Genomic Expression Profiling and Bioinformatics Analysis of Chronic Recurrent Multifocal Osteomyelitis | Zendy

Kai Huang | Zendy; Bingyuan Lin | Zendy; Yiyang Liu | Zendy; Qiaofeng Guo | Zendy; Haiyong Ren | Zendy

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Genomic Expression Profiling and Bioinformatics Analysis of Chronic Recurrent Multifocal Osteomyelitis

Author(s) -

Kai Huang,

Bingyuan Lin,

Yiyang Liu,

Qiaofeng Guo,

Haiyong Ren

Publication year - 2021

Publication title -

biomed research international

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.772

H-Index - 126

eISSN - 2314-6141

pISSN - 2314-6133

DOI - 10.1155/2021/6898093

Subject(s) - kegg , chronic recurrent multifocal osteomyelitis , gene , biology , gene expression profiling , gene expression , proteomics , ribosomal protein , dna microarray , computational biology , genetics , bioinformatics , ribosome , transcriptome , immunology , osteomyelitis , rna , osteitis

Objective Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disorder. Its most severe form is referred to as chronic recurrent multifocal osteomyelitis (CRMO). Currently, the exact molecular pathophysiology of CNO/CRMO remains unknown. No uniform diagnostic standard and treatment protocol were available for this disease. The aim of this study was to identify the differentially expressed genes (DEGs) in CRMO tissues compared to normal control tissues to investigate the mechanisms of CRMO.Materials Microarray data from the GSE133378 (12 CRMO and 148 matched normal tissue samples) data sets were downloaded from the Gene Expression Omnibus (GEO) database. DEGs were identified using the limma package in the R software. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) network analysis were performed to further investigate the function of the identified DEGs.Results This study identified a total of 1299 differentially expressed mRNAs, including1177 upregulated genes and 122 downregulated genes, between CRMO and matched normal tissue samples. GO analyses showed that DEGs were enriched in immune-related terms. KEGG pathway enrichment analyses showed that the DEGs were mainly related to oxidative phosphorylation, ribosome, and Parkinson disease. Eight modules were extracted from the gene expression network, including one module constituted with immune-related genes and one module constituted with ribosomal-related genes.Conclusion Oxidative phosphorylation, ribosome, and Parkinson disease pathways were significantly associated with CRMO. The immune-related genes including IRF5, OAS3, and HLA-A, as well as numerous ribosomal-related genes, might be implicated in the pathogenesis of CRMO. The identification of these genes may contribute to the development of early diagnostic tools, prognostic markers, or therapeutic targets in CRMO.

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