We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.Aims
Methods
During the last decades, several research groups have used bisphosphonates for local application to counteract secondary bone resorption after bone grafting, to improve implant fixation or to control bone resorption caused by bone morphogenetic proteins (BMPs). We focused on zoledronate (a bisphosphonate) due to its greater antiresorptive potential over other bisphosphonates. Recently, it has become obvious that the carrier is of importance to modulate the concentration and elution profile of the zoledronic acid locally. Incorporating one fifth of the recommended systemic dose of zoledronate with different apatite matrices and types of bone defects has been shown to enhance bone regeneration significantly
