Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis

Medicine
Naiqiang ZhuYouxin Song

Abstract

Rheumatoid arthritis (RA) and osteoarthritis (OA) comprise the most common forms of arthritis. The aim of this study was to identify differentially expressed genes (DEGs) and associated biological processes between RA and OA using a bioinformatics approach to elucidate their potential pathogenesis.The gene expression profiles of the GSE55457 datasets, originally produced through use of the high-throughput Affymetrix Human Genome U133A Array, were downloaded from the Gene Expression Omnibus (GEO) database. The GSE55457 dataset contains information from 33 samples, including 10 normal control (NC) samples, 13 RA samples, and 10 OA samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to identify functional categories and associated molecular and biochemical pathways, respectively, for the identified DEGs, and a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software.GO and KEGG results suggested that several biological pathways (ie, "immune response," "inflammation," and "osteoclast differentiation") are commonly involved in the development of both RA and OA, whereas several other pathways (eg, "MAPK signaling pathway," and ...Continue Reading

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Citations

Jul 16, 2020·International Journal of Molecular Sciences·Dmitry S MikhaylenkoAndrey A Zamyatnin

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Datasets Mentioned

BETA
GSE55457

Software Mentioned

MCODE
GeneSpring
DAVID
CytoHubba
Cytoscape

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