Hierarchical Porous Microspheres-Assisted Serum Metabolic Profile for the Early Diagnosis and Surveillance of Postmenopausal Osteoporosis

With the aging global population, the incidence of osteoporosis (OP) is increasing, putting more individuals at risk. Since postmenopausal osteoporosis (PMOP) often remains asymptomatic until a fracture occurs, making the early clinical diagnosis of PMOP particularly challenging. In this work, the AuNPs-anchored hierarchical porous ZrO₂ microspheres (Au/HPZOMs) is designed to assist laser desorption/ionization mass spectrometry (LDI-MS) for the requirement of serum metabolic fingerprints of PMOP, postmenopausal osteopenia (PMON), and healthy controls (HC) and realize the early diagnosis and surveillance of PMOP. With its large surface area, suitable surface roughness, and enhanced UV absorbance, the LDI efficiency of Au/HPZOMs is significantly enhanced. Combining machine learning, PMOP and non-PMOP (HC and PMON) are clearly distinguished with the area under the receiver operating characteristic curves reaching up to 1.000. Furthermore, seven key m/z features are identified, facilitating the specific detection of PMON and two stages of PMOP. The precision of distinguishing PMON and PMOP at different stages based on these features exceeds 86.5% in both the training and validation sets, aiding in the early diagnosis and monitoring of PMOP. This work sheds light on the metabolic profile for large-scale screening, early detection, and monitoring of PMOP, which will promote the application of fluid metabolism-driven precision medicine into practical clinical use.