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Article . 2011 . Peer-reviewed
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Article . 2011
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Biomarker Development for Musculoskeletal Diseases

Authors: Wan Huang; Gwendolyn Sowa;

Biomarker Development for Musculoskeletal Diseases

Abstract

AbstractMore than one in 4 Americans has a musculoskeletal (MSK) disorder that requires medical diagnosis and treatment. Imaging tools are able to demonstrate structural changes but cannot reflect the disease activity or symptom severity of MSK conditions. This is of paramount concern in the aging population, in which imaging findings have poor correlation with symptoms, and multiple pain generators frequently coexist. Because levels of inflammatory and matrix breakdown products address disease activity, evaluation of biomarkers has the potential to provide assessment of active pain generators above and beyond the changes observable on imaging studies. This fact has stimulated research interest in the search for novel biomarkers of disease activity and response to treatment in body fluids. The goal is to develop panels of multi‐biomarkers, which could be used independently or in conjunction with the imaging tools, for the diagnosis, prognosis, and treatment validation in MSK diseases. The current review of MSK biomarkers is organized into 3 mechanistic categories: the metabolites of extracellular matrix of MSK tissues; inflammatory cytokines and chemokines; and pain‐related neuropeptides and/or chemicals. Although some representative biomarkers could be used alone, the fact that MSK diseases are multi‐tissue disorders that involve the muscles, bones, cartilage, and nerves suggests that panels of biomarkers may have greater potential than any single biomarker used in isolation. As advances in biotechnology make this a reality, multi‐biomarker panels that include all 3 categories of biomarkers, used either alone or in combination with imaging tools, has the potential to revolutionize the clinical approach to MSK diseases.

Related Organizations
Keywords

Humans, Musculoskeletal Diseases, Prognosis, Biomarkers

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Average
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