Association of a Serum Protein Signature With Rheumatoid Arthritis Development

Abstract

Objective. The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new insights into the pathogenic mechanisms that lead to its development. Methods. In a cohort of first-degree relatives of Indigenous North American RA patients, the SomaScan proteomics platform was used to determine the levels of 1,307 proteins in multiple longitudinal serum samples from 17 individuals who were followed up prospectively to the time of disease onset. Proteomic signatures from this group of individuals (designated the progressor group) were compared to those in a group of individuals who were considered at risk of developing RA, stratified as either positive (n = 63) or negative (n = 47) for anti-citrullinated protein antibodies (ACPAs) (designated the at-risk group). Machine learning was used to identify a protein signature that could accurately classify those individuals at highest risk of future RA development. Results. A preclinical proteomic signature that differentiated RA progressors from at-risk individuals, irrespective of ACPA status, was identified (area under the curve 0.913, accuracy 91.2%). Importantly, the predictive preclinical proteomic signature was present not only in serum samples obtained close to the onset of RA, but also in serum samples obtained a median of 30.9 months prior to onset. Network analysis implicated the activation of Toll-like receptor 2 and production of tumor necrosis factor and interleukin-1 as key events that precede RA progression. Conclusion. Alterations in the serum proteome in the preclinical phase of RA can emerge years prior to the onset of disease. Our findings suggest that the serum proteome provides a rich source of proteins serving both to classify at-risk individuals and to identify molecular pathways involved in the development of clinically detectable RA.

Challenges and Opportunities: Using Omics to Generate Testable Insights Into Pathogenic Mechanisms in Preclinical Seropositive Rheumatoid Arthritis

“…Moreover, studies are seeking to identify the transition mechanisms that then lead, in a subset of individuals, to the initial development and propagation of arthritis. This research area is greatly facilitated by study findings such as those reported by O’Neil and colleagues (7), especially those pointing to a TLR‐2–mediated pathway as a novel therapeutic target, as well as other investigations yet to come.…”

“…These are also questions of increasing relevance across the field of autoimmune disease research, as many other such diseases, including type 1 diabetes and systemic lupus erythematosus, clearly evolve through the same type of autoantibody‐positive preclinical period and exhibit similar forms of immune dysregulation during that time (5), including involvement of autoantibodies that can also cross these disease boundaries throughout the disease course (6). In this issue of Arthritis & Rheumatology , O’Neil and colleagues (7) add important information to our understanding of these concepts in the preclinical RA period.…”

“…Starting with investigations of Pima Indians in the United States (11), studies of uniquely informative populations with a high risk of developing RA have been undertaken to understand the preclinical evolution of RA. The advantages of using Indigenous North American populations, as in the study by O’Neil et al (7), are many (for review, see ref. 12).…”

Contribution of Multiplex Immunoassays to Rheumatoid Arthritis Management: From Biomarker Discovery to Personalized Medicine

“…Some studies have shown that the levels of signalling molecules and markers of bone metabolism circulating in the blood of RA patients could be additional markers used in assessing the degree of activity in RA [ 98 , 99 ]. Recently, O’Neil et al showed that the serum proteome provides a source of proteins that serves both to identify the molecular pathways involved in the development of RA and to classify at-risk individuals [ 100 ]. The multiple biomarker approach could utilize a variety of new potential biomarkers and could be used for the early diagnosis of seronegative RA patients, the measurement of disease activity and as a prognostic tool during treatment therapy.…”

Proteomic Approaches to Defining Remission and the Risk of Relapse in Rheumatoid Arthritis

“…Although mass spectrometry tends to dominate this evolving field, broad-based targeted proteomics has its own advantages, including simplified sample preparation and user-friendly output data ( 12 ). Our group has previously defined protein sets that are associated with future disease flare from pre-clinical RA by coupling machine learning with proteomic approaches ( 13 ). Indeed, leveraging omics approaches to resolve heterogeneity in common diseases remains a distinct challenge in clinical medicine ( 14 ), though this has not been systematically undertaken in a stable RA cohort.…”