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A Pilot Study on Circulating, Cellular, and Tissue Biomarkers in Osteosarcopenic Patients
Francesca Salamanna1, Cesare Faldini2,3, Francesca Veronesi1
1Surgical Sciences and Technologies, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136 Bologna, Italy.
International Journal of Molecular Sciences
|June 19, 2024
Summary
Researchers identified novel biomarkers for osteosarcopenia, a condition of aging involving muscle and bone loss. Elevated basophils and specific protein changes may aid in diagnosing this aging-related disease.
Area of Science:
- Gerontology and Regenerative Medicine
- Biomarker Discovery
- Musculoskeletal Health
Background:
- Aging is characterized by progressive loss of muscle and bone mass, leading to osteosarcopenia.
- Currently, no established biomarkers exist for osteosarcopenia, hindering early diagnosis and intervention.
- Research into circulating, cellular, and tissue biomarkers for this condition is limited.
Purpose of the Study:
- To identify novel circulating, cellular, and tissue biomarkers for osteosarcopenia.
- To investigate the differences in biomarker expression and tissue micro-architecture between osteosarcopenic and healthy individuals.
- To assess the potential of identified biomarkers as diagnostic tools for promoting healthy aging.
Main Methods:
- Analysis of circulating biomarkers including cytokines (e.g., TNFα, IL15), hormones (e.g., DHEA-S), and coagulation factors (e.g., aPPT, PT/INR).
- Assessment of cellular markers, including basophil and neutrophil percentages, and osteoclast precursor activity.
- Examination of bone and muscle tissue micro-architecture and associated biomarker expressions.
- Application of linear discriminant analysis (LDA) to evaluate classification accuracy of biomarker models.
Main Results:
- Osteosarcopenic patients showed elevated basophils and TNFα levels.
- Decreased levels of aPPT, PT/INR, IL15, alpha-Klotho, DHEA-S, and FGF-2 were observed in osteosarcopenic patients.
- Distinctive bone and muscle tissue micro-architecture and biomarker expressions were noted, along with increased osteoclast precursors and spontaneous osteoclastogenesis.
- LDA models achieved classification accuracies ranging from 61-78% based on selected biomarkers.
Conclusions:
- The study provides compelling evidence for novel biomarkers associated with osteosarcopenia.
- These identified biomarkers, including specific cell counts and protein expressions, show potential as diagnostic tools.
- The findings contribute to the understanding of osteosarcopenia pathophysiology and may aid in developing strategies for healthy aging.
