Identification of a Human SOCS1 Polymorphism That Predicts Rheumatoid Arthritis Severity

Abstract

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by an autoimmune response in the joints and an exacerbation of cytokine responses. A minority of patients with RA experience spontaneous remission, but most will show moderate/high disease activity, with aggressive joint damage and multiple systemic manifestations. There is thus is a great need to identify prognostic biomarkers for disease risk to improve diagnosis and prognosis, and to inform on the most appropriate therapy. Here we focused on suppressor of cytokine signaling 1 (SOCS1), a physiological negative regulator of cytokines that modulates cell activation. Using four independent cohorts of patients with arthritis, we characterized the correlation between SOCS1 mRNA levels and clinical outcome. We found a significant inverse correlation between SOCS1 mRNA expression and disease activity throughout the follow-up of patients with RA. Lower baseline SOCS1 levels were associated with poorer disease control in response to methotrexate and other conventional synthetic disease-modifying anti-rheumatic drugs in early arthritis, and to rituximab in established (active) RA. Moreover, we identified several single nucleotide polymorphisms in the SOCS1 gene that correlated with SOCS1 mRNA expression, and that might identify those patients with early arthritis that fulfill RA classification criteria. One of them, rs4780355, is in linkage disequilibrium with a microsatellite (TTTTC)_3-5, mapped 0.9 kb downstream of the SNP, and correlated with reduced SOCS1 expression in vitro. Overall, our data support the association between SOCS1 expression and disease progression, disease severity and response to treatment in RA. These observations underlie the relevance of SOCS1 mRNA levels for stratifying patients prognostically and guiding therapeutic decisions.

Keywords: biomarkers; cytokines; disease activity; inflammation; rheumatoid arthritis.