Genes (STRING) database and visualized using the Cytoscape software. Finally, we identified 10 hub genes by cytoHubba plugin.

RESULTS: A total of 592 DEGs were identified, including 203 up-regulated genes and 389 downregulated genes. The DEGs were mainly enriched in visual perception, photoreceptor outer segment membrane, retinal binding, and PI3K-Akt signaling pathway. By constructing a protein-protein interaction (PPI) network, 10 central genes were finally identified, including CNGA1, PDE6G, RHO, ABCA4, PDE6A, PDE6B, NRL, RPE65, GUCA1B and AIPL1.

CONCLUSIONS: CNGA1, PDE6G, RHO, ABCA4, PDE6A, PDE6B, NRL, RPE65, GUCA1B, and AIPL1 may be potential biomarkers and therapeutic targets for DR.

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To cite this article

J.-H. Xiong, J.-L. Chen, J.-Y. Liang, F.-F. Zhang, S.-M. Cheng
Identification of hub genes correlated with diabetic retinopathy via bioinformatics methods

Eur Rev Med Pharmacol Sci
Year: 2023
Vol. 27 - N. 11
Pages: 4876-4882
DOI: 10.26355/eurrev_202306_32604