Identification of drug candidate for osteoporosis by computational bioinformatics analysis of gene expression profile

BACKGROUND: Osteoporosis is a condition of bones that leads to an increased susceptibility to fracture and consequent painful morbidity. It has become a major issue of life quality worldwide. However, until now, the molecular mechanism of this disease is far from being clear. METHODS: In this study, we obtained the gene expression profile of osteoporosis and controls from Gene Expression Omnibus and identified differentially expressed genes (DEGs) using classical t-test method. Then, functional enrichment analyses were performed to identify the dysregulated Gene Ontology categories and dysfunctional pathways in osteoporosis patients compared to controls. Besides, the connectivity map was used to identify compounds that induced inverse gene changes to osteoporosis. RESULTS: A total of 5581 DEGs were identified. We found these DEGs were enriched in 9 pathways by pathway enrichment analysis, including focal adhesion and MAPK signaling pathway. Besides, sanguinarine was identified as a potential therapeutic drug candidate capable of targeting osteoporosis. CONCLUSION: Although candidate agents identified by our approach may be premature for clinical trials, it is clearly a direction that warrants additional consideration.