Serum-based soluble markers differentiate psoriatic arthritis from osteoarthritis. Issue 6 (25th June 2019)

• Record Type: Journal Article
• Authors: Chandran, Vinod; Abji, Fatima; Perruccio, Anthony V; Gandhi, Rajiv; Li, Suzanne; Cook, Richard J; Gladman, Dafna D
• Is Part Of: Annals of the rheumatic diseases. Volume 78:Issue 6(2019)
• Page Start: 796
• Publication Date: 2019-06-25
• Subjects: biomarkers -- psoriatic arthritis -- osteoarthritis; Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2018-214737
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Objectives: We aimed to identify soluble biomarkers that differentiate psoriatic arthritis (PsA) from osteoarthritis (OA). Methods: Markers of cartilage metabolism (cartilage oligomeric matrix protein [COMP], hyaluronan), metabolic syndrome (adiponectin, adipsin, resistin, hepatocyte growth factor [HGF], insulin, leptin) and inflammation (C-reactive protein [CRP], interleukin-1β [IL-1β], IL-6, IL-8, tumour necrosis factor alpha [TNFα], monocyte chemoattractant protein-1 [MCP-1], nerve growth factor [NGF]) were compared in serum samples from 201 patients with OA, 77 patients with PsA and 76 controls. Levels across the groups were compared using the Kruskal-Wallis test. Pairwise comparisons were made with Wilcoxon rank-sum test. Multivariate logistic regression analyses were performed to identify markers that differentiate PsA from OA. Receiver operating characteristic (ROC) curves were constructed based on multivariate models. The final model was further validated in an independent set of 73 PsA and 75 OA samples using predicted probabilities calculated with coefficients of age, sex and biomarkers. Results: Levels of the following markers were significantly different across the three groups (p<0.001)—COMP, hyaluronan, resistin, HGF, insulin, leptin, CRP, IL-6, IL-8, TNFα, MCP-1, NGF. In multivariate analysis, COMP (OR 1.24, 95% CI 1.06 to 1.46), resistin (OR 1.26, 95% CI 1.07 to 1.48), MCP-1 (OR 1.10, 95% CI 0.07 to 1.48) and NGF (OR<0.001, 95% CI <0.001 to 0.25) were found to be independently associated with PsA versus OA. The area under the ROC curve (AUROC) for this model was 0.99 compared with model with only age and sex (AUROC 0.87, p<0.001). Similar results were obtained using the validation sample. Conclusion: A panel of four biomarkers may distinguish PsA from OA. These results need further validation in prospective studies.