| ObjectiveBioinformatics analysis was used to screen and identify biomarkers related to the pathogenesis of Osteoarthritis(OA),to explore its possible pathogenesis and predictive efficacy,and to search for possible drug targets.At the same time,the ability of Mesenchymal stem cells(MSC)to repair OA knee tenderness was evaluated to provide a scientific basis for the diagnosis and treatment of OA and the prognosis of OA.Materials and Methods(1)Screening of differential genes: GSE1919,GSE55235 and GSE55457 data sets were obtained from GEO(Gene Expression Omnibus)database,and fold change were calculated by GEO2 R.The screening criteria were P<0.05,|log2FC| >1.The volcano map is drawn by the Limma package of R software.(2)Enrichment analysis of differential genes and protein interaction network diagram: the intersection of the Venn diagram was used to obtain the common differentially expressed genes in the three data sets,and the GO function enrichment and KEGG signaling pathway enrichment analysis were conducted on the David platform to further map the protein interaction network.(3)Functional analysis,diagnostic efficacy and drug interaction analysis of pivot genes: The key modules were screened by MCODE plug-in,and the key genes regulating the pathogenesis of OA were defined according to Degree ≥10,and the biological functions of the key genes were analyzed.The ROC curve was drawn according to the gene expression,and the predictive ability of the gene on the disease was evaluated by the AUC value,and the drug-hub gene interaction network was drawn.(4)The databases including Cochrane library,Pubmed,Embase(via Ovid),CNKI and Wanfang were searched from inception to March 2020.The clinical randomized controlled trials(RCTs)of MSC-based therapy in knee OA were conducted.Two independent reviewers selected studies and extracted information according to inclusion and exclusion criteria.The quality was assessed by Cochrane Handbook’s risk of bias tool.The Meta-analysis was conducted by Revman 5.3software.I2 was used for heterogeneity test,and random effects model was used for statistical analysis.Based on the Inverse-variance method,the Dersimonian & Laird method was used to introduce correction factors to correct the weights and then calculate the combined effect amount and its 95% confidence interval(CI).Results(1)Screening and enrichment analysis results of differential genes: Volcano map showed that there were significant differences in genes between OA patients and healthy controls.A total of 103 differential genes were screened out by Venn map,including 43 up-regulated genes and 49 down-regulated genes.GO functional analysis was mainly concentrated in biological processes,and differential genes were mainly concentrated in the positive regulation of cell proliferation,inflammatory response and immune response,etc.Differential genes were mainly concentrated in cytokine receptor interactions,PI3K-Akt signaling pathway,and osteoclast differentiation pathway.(2)Functional analysis of key genes: The key genes in the pathogenesis of OA were further identified,including IL-6,VEGFA,MYC,ATF3,PTPRC,FOSB,KLF4,CXCL2,and CDKN1 A.In biological processes,they are mainly enriched in the positive regulation of RNA polymerase II promoter transcription,the negative regulation of RNA polymerase II promoter transcription and the positive regulation of gene expression.In terms of cellular components,they were mainly concentrated in the nucleus and lateral plasma membrane.In terms of molecular function,it is mainly enriched in protein binding,transcription factor active sequence specific DNA binding and transcriptional activation activity.KEGG signaling pathway analysis was mainly concentrated in HTLV-I infection,PI3K-Akt signaling pathway and cancer-related pathway.(3)Analysis of diagnostic efficacy and drug interaction of hub genes: the AUC of each hub gene was > 0.7,P < 0.05.It indicates that they all have good ability to predict OA.FOSB,CXCL2 and CDKN1 A had the highest AUC,which had the best predictive efficacy and the strongest specificity for OA.A total of 94 drug-hub gene interaction pairs were identified,and VEGFA had the largest number of active drugs,up to 26.These genes can be used as potential diagnostic biomarkers and therapeutic targets.(4)Fifteen eligible clinical trials were included in this meta-analysis,with a total of 576 patients.Compared with the control group,our study showed that the VAS score[MD=-15.51,95%CI=(-24.29,-6.74),P=0.0005],WOMAC score[MD=-11.08,95%CI=(-16.78,-5.38),P=0.0001],and Lequesne index[MD=-8.45,95%CI=(-15.11,-1.80),P=0.01] were significantly decreased in the MSCs treatment group.In cumulative functional analysis[SMD=1.24,95%CI=(0.33,2,15),P=0.008] and Cumulative pain evaluation[SMD=-1.00,95%CI=(-1.47,-0.52),P<0.0001] there was a significant improvement after treatment.However,there was no statistical significance in Lysholm knee score and MRI evaluation results(P>0.05).ConclusionsIn this study,9 pivotal genes were screened in synovium cells of knee joint patients by bioinformatics analysis,which were IL-6,VEGFA,MYC,ATF3,PTPRC,FOSB,KLF4,CXCL2,and CDKN1 A,CXCL2 and CDKN1 A had the best predictive efficacy and the strongest specificity for OA.The PI3K-Akt signaling pathway and inflammatory cytokines such as IL-6 mediate the inflammatory effect of OA.The expression level of PTPRC is inconsistent in the three data sets,and its specific trend remains to be verified.The molecular regulatory mechanisms of FOSB and KLF4 in OA still need to be further studied.Intra-articular injection of mesenchymal stem cells is effective and safe for pain control and functional improvement in patients with osteoarthritis of the knee,but the evidence for repair of damaged cartilage by MSCs is insufficient in the present study. |
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