Identification Of Osteoporosis Markers Through Bioinformatic Functional Analysis Of Serum Proteome

Osteoporosis is a severe chronic skeletal disorder that increases the risks of disability and mortality; however, the mechanism of this disease and the protein markers for prognosis of osteoporosis have not been well characterized. This study aims to characterize the imbalanced serum proteostasis, the disturbed pathways, and potential serum markers in osteoporosis by using a set of bioinformatic analyses. In the present study, the large-scale proteomics datasets (PXD006464) were adopted from the Proteome Xchange database and processed with MaxQuant. The differentially expressed serum proteins were identified. The biological process and molecular function were analyzed. The protein-protein interactions and subnetwork modules were constructed. The signaling pathways were enriched. We identified 209 upregulated and 230 downregulated serum proteins. The bioinformatic analyses revealed a highly overlapped functional protein classification and the gene ontology terms between the upregulated and downregulated protein groups. Protein-protein interactions and pathway analyses showed a high enrichment in protein synthesis, inflammation, and immune response in the upregulated proteins, and cell adhesion and cytoskeleton regulation in the downregulated proteins. Our findings greatly expand the current view of the roles of serum proteins in osteoporosis and shed light on the understanding of its underlying mechanisms and the discovery of serum proteins as potential markers for the prognosis of osteoporosis.