In silico analysis of the molecular mechanism of postmenopausal osteoporosis

Postmenopausal osteoporosis (PO) is a common disease in females >50 years of age worldwide and is becoming an increasing burden to society. The present study aimed to assess the molecular mechanism of PO using bioinformatic methods. The gene expression data from patients with PO and normal controls were downloaded from the ArrayExpress database provided by European Bioinformatics Institute. Following the screening of the differentially expressed genes (DEGs) using the Limma package in R language, Kyoto Encyclopedia of Genes and Genomes pathways enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery online tools. Sequentially, modulators of the DEGs, including transcription factors (TFs) and microRNAs, were predicted by the ChIP Enrichment Analysis databases and WEB‑based GEne SeT AnaLysis Toolkit system, respectively. In addition, the protein‑protein interaction network of DEGs was constructed via the search tool for the retrieval of interacting genes and then the functional modules were further analyzed via the clusterMaker package and The Biological Networks Gene Ontology package within the Cytoscape software. A total of 482 DEGs, including 279 upregulated and 203 downregulated DEGs, were screened out. DEGs were predominantly enriched in the pathways of fatty acid metabolism, cardiac muscle contraction and DNA replication. TFs, including SMAD4, in addition to microRNAs, including the microRNA‑125 (miR‑125) family, miR‑331 and miR‑24, may be the modulators of the DEGs in PO. In addition, the five largest modules were identified with TTN, L1G1, ACADM, UQCRC2 and TRIM63 as the hub proteins, and they were associated with the biological processes of muscle contraction, DNA replication initiation, lipid modification, generation of precursor metabolites and energy, and regulation of acetyl‑CoA biosynthetic process, respectively. SMAD4, CACNG1 and TRIM63 are suggested to be important factors in the molecular mechanisms of PO, and miR‑331 may be novel potential biomarker for PO.