A Serum Protein Signature is associated with Rheumatoid Arthritis development.

OBJECTIVES The pathophysiologic events that precede the onset of Rheumatoid Arthritis (RA) remain incompletely understood. We aimed to identify changes in the serum proteome that precede RA and provide new insights into the pathogenic mechanisms that lead to its development. METHODS We studied a cohort of first-degree relatives (FDR) of Indigenous North American RA patients using the SOMAscan platform and determined the levels of 1307 proteins in multiple longitudinal serum samples from seventeen individuals who were followed prospectively into disease onset. Proteomic signatures from this Progressor group were compared to those of At-risk ACPA positive (n=63) and ACPA negative (n=47) individuals. Machine learning was used to identify a protein signature that accurately classifies individuals at highest risk of future RA development. RESULTS We identified a pre-clinical proteomic signature that differentiates Progressors from At-risk individuals, irrespective of ACPA status (AUC=0.913, accuracy=91.2%). Importantly, the predictive pre-clinical proteomic signature was present not only in samples obtained close to the onset of RA, but also samples obtained a median of 30.9 months prior to onset. Network analysis implicated the activation of toll like receptor 2 (TLR2) and production of TNF and IL1 as key events that precede progression. CONCLUSIONS Alterations in the serum proteome in the pre-clinical phase of RA exist years prior to the onset of disease. Our findings suggest that the serum proteome provides a rich source of proteins that serves both to classify At-risk individuals and to identify molecular pathways involved in the development of clinically detectable RA.