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Application of Atomic Force Microscopy to Detect Early Osteoarthritis
Published on: May 24, 2020
Applications of proteomics to osteoarthritis, a musculoskeletal disease characterized by aging
1Musculoskeletal Research Group, Division of Veterinary Medicine, School of Veterinary Medicine and Science, University of Nottingham Nottingham, UK.
Abstract:
The incidence of age-related musculoskeletal impairment is steadily rising throughout the world. Musculoskeletal conditions are closely linked with aging and inflammation. They are leading causes of morbidity and disability in man and beast. Aging is a major contributor to musculoskeletal degeneration and the development of osteoarthritis (OA). OA is a degenerative disease that involves structural changes to joint tissues including synovial inflammation, catabolic destruction of articular cartilage and alterations in subchondral bone. Cartilage degradation and structural changes in subchondral bone result in the production of fragments of extracellular matrix molecules. Some of these biochemical markers or "biomarkers" can be detected in blood, serum, synovial fluid, and urine and may be useful markers of disease progression. The ability to detect biomarkers of cartilage degradation in body fluids may enable clinicians to diagnose sub-clinical OA as well as determining the course of disease progression. New biomarkers that indicate early responses of the joint cartilage to degeneration will be useful in detecting early, pre-radiographic changes. Systems biology is increasingly applied in basic cartilage biology and OA research. Proteomic techniques have the potential to improve our understanding of OA physiopathology and its underlying mechanisms. Proteomics can also facilitate the discovery of disease-specific biomarkers and help identify new therapeutic targets. Proteomic studies of cartilage and other joint tissues may be particularly relevant in diagnostic orthopedics and therapeutic research. This perspective article discusses the relevance and potential of proteomics for studying age-related musculoskeletal diseases such as OA and reviews the contributions of key investigators in the field.
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