A Review and Meta-Analysis of Biomarkers in Early-Stage Osteoarthritis

Abstract

Osteoarthritis (OA) is a common musculoskeletal disorder impacting millions in the United States, presenting with joint pain, stiffness, and reduced mobility. Its complex origins and lack of clear early-stage symptoms make early detection challenging. Traditional diagnostic methods, including imaging, are often used when significant cartilage loss has already occurred. However, serum biomarkers offer potential for earlier and less invasive detection. For our review, articles published from 1980 to 2024 that analyzed OA serum biomarkers were retrieved from PubMed, Embase, and Web of Science. The analysis included biomarker frequency, percent changes from baseline levels, and logistic regression to assess correlations with OA. Several biomarkers exhibited altered levels in OA, classified into inflammatory, collagenous, mechanical stress, and other categories. Inflammatory markers such as IL-6 and MPO showed significant elevation, while TNF-α showed minimal correlation with OA. Collagenous markers, especially COMP, were consistently elevated in patients, correlating with disease severity. Additionally, PIIANP showed a strong negative correlation with OA progression. Obesity-related markers, including resistin, were also associated with OA, and logistic regression confirmed IL-6, COMP, and resistin as strongly correlated with OA, with PIIANP demonstrating a significant inverse relationship. This review highlights the critical role of serum biomarkers in OA detection and progression. Markers like IL-6, COMP, and PIIANP offer significant potential for early diagnosis. Integrating these biomarkers into clinical practice may facilitate earlier intervention, potentially slowing OA progression. Future research should focus on validating these findings across larger, diverse populations and refining therapeutic strategies targeting these biomarker pathways.

Keywords

biomarkers / detection / early-stage / osteoarthritis / serum

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