Exploration of biomarkers in osteoarthritis based on bioinformatics

Abstract

Osteoarthritis (OA) seriously affects human health and brings a heavy social burden. This study aimed to identify new biomarkers involved in OA. Differential expression analysis and gene set enrichment analysis were performed on the microarray data set of OA. Identify key genes from immune-related DEGs and verify their expression in the validation set. CIBERSORT was used to analyze the infiltration of immune cells. The correlation between key genes and immune cells were conducted. A total of 1779 DEGs were identified in GSE82107. Gene set enrichment analysis results of top 4 for hallmark revealed the enrichment of DEGs were associated with genes in "HALLMARK_TNFA_SIGNALING_VIA_NFKB", "HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION", "HALLMARK_INFLAMMATORY_RESPONSE" and "HALLMARK_HYPOXIA". A total of 108 immune-related DEGs were identified from the overlap between 2498 immune-related genes and 1779 DEGs. The expression of top 6 immune-related DEGs including ADIPOQ, FABP4, FOS, IGLC1, IGLV1-44 and leptin were measured in the validation set, the results shown that IGLC1 and IGLV1-44 might play a key role in the synovial membrane of OA. A total of 8 kinds of cells including B cells memory, Plasma cells, T cells CD4 memory resting, T cells gamma delta, natural killer cells activated, macrophages M0, Mast cells resting and Mast cells activated have significant differences in infiltration between the OA group and the control group. Besides, the expressions of IGLC1 and IGLV1-44 are highly correlated. Our results indicated that IGLC1 and IGLV1-44 may play the role of immune-related biomarkers in OA.