Expression of immune-related genes in rheumatoid arthritis and a two-sample Mendelian randomization study of immune cells
- VernacularTitle:类风湿性关节炎中免疫相关基因表达及免疫细胞的双样本孟德尔随机化分析
- Author:
Yidong FAN
1
;
Gang QIN
;
Kaiyi HE
;
Yufang GONG
;
Weicai LI
;
Guangtao WU
Author Information
- Keywords: rheumatoid arthritis; machine learning; immune infiltration; genome-wide association studies; Mendelian randomization
- From: Chinese Journal of Tissue Engineering Research 2024;28(27):4312-4318
- CountryChina
- Language:Chinese
- Abstract: BACKGROUND:Rheumatoid arthritis is a chronic systemic autoimmune disease.It is important to study the immunological changes involved in it for diagnosis and treatment. OBJECTIVE:To identify immune-related biomarkers associated with rheumatoid arthritis utilizing bioinformatics techniques and examine alterations in immune cell infiltration as well as the relationship between immune cells and biomarkers. METHODS:Differential expression analysis was used to identify the immune-related genes that were up-regulated in rheumatoid arthritis based on the GEO and Immport databases.Kyoto encyclopedia of genes and genomes(KEGG)and gene ontology(GO)enrichment analyses were used to investigate the possible function of these elevated genes.The immunological characteristic genes associated with rheumatoid arthritis were screened using least absolute shrinkage and selection operator(Lasso)and support vector machine recursive feature elimination(SVM-RFE).Independent datasets were used for difference validation,and the diagnostic performance was evaluated by plotting receiver operating characteristic curves for feature genes.Immune cell infiltration was used to analyze the differential profile of immune cells in rheumatoid arthritis and the correlation between the characterized genes and immune cells.In order to ascertain the causal relationship between monocytes and rheumatoid arthritis in immune cells,Mendelian randomization analysis was ultimately employed. RESULTS AND CONCLUSION:There were 39 upregulated differentially expressed genes in rheumatoid arthritis.The genes were primarily enriched in chemotaxis,cytokine activity,and immune receptor activity,according to GO enrichment analysis,while kEGG enrichment analysis revealed that the genes were considerably enriched in the tumor necrosis factor signaling pathway and peripheral leukocyte migration.Lasso and SVM-RFE identified five feature genes:CXCL13,SDC1,IGLC1,PLXNC1,and SLC29A3.Independent dataset validation of the feature genes found them to be similarly highly expressed in rheumatoid arthritis samples,with area under the curve values greater than 0.8 for all five feature genes in both datasets.Immune cell infiltration indicated that most immune cells,including natural killer cells and monocytes,exhibited increased levels of infiltration in rheumatoid arthritis samples.The correlation analysis revealed a significant positive correlation between memory B cells and immature B cells and these five feature genes.Correlation analysis showed that the five feature genes were positively correlated with memory B cells and immature B cells.The inverse variance weighting method revealed that monocytes were associated with the risk of developing rheumatoid arthritis.
