Two Predictive Competitive Endogenous RNA Regulatory Networks Were Used To Distinguish Early And Late Osteoarthritis And Its Immune Landscape

Objective:The purpose of this study is to analyze the database related to osteoarthritis(OA)through bioinformatics methods,screen biomarkers and their immune landscape for distinguishing early and late osteoarthritis,and provide important information for the diagnosis and treatment of OA.Methods:From GEO database(http://www.ncbi.nlm.nih.gov/geo),by searching "osteoarthritis" and "synovium",the species is selected as "Homo sapiens".After screening,three data sets GSE55235,GSE55457 and GSE55584 from GPL96 were finally obtained.Similarly,after screening,GSE1919(GPL91 platform),GSE12021(GPL96platform),GSE105027(GPL21575 platform)and GSE151341(GPL21697 platform)are obtained as verification sets.Use the "in Silico Merging","limma","ggplot2" and other packages in R software to merge data sets,remove batch effects,screen and visualize differentially expressed genes(DEGs).The tissue-specific genes were determined by inputting differentially expressed genes(DEGs)into the Human Protein Atlas.Next,GO enrichment analysis was performed on all DEGs through the Cytoscape plug-in "Clue GO".The hub gene was further screened by constructing PPI network,random forest and WGCNA.Next,the interaction between miRNAs and lncRNAs was predicted in the hub gene by Starbase v3.0 and Cytascape,and a potential ceRNA network was constructed.The hub gene and target miRNAs were verified to determine the relationship between hub gene and immune cells.Results:182 differentially expressed genes were screened from the comprehensive data set obtained from the gene expression database(GEO),including 134 down-regulated genes and 48 up-regulated genes.We imported all DEGs into the human protein map database to determine their tissue specificity,and found that 94 genes have tissue specificity.We enriched and analyzed all DEGs through KEGG and Reactome,and found that DEGs played an important role in regulating our body’s immune microenvironment and cell signal transduction.Next,three immune system-specific hub genes were analyzed by PPI network as follows: NFKBIA,IL1 B and CXCL8.Using the expression matrix of 20 NM and 26 OA samples for WGCNA detection,two final hub genes were obtained,and the ROC curve confirmed that these two genes had high diagnostic validity in OA.In addition,we proved the significant correlation between NFKBIA/CXCL8 and resting mast cells by GSVA,Wilcoxon rank sum test and CIBERSORT.The interaction between NFKBIA/CXCL8 and miRNAs was studied through online database,and the relevant ceRNA network was constructed.This ceRNA network can be used to distinguish early and late osteoarthritis,including three microRNAs(hsa-miR-493-255 p,hsa-miR-381-3p and hsa-miR-889-3p)and two long-chain non-coding RNAs(NEAT1 and XIST).Conclusion:In this study,we revealed the association between OA and two immune system-specific genes NFKBIA and CXCL8.In addition,we have constructed two ceRNA networks,which may serve as potential biomarkers to distinguish early and late OA.In addition,we verified the diagnostic value of these two networks,and confirmed the relationship between resting mast cells and two ceRNA networks.These two ceRNA networks may provide new insights for the early diagnosis and improvement of prognosis of osteoarthritis.