For many years, musculoskeletal degeneration was seen mostly as a mechanical problem. Cartilage wears out, discs herniate, and joints fail under stress. As a result, treatment has usually focused on repairing or replacing damaged parts once they appear on scans. But this approach is no longer enough.
New research shows that musculoskeletal degeneration is not just caused by wear and tear. It is also driven by biological changes, like shifts in molecular signals, genetics, and the cellular environment, often starting years before any visible damage.
Is musculoskeletal degeneration truly a molecular disease?
Recent studies in genomics, transcriptomics, and metabolomics suggest that joint and spine degeneration starts with disrupted signaling pathways long before changes appear on scans.
Inflammatory pathways contribute to the progression of osteoarthritis, driving cartilage breakdown and ongoing inflammation. Other pathways, such as Wnt and beta-catenin, help regulate tissue repair and balance, but when disrupted, they can accelerate degeneration.
Cellular aging, or senescence, also plays a key role. As we age, senescent cells accumulate and release substances that trigger inflammation and weaken tissues. This process is called the senescence-associated secretory phenotype, or SASP.
These changes at the molecular level can start years before any symptoms or scan results show a problem. By the time damage is visible, the underlying biology has often been getting worse for a long time.
Why do similar injuries lead to different outcomes?
Doctors often see that two people with similar injuries can heal in very different ways. Genetics may help explain why.
Prospective studies have identified single-nucleotide polymorphisms, or SNPs, in genes involved in tissue repair and extracellular matrix functions that influence healing ability. Variants in genes such as TGFB1, COL1A1, MMP3, and VEGFA are associated with differences in ligament strength, collagen structure, and tissue remodeling.
These findings suggest that a person’s genes affect how well they heal and how they respond to treatment. In short, biology may decide if someone recovers or develops long-term problems. This variation challenges the idea that one approach works for everyone. It raises important questions about how we assess risk and choose treatments.
How does aging impact the regenerative environment?
Another key factor is the age of the bone marrow, since it is vital for tissue repair.
Mesenchymal stem cells, which support healing, decline sharply with age. Studies show that both the number and function of these cells drop over time, while fat cells in the marrow increase.
These changes shift the local environment from one that supports healing to one that causes inflammation. This means a patient’s tissue health may not match their actual age.
For doctors using treatments such as platelet-rich plasma or bone marrow concentrate, this highlights an important point. Success may depend not just on the method, but also on the health of the tissue being used.
Can we intervene before degeneration turns structural?
Using multi-omics data together gives us a chance to address disease earlier in its course.
By combining genetic information with metabolic and inflammatory markers, doctors may identify patients at risk of degeneration before major symptoms appear.
For example, problems with metabolism and body-wide inflammation are linked to worsening osteoarthritis. This suggests that improving metabolic health could help protect joints.
This approach shifts the focus from treating problems after they appear to acting early before symptoms start. Rather than waiting for signs like joint narrowing or disc collapse, doctors could step in sooner with targeted treatments such as metabolic interventions, exercise programs, or biologic therapies.
While this model is still developing, it aligns with the broader move toward precision medicine, where early risk assessments and interventions are becoming increasingly important in managing disease.
Is it time to rethink our use of orthobiologics?
As orthobiologic therapies become more popular, they bring both new opportunities and new challenges.
Right now, doctors often use set protocols, giving similar treatments to different patients. But new research shows that how people respond to biologic therapies can depend on their genes, metabolism, and tissue health.
Researchers have found over 100 genetic variants that may affect tissue repair and inflammation. This means that carefully choosing and preparing patients could make a big difference in treatment outcomes.
In fields like cancer care, doctors already use genetic data to guide treatment. Musculoskeletal care could do the same by combining genetic screening with metabolic and inflammatory assessments before starting biologic therapy.
While this idea is still new, it highlights the need to move away from one-size-fits-all treatments and toward more personalized care.
What are the implications for clinical practice?
Moving toward a multi-omics approach does not replace traditional scans or biomechanics. Instead, it adds to their understanding by offering a deeper look at the biology underlying degeneration.
For doctors, this may mean looking beyond scans and symptoms to include molecular and body-wide factors. For patients, it could mean finding risks earlier and getting more personalized prevention and treatment.
There are still key questions, such as how to standardize multi-omics data, integrate it into daily medical practice, and measure its effects on patient outcomes.
Still, the path forward is becoming clearer. Musculoskeletal degeneration is not just a mechanical problem; it is a complex process shaped by genetics, aging cells, and overall health.
Recognizing this complexity may be the first step toward better, longer-lasting care.
References
Ambrosi, T., Marecic, O., McArdle, A., et al. (2021). Aged skeletal stem cells generate an inflammatory degenerative niche. Nature, 597, 256–262. https://doi.org/10.1038/s41586-021-03795-7
Brazier, J., Antrobus, M., Callus, P., et al. (2025). Variants within the MMP3 and COL5A1 genes associate with soft tissue injury history in elite male rugby athletes. Journal of Science and Medicine in Sport. https://doi.org/10.1016/j.jsams.2025.05.007
Çelebier, M. (2025). From metabolomics to theragnostic: Advancing personalized care in musculoskeletal disorders. Orthopaedic Proceedings. https://doi.org/10.1302/1358-992x.2025.9.067
Deng, M., Tang, C., Yin, L., et al. (2025). Clinical and omics biomarkers in osteoarthritis diagnosis and treatment. Journal of Orthopaedic Translation, 50, 295–305. https://doi.org/10.1016/j.jot.2024.12.007
Fukuyama, Y., Murakami, H., & Iemitsu, M. (2024). Single nucleotide polymorphisms and tendon/ligament injuries in athletes: A systematic review and meta-analysis. International Journal of Sports Medicine. https://doi.org/10.1055/a-2419-4359
Ganguly, P., El-Jawhari, J., Giannoudis, P., et al. (2017). Age-related changes in bone marrow mesenchymal stromal cells. Cell Transplantation, 26, 1520–1529. https://doi.org/10.1177/0963689717721201
Gu, Y., Jin, Q., Hu, J., et al. (2023). Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: A two-sample Mendelian randomization study. Journal of Translational Medicine, 21. https://doi.org/10.1186/s12967-023-04165-9
Han, Z., Wang, K., Ding, S., & Zhang, M. (2024). Cross-talk of inflammation and cellular senescence: A new insight into the occurrence and progression of osteoarthritis. Bone Research, 12. https://doi.org/10.1038/s41413-024-00375-z
Hasebe, M., Su, C., Kiel, D., & Yoshiji, S. (2025). Leveraging proteomics and proteogenomics for understanding osteoporosis and other musculoskeletal diseases. Current Osteoporosis Reports, 23. https://doi.org/10.1007/s11914-025-00941-2
Juginović, A., Kekić, A., Aranza, I., et al. (2025). Next-generation approaches in sports medicine: The role of genetics, omics, and digital health in optimizing athlete performance and longevity. Life, 15. https://doi.org/10.3390/life15071023
Kumar, R., Sporn, K., Prabhakar, V., et al. (2025). Computational and imaging approaches for precision characterization of bone, cartilage, and synovial biomolecules. Journal of Personalized Medicine, 15. https://doi.org/10.3390/jpm15070298
Leńska-Duniec, A. (2025). Genetic susceptibility to sport-related muscle injuries: Insights from the literature and novel gene candidates. International Journal of Molecular Sciences, 26. https://doi.org/10.3390/ijms262211175
Lin, H., Sohn, J., Shen, H., Langhans, M., & Tuan, R. (2019). Bone marrow mesenchymal stem cells: Aging and tissue engineering applications to enhance bone healing. Biomaterials, 203, 96–110. https://doi.org/10.1016/j.biomaterials.2018.06.026
Navani, A., Jeyaraman, M., Jeyaraman, N., et al. (2025). Precision medicine in orthobiologics: A paradigm shift in regenerative therapies. Bioengineering, 12. https://doi.org/10.3390/bioengineering12090908
Peng, X., Zhou, X., Yin, Y., et al. (2022). Inflammatory microenvironment accelerates bone marrow mesenchymal stem cell aging. Frontiers in Bioengineering and Biotechnology, 10. https://doi.org/10.3389/fbioe.2022.870324
Welhaven, H., Welfley, A., & June, R. (2024). Osteoarthritis year in review 2024: Molecular biomarkers of osteoarthritis. Osteoarthritis and Cartilage. https://doi.org/10.1016/j.joca.2024.10.003
Yao, Q., Wu, X., Tao, C., et al. (2023). Osteoarthritis: Pathogenic signaling pathways and therapeutic targets. Signal Transduction and Targeted Therapy, 8. https://doi.org/10.1038/s41392-023-01330-w
Zhou, Y., Wang, T., Hamilton, J., & Chen, D. (2017). Wnt/β-catenin signaling in osteoarthritis and in other forms of arthritis. Current Rheumatology Reports, 19, 1–8. https://doi.org/10.1007/s11926-017-0679-z

Trevor Turner, MD
Trevor Turner, MD, is a doctor specializing in regenerative orthopedics and musculoskeletal health. He trained at institutions such as the Andrews Orthopedic & Sports Medicine Institute and focuses on the overlap of sports medicine, biologic therapies, and precision diagnostics. He is the founder of CartiNova, a regenerative medicine platform based in Atlanta.






