BackgroundDiabetic retinopathy (DR) is one of the most common microvascular complications of diabetes, which is associated with damage of blood-retinal barrier and ischemia of retinal vasculature. It devastates visual acuity due to leakage of retinal vessels and aberrant pathological angiogenesis in diabetic patients. The etiology of DR is complex, accumulated studies have shown that autophagy plays an important role in the pathogenesis of DR, but its specific mechanism needs to be further studied.MethodsThis study chose the online Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE146615 to carry on the research. Autophagy-related genes that were potentially differentially expressed in DR were screened by R software. Then, the differentially expressed autophagy-related genes were analyzed by correlation analysis, tissue-specific gene expression, gene-ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) network analysis. Finally, retinal pigment epithelial cell line (ARPE-19) incubated with high glucose (HG) was used to mimic the DR model, and the mRNA level of key genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR) in vitro.ResultsA total of 23 differentially expressed autophagy-related genes (9 up-regulated genes and 14 down-regulated genes) were identified by differential expression analysis. The analysis of tissue-specific gene expression showed that these differentially expressed autophagy-related genes were enriched in the retina. GO and KEGG enrichment analysis showed that differentially expressed autophagy-related genes were significantly enriched in autophagy-related pathways such as regulation of autophagy and macroautophagy. Then 10 hub genes were identified by PPI network analysis and construction of key modules. Finally, qRT-PCR confirmed that the expression of MAPK3 in the DR model was consistent with the results of bioinformatics analysis of mRNA chip.ConclusionThrough bioinformatics analysis, we identified 23 potential DR autophagy-related genes, among which the down-regulated expression of MAPK3 may affect the occurrence and development of DR by regulating autophagy. It provides a novel insight into the pathogenesis of DR.
Background. Ferroptosis, a type of cell death caused by phospholipid peroxidation, has lately been linked to the onset and development of numerous illnesses. Numerous investigations have demonstrated the close relationship between lipid peroxidation and carotid atherosclerosis. In order to get new knowledge for targeted therapy, bioinformatics analysis was employed in this study to discover the probable ferroptosis-related genes of carotid atherosclerosis. Methods. The GSE43292 gene expression dataset was downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed ferroptosis-related genes were screened by R software and then analyzed by protein-protein interaction (PPI) network, differential gene correlation analysis, Kyoto Encyclopedia of Gene and Genome (KEGG) pathway, and Gene Ontology (GO) terminology enrichment analysis to explore the functional role. Result. In samples of atherosclerosis, we found 33 ferroptosis genes that were differentially expressed, including 21 upregulated genes and 12 downregulated genes. These differentially elevated genes were mainly connected to the ferroptosis and glutathione metabolism pathways, according to GO and KEGG enrichment analysis. We also discovered 10 hub genes and 2 important modules through the analysis of the PPI network and the creation of key modules. Conclusion. The current findings imply that the carotid atherosclerosis phenomenon involves ferroptosis, and 10 important genes associated to ferroptosis may play a role in the development of carotid atherosclerosis. This study offered a novel approach to future research on the carotid atherosclerosis pathogenic processes and treatment targets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.