Quantitative proteomics and reverse engineer analysis identified plasma exosome derived protein markers related to osteoporosis.

Alongside an aging population, osteoporosis has become increasingly common, representing a major public health problem. Human blood provides the predominant matrix for pathological targets underlining disease mechanisms. In the present study, the protein profiles of blood plasma exosomes from patients with osteoporosis, osteopenia, and those with normal bone mass were compared. The aim of the study was to search for potential novel diagnostic/therapeutic targets for further investigation in osteoporosis. A total of 60 participants were included from the PLAGH Hip Fracture Database. Quantitative proteomics was carried out to profile the plasma exosome derived proteins from patients diagnosed with osteoporosis, osteopenia, and normal bone mass, respectively. A Parallel reaction monitoring (PRM) analysis was further carried out to validate the identified proteins. Bio-informatics analyses including GO annotation and reverse engineering of gene regulatory networks analysis were applied in annotating the biological relevance of the identified proteins. Forty-five differentially expressed proteins were identified in the discovery dataset and four of them, PSMB9, AARS, PCBP2, and VSIR were further verified in a validation set. Based on the results, an exosomal-proteins index was constructed to classify individuals with osteoporosis from those without, an AUC of 0.805 (95% CI 0.620-0.926, p < 0.001) was achieved in classification performance assessment. Additionally, a reverse engineer of the regulatory network analysis identified and predicted the proteins which may interact with the four target proteins identified, providing references for further investigations into the pathological mechanisms of osteoporosis.