AB1248 MOLECULAR MARKERS OF PAIN AND OTHER SYMPTOMS IN KNEE OSTEOARTHRITIS
Authors: Y. Liem, A. Judge, K. Ourradi, Y. Li, M. Sharif
Journal: Annals of the Rheumatic Diseases (2020)

Background: Osteoarthritis (OA) is one of the leading causes for disability in adults. The diagnosis of OA is generally based on patient reported pain, other symptoms and radiographic changes which occur in late stages. There have been extensive research over the last 30 years to identify and validate molecular markers for early diagnosis of OA and a large range of potential biomarkers has been identified[1, 2]. However, most of these biomarkers are markers of structural and metabolic changes, and have poor correlation with pain and stiffness in knee OA. The publicly available data from the National Institute of Health Osteoarthritis Initiative (OAI) provides an opportunity to search for clinically useful biomarkers associated with the main symptoms in OA. Objectives: To identify molecular biomarkers which are associated with the main symptoms of knee OA. Methods: 600 participants from 4791 men and women aged 45 to 79 who were Kellgren &amp; Lawrence grade 1 or more were identified with biochemical markers data, radiographic and clinical features of OA. Nineteen biochemical markers measured in serum and/or urine were analysed for their association with primary clinical features of OA: Knee injury and Osteoarthritis Outcome Score (KOOS) pain and symptoms, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and stiffness score. Patient level analysis was carried out based on the worst affected knee. The association of molecular biomarkers with KOOS and WOMAC scores were assessed using univariate and multivariate linear and logistic regression, and receiving operator characteristic curves (ROC). Area under the curve (AUC) was calculated in order to determine if a combination of the biomarkers improve the associations with the outcome variables. Results: Only 3 of the 19 biomarkers investigated were associated with clinical symptoms. Serum cartilage oligomeric matrix protein (COMP) and chondroitin sulphate 846 (CS846) were associated with WOMAC pain and stiffness respectively, while, urinary C-terminal crosslinked telopeptide of type II collagen (CTXII) appeared to be highly associated with WOMAC stiffness, KOOS pain and symptoms (Table 1 / 2). The AUC from the univariate model for the association of biomarkers with WOMAC pain and stiffness were 0.5 (Table 1), while the AUC for unadjusted and adjusted multivariate model for the 3 biomarkers combined were 0.56 and 0.67 respectively (Figure 1). Table 1. Univariate logistic regression model. WOMAC Pain WOMAC Stiffness Biomarkers OR (95%) AUC (p-value) OR (95%) AUC (p-value) sCS846 1.0026 (0.9996, 1.0056) 0.5200 (0.088) 1.0047 (1.0013, 1.0081) 0.5399 (0.007) sCOMP 0.9419 (0.8912, 0.9954) 0.5462 (0.034) 1.0424 (0.9843, 1.1039) 0.5317 (0.156) uCTXII 1.0077 (0.9990, 1.0165) 0.5300 (0.083) 1.0099 (1.0005, 1.0194) 0.5489 (0.039) Conclusion: Serum COMP and urinary CTXII are associated with pain in knee OA, while serum CS846 and urinary CTXII are associated with joint stiffness. The multivariate logistic regression model shows good discrimination for the association of biomarkers with clinical symptoms of OA. The data from the multivariate model suggests that a clinically useful biomarker may be created using AUC values for better specificity and sensitivity. References: [1]Lotz, M., et al. Annals of the Rheumatic Diseases, 2013. 72(11) [2]Kraus, V.B., et al. Annals of the Rheumatic Diseases, 2017. 76(1) Table 2. Univariate and multivariate linear regression model. Confounders such as age, body mass index, gender and race were adjusted in the multivariate model. Biomarkers KOOS Pain KOOS Symptoms Univariate Multivariate Univariate Multivariate Coefficient (95%) p-value Coefficient (95%) p-value Coefficient (95%) p-value Coefficient (95%) p-value sMMP3 0.057 (-0.024, 0.138) 0.165 0.019 (-0.074, 0.111) 0.696 0.092 (0.022, 0.162) 0.010 0.059 (-0.021, 0.140) 0.147 uCTXII -0.678 (-0.124, -0.012) 0.017 -0.086 (-0.152, -0.021) 0.010 -0.730 (-0.121, -0.025) 0.003 -0.091 (-0.148, -0.034) 0.002 Acknowledgments Disclosure of Interests: None declared