Background Biomarkers can help identify patients that are more likely to respond favorably to a given therapy (a Predictive or patient stratification biomarker). Biomarkers can also be used to provide objective proof of a biological response to a drug (Efficacy of Intervention biomarker).
Objectives The overall goal of this project was to identify protein biomarkers that predict likelihood of response to glucosamine hydrochloride and chondroitin sulfate (GH+CS), both predictive and efficacy of intervention biomarkers. We hypothesized that a subset of peptides in a mass spectrometry panel, developed to predict Osteoarthritis (OA) progression, would identify responders to GH+CS, knowing that CS is an NFkB activity and inflammation inhibitor.
Methods This study analyzed a subset of 80 baseline serum samples from the MOVES (Multicentric Osteoarthritis Intervention Study with SYSADOA) trial1. The MOVES trial was an international multicentric, phase IV, double-blind, non-inferiority, randomized trial to compare the efficacy and safety of the combination of glucosamine hydrochloride (GH 1.500mg/day) and chondroitin sulfate (CS 1.200mg/day) known as Droglican® (Bioiberica), versus celecoxib Celebrex (200mg/day) in patients with Kellgren Lawrence grades 2–3 knee OA with severe pain. The sample selected for this study consisted of half drug responders and half non-responders by OARSI-OMERACT criteria. A total of 25 peptides from 23 proteins were analyzed by mass spectrometry. This panel was based on results of discovery proteomic studies in synovial fluid (n=23), urine (n=45) and serum (n=40) from knee OA subjects to identify biomarkers indicative of an OA diagnosis and OA progression.
Quantitative LC/MRM was performed on a 1 μg of protein digest spiked with 10 fmol of 25 stable isotope labeled peptides using a nanoAcquity UPLC system (Waters Corp) coupled to a Waters Xevo TQ-S triple quadrupole mass spectrometer via a nanoelectrospray ionization source. Technical variability (based on spiked in yeast alcohol dehydrogenase was 10.4%). Logistic regression was used to evaluate the association of demographics (age, gender and BMI) and the biomarkers with drug response (yes/no) after 180 days of treatment. P values <0.05 were considered significant.
Results The sample was 90% female, mean age 64 (SD 7) years, 55% with BMI >30 kg/m2. Higher age (p=0.004) but neither gender, nor KL grade were associated with likelihood of drug response. Age plus the marker panel significantly predicted drug response (overall model p=0.0007). In the multivariable logistic regression, adjusted for age, a total of 12 peptides, corresponding to 11 proteins, were significantly independently associated with drug response (p<0.0001 by Effect likelihood Ratio tests).
Conclusions These biomarkers in theory could be used to stratify different patient groups in terms of likelihood of clinical response to GH+CS in efforts to develop personalized treatment algorithms for OA patients.
Hochberg et al. ARD 2015.
Disclosure of Interest None declared
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