Abstract:
Objective To search for potential diagnostic markers of osteoporosis (OP) and analyze the roles of immune infiltration in the development of OP.
Methods Gene expression profile datasets derived from the Gene Expression Omnibus database (GEO) were first used to identify differentially expressed genes(DEGs) for OP. Then, the underlying mechanisms of DEGs were revealed by enrichment analysis. Least Absolute Shrinkage and Selection Operator (LASSO) Logistic regression and support vector machine recursive feature elimination algorithm (SVM-RFE) were used to screen and validate the diagnostic markers of OP. CIBERSORT was used to evaluate the infiltration of immune cells in OP tissues, and the correlations between the diagnostic markers and immune cell infiltration were detected.
Results In this study, five diagnostic genes were selected as key genes: SKAP2, SLC30A3, TDRD12, RPL10 and CSPP1. SKAP2, SLC30A3, TDRD12, RPL10 and CSPP1 were identified as diagnostic markers of OP. SKAP2, SLC30A3, TDRD12 and RPL10 combined with CSPP1 had higher diagnostic efficiency. The heat maps of 22 kinds of immune cells showed that activated mast cells were positively correlated with plasma cells, and resting mast cells positively correlated with eosinophils. In addition, activated CD4 memory T cells were negatively correlated with regulatory T cells, and macrophages were negatively correlated with memory B cells.
Conclusion Immune cell infiltration is crucial in the occurrence and development of OP. Resting CD4 memory T cells and M2 macrophages may be involved in the pathogenesis of osteoporosis. These results help to provide new ideas for the diagnosis and treatment of OP.
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