To integrate Raman-derived compositional information with microarchitectural, local mechanical, and single-cell transcriptomic data to identify a conserved compositional fingerprint of osteoporotic trabecular bone, highlighting its significance for osteoporosis evaluation.
Key Findings:
A conserved osteoporotic Raman fingerprint was identified, characterized by reduced phosphate and collagen signals and increased lipid-associated bands, with implications for treatment strategies.
These compositional signatures correlated with micro-CT-defined structural deterioration and local mechanical alterations, emphasizing their relevance in clinical settings.
Single-cell RNA sequencing revealed shifts in BMMSC transcriptomic programs related to mineral, extracellular matrix, and lipid metabolism, paralleling the Raman-defined changes.
Interpretation:
Raman-based compositional fingerprinting provides a multidimensional readout that can be integrated with structural imaging, mechanical testing, and transcriptomic profiling, with potential clinical applications.
Limitations:
The study was conducted in murine models, which may not fully replicate human osteoporosis; further validation in larger and more diverse human populations is needed.
Conclusion:
Raman spectroscopy offers a data-rich modality for advanced bone-quality evaluation and diagnostic development, underscoring its importance in future osteoporosis research.
