Gene expression profiling in autoantibody-positive patients with arthralgia predicts development of arthritis

Abstract

Objective: To identify molecular features associated with the development of rheumatoid arthritis (RA), to understand the pathophysiology of preclinical development of RA, and to assign predictive biomarkers.

Methods: The study group comprised 109 anti-citrullinated protein antibody (ACPA)- and/or rheumatoid factor-positive patients with arthralgia who did not have arthritis but were at risk of RA, and 25 patients with RA. The gene expression profiles of blood samples obtained from these patients were determined by DNA microarray analysis and quantitative polymerase chain reaction.

Results: In 20 of the 109 patients with arthralgia who were at risk of RA, arthritis developed after a median of 7 months. Gene expression profiling of blood cells revealed heterogeneity among the at-risk patients, based on differential expression of immune-related genes. This report is the first to describe gene signatures relevant to the development of arthritis. Signatures significantly associated with arthritis development were involved in interferon (IFN)-mediated immunity, hematopoiesis, and chemokine/cytokine activity. Logistic regression analysis revealed that the odds ratio (OR) for developing arthritis within 12 months was 21.0 (95% confidence interval [95% CI] 2.8-156.1 [P = 0.003]) for the subgroup characterized by increased expression of genes involved in IFN-mediated immunity and/or cytokine/chemokine-activity. Genes involved in B cell immunology were associated with protection against progression to arthritis (OR 0.38, 95% CI 0.21-0.70 [P = 0.002]). These processes were reminiscent of those in patients with RA, implying that the preclinical phase of disease is associated with features of established disease.

Conclusion: The results of this study indicate that IFN-mediated immunity, hematopoiesis, and cell trafficking specify processes relevant to the progression of arthritis independent of ACPA positivity. These findings strongly suggest that certain gene signatures have value for predicting the progression to arthritis, which will pave the way to preventive medicine.