Bioinformatic Screening of Key Regulatory Molecules and Mechanisms in Osteoporosis Based on Tryptophan Metabolism-Related Genes

This bioinformatic study reveals the potential role of tryptophan metabolism in OP pathogenesis and identifies DVL1 and RBM39 as candidate diagnostic biomarkers and therapeutic targets through computational analysis. These findings are inferential based on transcriptomic data mining and require further validation through experimental approaches. Future studies should include functional characterization in cellular and animal models, prospective clinical cohort validation, and mechanistic investigations to confirm the diagnostic and therapeutic value of these candidates. If validated, these findings could provide a molecular foundation for developing non-invasive diagnostic tools and precision medicine approaches in OP management, potentially improving early detection and personalized treatment strategies for patients at risk of osteoporotic fractures.