Bioinformatics analysis reveals the key factors affecting the progress of osteoporosis

Abstract

The incidence rate of osteoporosis is high, and patients usually have decreased bone density and increased risk of fracture, which seriously affects their quality of life. This study aims to reveal key biomarkers that affect the progression of osteoporosis through bioinformatics methods. This study selected the GSE91033 and GSE93883 datasets for analysis, and obtained differentially expressed miRNAs using the GEO2R analysis tool; Predicting potential miRNA target factors through miRDIP and conducting pathway enrichment analysis of target factors through DAVID database; Analyze the interaction relationships between target factors through the STRING database, and construct a protein interaction network and a miRNA mRNA interaction network. The results showed that 73 and 79 differentially expressed genes were obtained in the GSE91033 and GSE93883 datasets, respectively. Common genes included hsa-miR-4508, hsa-miR-660-5p, and hsa-miR-424-5p. Pathway enrichment analysis showed that downstream target factors of differentially expressed miRNAs involved PIK/AKT, Wnt, Hippo, MAPK, and NF-κB pathway is closely related to cell proliferation and differentiation, and also involves intracellular phosphorylation activity. Protein interaction analysis revealed that CCND1, WEE1, MAP2K1, BTRC, FGF2, AXIN2, PTCH1, CCND2, KIF5C, DYNC1I1 and PAFAH1B1 are node genes involved in the progression of osteoporosis. The miRNA mRNA interaction network revealed that hsa-miR-424-5p is a key factor affecting the progression of osteoporosis.