ReviewBiomarkers of cartilage turnover. Part 1: Markers of collagen degradation and synthesis
Introduction
Osteoarthritis (OA) is a common, debilitating joint disease that affects all mammals including the horse, dog and man (Poole, 1996). Degradation of articular cartilage in the affected joint is a major feature of the disease (Evans et al., 1982, Spiers et al., 1994) and OA can be defined as a process of aberrant repair with gradual and progressive loss of articular cartilage through degradative mechanisms. Progressive deterioration of the articular cartilage leads to loss of function and, ultimately, to failure of the joint.
The dry-weight of cartilage is predominantly composed of collagen (Eyre, 2004) and the remainder is proteoglycan and glycoprotein (Todhunter, 1996). Since adult cartilage contains neither a vascular nor a neural supply, chondrocytes metabolise largely anaerobically, obtaining their nutrition via the synovial fluid (SF), by means of diffusion. Since type II collagen is specific for hyaline cartilage and is in high abundance in this tissue, the major biomarkers of collagen turnover in cartilage are epitopes derived from type II collagen.
Over the past three decades, one focus of OA research has been the study of candidate molecular biomarkers for the early detection of OA, as well as for monitoring disease or prediction of progression. The ability to detect cartilage loss is highly desirable, not only from a diagnostic, prognostic and therapeutic perspective, but also as surrogate outcome measures in trials of candidate structure-modifying agents (Felson and Lohmander, 2009). The current imaging modalities of radiography, arthroscopy and magnetic resonance imaging (MRI) are costly, require general anaesthesia in some instances, and typically yield results only when gross damage to the cartilage has already occurred. The aim of biomarker research is to reduce or alleviate these disadvantages.
Cartilage destruction leads to an accumulation of breakdown products in the SF. These are released into the circulation and ultimately filtered and excreted, or broken down in vivo. Analysis of body fluids (such as plasma, serum, urine or SF) can provide information regarding the health, or turnover of the cartilage prior to the development of gross pathology, or can highlight any metabolic changes attributable to the treatment being studied.
The perfect biomarker would be specific to the diseased tissue and pathology, sensitive to changes in disease progression or therapeutic intervention, and predictive of disease outcome. Although the discovery of a single ‘golden marker’ of OA is unlikely, the search continues for a marker which is both sensitive to cartilage damage, and specific to the damaged joint. If such a screening tool was available, it would be of enormous value in early diagnosis. It is unlikely that a single biomarker will ever meet all the necessary criteria for the complex diagnosis and observation of OA, and that a profile of several markers will emerge as a more accurate and discriminatory watermark.
When considering the measurement of biomarkers in serum or urine, it is important to remember that the greatest proportion of cartilage in the body is located in the spine and respiratory system, and that contribution from a single diseased joint may be relatively small. In addition, experimental induction of joint instability, performed with the aim of inducing experimental OA (for example, transection of the cranial cruciate ligament) often stimulates degeneration of soft tissues associated with those joints which may result in the release of significant quantities of biomarker. As a result, the epitope of interest could have originated from sources other than the specific cartilage of interest. Biomarkers may therefore be considered ‘non-specific’ not only to the cartilage itself, but to OA, as other diseases of articular cartilage may also result in alterations in their concentrations. Additionally, conflicting conclusions have sometimes been drawn when comparing studies of naturally-occurring with experimentally-induced OA.
Elevated clearance, prior loss of cartilage, or dilution of the biomarker (particularly in the case of joint effusion), may all render inaccurate the absolute concentration of SF concentrations of a biomarker (Lohmander et al., 1994). Synovial inflammation, which often accompanies joint disease, may partly explain differences in measurements from blood and SF from the same patient (Meyers et al., 1995). Expressing a biomarker concentration as a ratio to another marker (Saxna and Heinegard, 1992) may avoid this problem.
Further criticisms levelled at studies measuring serum or SF biomarker concentrations include reports that since the concentration of several biomarkers have been shown to increase with exercise, the activity level of a subject may influence an association (Roos et al., 1995, Neidhart et al., 2000, Mündermann et al., 2005, Frisbie et al., 2008), and that some species differences are apparent when considering the value of different biomarkers as a diagnostic or prognostic indicator of disease (Sharif et al., 1995, Petersson et al., 1998). Furthermore, the highly concentrated samples may require dilution to fit with the standard curve of an assay, increasing the potential for error.
Another, as yet unresolved issue, concerns that of epitope stability, since further enzymatic cleavage of biomarker fragments may occur following release into the circulation. In addition, the rate of degradation of cartilage and progression of subsequent OA is considerably faster in an experimental model than occurs in natural disease, leading to earlier production of peak levels, which may also be of higher concentration. Whilst a more rapid disease progression is essential for laboratory study, it may explain discrepancies between associations arising from experimental studies, and studies concerning the same biomarkers in populations with natural disease. This area deserves further study.
A variety of methods used to quantify collagen destruction and repair from cartilage have been developed. However, while these methods provide important information about disease mechanisms in OA, they have left many questions unanswered. For a biomarker to be appropriate for use as a measure of the joint’s response to the test treatment, it ‘must reliably predict the overall effect on the clinical outcome’ (Fleming and DeMets, 1996); a standard which many biomarkers have failed to meet. OA is a complex process and numerous interdependent factors can affect the clinical outcome; the requirement for a biomarker to correlate with the clinical outcome, but also capture the net effect of treatment, has proved challenging (Felson and Lohmander, 2009).
In this first part of a two-part review we focus on the current status of collagen biomarkers. The second article considers the non-collagenous biomarkers of cartilage matrix turnover (Garvican et al., 2010).
Section snippets
Production of type II collagen
Type II collagen is synthesised as a pre-propeptide with C- and N-terminal globular domains (Fig. 1). Final aggregation of procollagens and formation of collagen fibrils requires the removal of these domains to give tropocollagen. This cleavage (by the extracellular proteinases C- and N-proteinase) ensures that intracellular helix formation cannot occur. The C- and N-terminal propeptides are present in the highest proportion in fetal cartilage, are rapidly reduced at birth, and are present only
Breakdown of type II collagen
It is thought that the structural design of mature collagen aids its longevity and provides an inherent degree of protection from proteolysis, because enzymatic cleavage sites in and between molecules are limited. Breakdown and turnover of cartilage collagen is largely mediated by a family of degradative enzymes called matrix metalloproteinases (MMPs), named for the metal ion (generally zinc) present at the active site (Fig. 2). Collagenolysis must (for reasons of functional continuation) be
Conclusions
The processes which result in the catabolism of collagen, the subsequent synthesis in an attempt to maintain tissue integrity, and the ensuing detectable metabolites, are numerous and complex and, as yet, not fully understood. Measurement of a combination of biomarkers, often including more than one marker for degradation or synthesis, often provides complementary information, not necessarily a redundant replication of data. In addition, further methods for the quantification of these processes
Conflict of interest statement
None of the authors of this paper has a financial or personal relationship with other people or organisations that could inappropriately influence or bias the content of the paper.
Acknowledgements
Elaine Garvican was funded by a Pfizer Global Research studentship. This review is dedicated to the memory of Dr. Anne Vaughan-Thomas, a dear colleague and friend.
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2022, Osteoarthritis and CartilageCitation Excerpt :A significant initial increase in concentration was observed following ACI, returning to baseline by 1 year28. PICP is released during collagen I synthesis53. Type I collagen is involved in OA progression and is a potential marker for osteophyte progression54.
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2022, Osteoarthritis and CartilageCitation Excerpt :One of the hallmarks of OA is cartilage degradation, due to increased catabolism where the proteoglycans and glycosaminoglycans (GAGs) are removed, thereby exposing the underlying collagen fibres for possible irreversible breakdown, mainly by matrix metalloproteinase 13 (MMP-13)6. As cartilage sampling is highly invasive and destructive, biomarkers for assessing in vivo collagen turnover have been used with somewhat unclear results7. Further, the biomarkers target the cleaved-off N-terminal and C-terminal collagen propeptides, and thus, do not reflect collagen incorporation but only synthesis.
Low magnitude high frequency vibration promotes chondrogenic differentiation of bone marrow stem cells with involvement of β-catenin signaling pathway
2020, Archives of Oral BiologyCitation Excerpt :The application of cyclic tensile strain or fluid flow was also reported to significantly stimulate the expression levels of Sox9 in undifferentiated hMSCs (Friedl et al., 2007) and C3H10T1/2 murine MSCs (Arnsdorf, Tummala, Kwon, & Jacobs, 2009). Our studies found that LMHF vibration resulted in an increase in chondrogenic markers Aggrecan (Acan), BMP7, SOX9 and a decrease in the expression of hypertrophic marker X-type Colla (COL10A1), which is accepted as an important regulator for chondrocyte differentiation and maturation (Garvican, Vaughan-Thomas, Innes, & Clegg, 2010; Mueller & Tuan, 2008). During the development of chondrocytes, Sox9 promotes the differentiation of mesenchymal cells into chondrocytes and inhibits the differentiation of chondrocytes into hypertrophic chondrocytes (Nalesso et al., 2011).
Viewpoint on the role of tissue maintenance in ageing: focus on biomarkers of bone, cartilage, muscle, and brain tissue maintenance
2019, Ageing Research ReviewsCitation Excerpt :These markers can be grouped based on the particular process they are associated with or whether they are collagen-derived or not. Most markers of cartilage turnover are based on collagen type 2 metabolism; markers for degradation include C-terminal cross-linked telopeptide of type 2 collagen (CTX-II) and type 2 collagen fragments (C2C), while the predominant markers for formation are the C- and N-terminal propeptide of type 2 procollagen (PIICP and PIINP) (Charni-Ben Tabassi and Garnero, 2007; Garvican et al., 2010b; Woitge and Seibel, 2017). The main non-collagenous marker of cartilage turnover is cartilage oligomeric matrix protein (COMP), a glycoprotein constituent of articular cartilage (Garvican et al., 2010a; Woitge and Seibel, 2017).
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Deceased.