Affiliation:
1. Department of Rheumatology, Guangxi International Zhuang Medicine Hospital, Nanning, Guangxi, 530201, China
2. Department of Ultrasound, Guangxi International Zhuang Medicine Hospital, Nanning, Guangxi, 530201, China
3. Graduate School, Guangxi University of Chinese Medicine, Nanning, Guangxi, 530201, China
4. Department of Cardiology, Guangxi International Zhuang Medicine Hospital, Nanning, Qiuyue Road No. 8, Liang Qing District, Nanning, Guangxi Zhuang Autonomous Region, 530201, China
Abstract
Objective. To explore the regulatory functions of ceRNA networks in the nosogenesis of gout and search for potential therapeutic targets. Methods. We searched the GEO database and downloaded the lncRNA microarray chipset GSE160170. This matrix series was analyzed to yield differentially expressed lncRNAs and mRNAs. Then, the correlations between lncRNAs and miRNAs were obtained by comparing the highly conserved miRNA families. The predicted miRNA-regulating mRNAs were matched to the differentially expressed mRNAs from the chipset analyses to obtain miRNA–mRNA interactions. Next, we used the Cytoscape software to model ceRNA networks and the STRING database to determine their protein–protein interactions. The R software was used to algorithmically screen the functional pathways of key PPI modules in the ceRNA networks. Results. A total of 354 lncRNAs (140 downregulated and 214 upregulated) and 693 mRNAs (399 downregulated and 294 upregulated) were differentially expressed between the gout group and the healthy group. The ceRNA network of differentially expressed lncRNAs contained 86 lncRNAs (35 downregulated and 51 upregulated), 29 miRNAs, and 57 mRNAs. The processes identified in the GO enrichment analysis included gene transcription, RNA polymerase II transcription, and the regulation of cell growth and apoptosis. The pathways identified in the KEGG enrichment analysis included IL-17, TNF, and MAPK signaling. Nine lncRNAs (AC104024, AC084082, AC083843, FAM182A, AC022819, FAM215B, AP000525, TTTY10, and ZNF346-IT1), eleven miRNAs (hsa-miR-1297, hsa-miR-17-5p, hsa-miR-429, hsa-miR-139-5p, hsa-miR-449c-5p, hsa-miR-125a-5p, hsa-miR-125b-5p, hsa-miR-23b-3p, hsa-miR-217, hsa-miR-363-3p, and hsa-miR-20b-5p), and nine mRNAs (JUN, CASP2, PMAIP1, FOS, TNFAIP3, MAP3K8, BTG2, NR4A2, and DUSP2) were identified in the exploration of the key modules. Conclusion. Characterization of ceRNA networks could be a promising approach for better understanding the pathogenesis of gout, with the TTTY10/hsa-miR-139-5p/AP-1 axis likely to be of clinical significance.
Funder
Guangxi University of Chinese Medicine
Subject
Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine
Cited by
3 articles.
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