Abstract
BACKGROUND: Osteoporosis represents a major global health challenge with increasing prevalence and substantial healthcare burden. Current diagnostic approaches relying primarily on bone mineral density measurements have limitations for early disease detection and understanding pathophysiological mechanisms. We conducted comprehensive metabolomic analysis of osteoporotic cancellous bone to identify potential metabolic features and explore disease mechanisms. METHODS: Hip cancellous bone samples from 18 osteoporotic patients and 18 age-matched non-osteoporotic controls were analyzed using dual-platform gas/liquid chromatography-mass spectrometry. Multivariate analysis combined with machine learning approaches identified metabolic patterns distinguishing osteoporotic from non-osteoporotic bone. RESULTS: Untargeted metabolomics of osteoporotic cancellous bone revealed widespread metabolic alterations. Key findings included significant reductions in amino acids (phenylalanine, glutamate, aspartate, lysine, arginine, serine, cystine), polyamines (spermidine), TCA intermediates (citrate, succinate), and purine nucleosides (adenosine, inosine, guanosine, inosine-2'-phosphate), together with decreased phospholipid precursors (phosphorylcholine, choline). In contrast, metabolites such as allantoic acid and inorganic sulfate were elevated. Pathway enrichment implicated amino acid, purine, energy, one-carbon, and phospholipid metabolism, converging on impaired osteoblast function, enhanced osteoclast activity, and oxidative stress. Statistically, inosine-2'-phosphate (AUC = 0.951) Allantoic acid (log2FC: 3.14785) and phenylalanine (log2FC: - 5.3884) showed strong discriminatory potential. CONCLUSIONS: This study provides the first comprehensive metabolomic profile of human osteoporotic cancellous bone, highlighting a network of metabolic disturbances that underlie dysregulated bone remodeling. These findings identify amino acid, purine, and phospholipid pathways as potential mechanistic drivers and therapeutic targets in osteoporosis. Metabolites with strong statistical significance warrant further validation and translational investigation.