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Identification of potential biomarkers of gout through competitive endogenous RNA network analysis.

作者信息

Li Yang, Huang Chengcheng, Yang Zhenguo, Wang Lei, Luo Dan, Qi Lu, Li Zhichao, Huang Yanqin

机构信息

Department of orthopedics, The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250000, China.

Department of Endocrinology and Metabology, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250000, China.

出版信息

Eur J Pharm Sci. 2022 Jun 1;173:106180. doi: 10.1016/j.ejps.2022.106180. Epub 2022 Apr 1.


DOI:10.1016/j.ejps.2022.106180
PMID:35378210
Abstract

OBJECTIVE: Gout is a widespread inflammatory arthritis. The present study aimed to identify potential biomarkers of gout and explore their underlying mechanisms through bioinformatics methods. METHODS: The microarray data was downloaded from the GSE160170 dataset from the Gene Expression Omnibus (GEO) database, and the GEO2R online tool was used to obtain differentially expressed genes (DEGs). We searched for gout-related genes through the DisGeNET and GeneCards databases, and the final DEGs was acquired by intersection with the DEGs obtained from the microarray dataset. Tissue- and organ-specific genes were identified by the BioGPS online tool. Enrichment analysis was performed using GSEA4.1.0 and KOBAS3.0, and a protein-protein interaction (PPI) network was constructed using STRING to understand the biological functions and enrichment pathways of the DEGs as well as to identify their hub genes. Cytoscape was used to construct the competitive endogenous RNA (ceRNA) networks. RESULTS: A total of 653 differentially expressed lncRNAs (DElncRNAs) and 818 differentially expressed mRNAs (DEmRNAs) were identified in the present study. After intersecting the differential DEGs from the dataset, 85 DEGs were obtained. Enrichment analyses showed that the DEGs were mainly enriched in the following biological processes (BPs): inflammation and regulation; immune response; and cell proliferation and apoptosis. Moreover, the DEGs were mainly enriched in rheumatoid arthritis (RA), osteoclast differentiation, interleukin (IL)-17 signaling pathway, nuclear factor kappa B (NF-κB) signaling pathway, Toll-like receptor signaling pathway and tumor necrosis factor (TNF) signaling pathway. Cytoscape software identified 15 hub genes, and the following 9 hub genes were obtained after intersecting with genes specifically expressed in the blood/immune and bone/muscle systems: TNF, JUN, PTGS2, STAT1, IL6, FOS, IL1β, CXCL8 and CD80. In addition, the lncRNA-NEAT1-miR-142-3p-IL-6 pathway may be a key regulatory pathway in the pathogenesis of gout. CONCLUSIONS: The present study indicated that the identified 9 hub genes may be potential biomarkers for the diagnosis and treatment of gout. In addition, the results suggested that the lncRNA-NEAT1-miR-142-3p-IL-6 pathway may be a potential RNA regulatory pathway that controls the progression of gout disease.

摘要

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Identification of potential biomarkers of gout through competitive endogenous RNA network analysis.

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[2]
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[3]
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[4]
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[5]
Expressions of Peptidoglycan Recognition Protein 1, Neuron Towards Axon Guidance Factor-1 and miR-142-3p and Their Correlations in Patients with Rheumatoid Arthritis.

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[6]
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[7]
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