Identification of Diagnostic Genes and Effective Drugs Associated with Osteoporosis Treatment by Single-Cell RNA-Seq Analysis and Network Pharmacology

Abstract

Background. Osteoporosis is a common bone metabolic disease with increased bone fragility and fracture rate. Effective diagnosis and treatment of osteoporosis still need to be explored due to the increasing incidence of disease. Methods. Single-cell RNA-seq was acquired from GSE147287 dataset. Osteoporosis-related genes were obtained from chEMBL. Cell subpopulations were identified and characterized by scRNA-seq, t-SNE, clusterProfiler, and other computational methods. “limma” R packages were used to identify all differentially expressed genes. A diagnosis model was build using rms R packages. Key drugs were determined by proteins-proteins interaction and molecular docking. Results. Firstly, 15,577 cells were obtained, and 12 cell subpopulations were identified by clustering, among which 6 cell subpopulations belong to CD45+ BM-MSCs and the other subpopulations were CD45-BM-MSCs. CD45- BM-MSCs_6 and CD45+ BM-MSCs_5 were consider as key subpopulations. Furthermore, we found 7 genes were correlated with above two subpopulations, and F9 gene had highest AUC. Finally, five compounds were identified, among which DB03742 bound well to F9 protein. Conclusions. This work discovered that 7 genes were correlated with CD45-BM-MSCs_6 and CD45+ BM-MSCs_5 subpopulations in osteoporosis, among which F9 gene had better research value. Moreover, compound DB03742 was a potential inhibitor of F9 protein.