Integrative Analyses of Genes Associated With Osteoporosis in CD16+ Monocyte - Hu, Bin; Kong, Xiangan; Li, Li; Dai, Fang; Zhang, Qiu; Shi, Ruifeng (Frontiers in Endocrinology, 2021)
Background: Osteoporosis is a metabolic bone disease that characterized by decreased bone mineral density and abnormal bone quality. Monocytes can secret cytokines for bone resorption, resulting bone mass loss. However, the mechanism of osteoporosis contributed by monocyte subsets is less clear. The aim of this study is to identify genes associated with osteopenia in monocytes subsets. Methods: Three microarray datasets from GSE7158 (transcription for low/high bone mass), GSE101489 (transcription for CD16+/CD16- monocyte) and GSE93883 (miRNA expression profile for osteoporosis) were derived from the Gene Expression Omnibus (GEO) database and analyzed with GEO2R tool to identify differentially expressed genes (DEGs). Functional enrichment was analyzed using Metascape database and GSEA software. STRING was utilized for the Protein-Protein Interaction Network construct. The hub genes were screened out using the Cytoscape software. Associated miRNA was predicted in miRWalk, miRDB and TargetScan databases. Results: Total 368 DEGs from GSE7158 were screened out, which were mostly enriched in signaling, positive regulation of biological process and immune system process. The hub genes were clustered into two modules by PPI network analysis. We identified 15 overlapped DGEs between GSE101489 and GSE7158 microarray datasets. Moreover, all of them were upregulated genes in both datasets. Then, 9 key genes were screened out from above 15 overlapped DEGs using Cytoscape software. It is a remarkable fact that the nine genes were all in one hub gene module of GSE7158. Additionally, 183 target miRNAs were predicted according to the above 9 DEGs. After cross-verification with miRNA express profile dataset for osteoporosis (GSE93883), 12 DEmiRNAs were selected. Finally, a miRNA-mRNA network was constructed with the 9 key genes and 12 miRNAs, which were involved in osteoporosis. Conclusion: Our analysis results constructed a gene expression framework in monocyte subsets for osteoporosis. This approach could provide a novel insight into osteoporosis.