Abstract
BACKGROUND We sought to identify immunoglobin G autoantibodies predictive of early treatment response to methotrexate, the recommended first-line therapy for patients with newly diagnosed rheumatoid arthritis, and to the interleukin-6 receptor inhibitor biologic tocilizumab, initiated as the first disease-modifying anti-rheumatic drug. MATERIALS AND METHODS In baseline sera of a subset of patients with newly diagnosed rheumatoid arthritis in the U-Act-Early study, selected based on specific responder/non-responder criteria using the Disease Activity Score assessing 28 joints (DAS28) within the first 20 weeks, we measured immunoglobin G antibody reactivity against 463 protein antigens and performed supervised cluster analysis to identify predictive autoantibodies for treatment response. The analysis subset comprised 56 patients in the methotrexate arm (22 responders, 34 non-responders) and 50 patients in the tocilizumab arm (34 responders, 16 non-responders). For comparison, these analyses were also performed in 50 age- and gender-matched healthy controls. RESULTS Increased reactivity in responders versus non-responders was found in the methotrexate arm against two antigens-DOT1-like histone lysine methyltransferase (p = 0.009) and tropomyosin (p = 0.003)-and in the tocilizumab arm against one antigen-neuro-oncological ventral antigen 2 (p = 0.039). Decreased reactivity was detected against two antigens in the methotrexate arm-G1 to S phase transition 2 (p = 0.023) and the zinc finger protein ZPR1 (p = 0.021). Reactivity against the identified antigens was not statistically significant in either treatment arm for patients with rheumatoid factor-positive versus-negative or anti-cyclic citrullinated test-positive versus test-negative rheumatoid arthritis (p ≥ 0.06). CONCLUSIONS Comprehensive profiling of baseline sera revealed several novel immunoglobin G autoantibodies associated with early treatment response to methotrexate and to tocilizumab in disease-modifying anti-rheumatic drug-naive patients with rheumatoid arthritis. These findings could eventually yield clinically relevant predictive markers, if corroborated in different patient cohorts, and may facilitate future benefit in personalised healthcare.
