Machine learning-based screening of diagnostic marker genes for rheumatoid arthritis and analysis of immune infiltration

LI Ling-qin; ZHOU Rui-jiao; ZHANG Yan-ni

doi:10.3969/j.issn.1674-3806.2023.12.07

Abstract：Objective To screen the diagnostic marker genes of rheumatoid arthritis(RA)and analyze the pos-sible immune infiltration mechanism based on bioinformatics and machine learning,and to provide reference for the clinical treatment of RA.Methods The gene expression profiles were downloaded from the Gene Expression Omnibus(GEO)data-base.GSE55235 and GSE77298 were used as the combined chip training set,and GSE55457 was used as the independent validation dataset.The differentially expressed genes(DEGs)were screened using R software,and Gene Ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were performed for these DEGs.Three machine learning algorithms were further applied to screen the diagnostic genes and perform the external validation and receiver operating characteristic(ROC)curve analysis.Finally,the xCell method was used to calculate the infiltration of immune cell types in the RA.The infiltration of immune cells in RA was analyzed by using xCell algo-rithm.Results A total of 704 DEGs of RA were screened.The results of enrichment analysis revealed that these DEGs were mainly involved in some related immune functions,such as leukocyte-mediated immunity,activation of immune response,and leukocyte migration,and some inflammatory pathways,such as chemokine signaling pathway,Leishmani-asis and Rheumatoid arthritis.Four diagnostic genes,including C-X-C motif chemokine ligand 13(CXCL13),leucine rich repeat containing 15(LRRC15),syndecan 1(SDC-1)and Y-box binding protein 3(YBX3),were screened using machine learning.The results of the immune infiltration analysis showed that the expression levels of B cells,CD4+T cells,dendritic cells and monocytes were significantly up-regulated in RA.Conclusion Multiple genes and path-ways are involved in the occurrence and development of RA.CXCL13,LRRC15,SDC-1 and YBX3 may be the poten-tial biomarkers for the diagnosis of RA.Moreover,B cells,CD4+T cells,dendritic cells and monocytes may play an important role in the occurrence of RA.