Biomarkers for osteoarthritis: Current position and steps towards further validation.
ABSTRACT Historically disease knowledge development and treatment innovation in osteoarthritis (OA) has been considered to be slow. One of the many reasons purported as responsible for this slow pace has been the alleged lack of valid and responsive biomarkers to ascertain efficacy, which itself has been dependent upon the slow evolution of the understanding of the complex nature of joint tissue biology. This narrative review outlines the rationale for why we need OA biomarkers with regard to biomarker validation and qualification. The main biomarkers in current development for OA are biochemical and imaging markers. We describe an approach to biomarker validation and qualification for OA clinical trials that has recently commenced with the Foundation of NIH OA Biomarkers Consortium study cosponsored by the Osteoarthritis Research Society International (OARSI). With this approach we endeavor to identify, develop, and qualify biological markers (biomarkers) to support new drug development, preventive medicine, and medical diagnostics for osteoarthritis.
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ABSTRACT: Objective: The present study aimed to link pain mechanisms (sensitization) and biochemical markers for cartilage, bone, and inflammation in patients with knee pain.Methods: 281 participants with different degrees of knee pain intensity and radiological findings (Kellgren & Lawrence (KL)) were included. Structurally related serological biomarkers were measured from serum: high sensitive (hs) CRP (C-reactive protein), CRPM (MMP-mediated [matrix metalloproteinase] breakdown of CRP), C1M, C2M, and C3M (MMP-mediated collagen Type I, II, and III degradation). Pressure pain thresholds (PPT) (peripheral and spreading sensitization), temporal summation (TS) of pain, and conditioning pain modulation (CPM) (both representing generalized sensitization) were assessed. For each pain parameter participants were categorized as most- or least-sensitized.Results: Correlations were found between the pain biomarkers (PPT, TS, CPM) and maximal pain intensity during the last 24 hours. Significant associations were found between most of the serologic biomarkers. High CRPM was associated with centralized sensitization (TS and CPM). None of the serologic markers correlated with knee pain intensity or duration. Only hsCRP correlated with KL. More females were present in the most-sensitized group and more males in the least-sensitized group.Conclusion: A platform of mechanistic pain bio-markers in combination with structure related serological biomarkers provides new possibilities of understanding how OA related structural features may be associated with pain and pain sensitization. The study showed significant correlations between central pain sensitization and MMP-dependent degradation of CRP as a possible measure for chronic inflammation. Future pain association studies should include biomarkers representing more specifically the local joint environment. © 2014 American College of Rheumatology.08/2014; DOI:10.1002/art.38856
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ABSTRACT: Biochemical and pain biomarkers can be applied to patients with painful osteoarthritis profiles and may provide more details compared with conventional clinical tools. The aim of this study was to identify an optimal combination of biochemical and pain biomarkers for classification of patients with different degrees of knee pain and joint damage. Such profiling may provide new diagnostic and therapeutic options. A total of 216 patients with different degrees of knee pain (maximal pain during the last 24 hours rated on a visual analog scale [VAS]) (VAS 0-100) and 64 controls (VAS 0-9) were recruited. Patients were separated into 3 groups: VAS 10 to 39 (N = 81), VAS 40 to 69 (N = 70), and VAS 70 to 100 (N = 65). Pressure pain thresholds, temporal summation to pressure stimuli, and conditioning pain modulation were measured from the peripatellar and extrasegmental sites. Biochemical markers indicative for autoinflammation and immunity (VICM, CRP, and CRPM), synovial inflammation (CIIIM), cartilage loss (CIIM), and bone degradation (CIM) were analyzed. WOMAC, Lequesne, and pain catastrophizing scores were collected. Principal component analysis was applied to select the optimal variable subset, and cluster analysis was applied to this subset to create distinctly different knee pain profiles. Four distinct knee pain profiles were identified: profile A (N = 27), profile B (N = 59), profile C (N = 85), and profile D (N = 41). Each knee pain profile had a unique combination of biochemical markers, pain biomarkers, physical impairments, and psychological factors that may provide the basis for mechanism-based diagnosis, individualized treatment, and selection of patients for clinical trials evaluating analgesic compounds. These results introduce a new profiling for knee OA and should be regarded as preliminary.Pain 01/2015; 156(1):96-107. DOI:10.1016/j.pain.0000000000000011 · 5.64 Impact Factor