Presenter of 1 Presentation
O061 - NOVEL BIOMARKERS FOR SERONEGATIVE EARLY RHEUMATOID ARTHRITIS (ID 359)
Abstract
Background and Aims
With a prevalence of approximately 1%, rheumatoid arthritis (RA) is one of the most frequent autoimmune disorders. Treatment at early stages can significantly slow down disease progression or even prevent irreversible damages. However, an early diagnosis is often challenging. Up to 50% of early RA patients are negative for the standard serological markers rheumatoid factor (RF) or anti-cyclic citrullinated peptide (CCP) antibodies. A more comprehensive analysis of antigenic proteins and their underlying epitopes can provide the necessary information for innovative serological tests with higher sensitivity for early diagnosis of RA.
Methods
To identify novel biomarkers, we applied high-density peptide microarrays displaying large numbers of autoantigens/antigen candidates converted into >100.000 overlapping peptides including all citrullinated and carbamylated variants. Using this highly diverse library, we screened sera from different disease and control cohorts and identified various epitopes with a higher prevalence in previously seronegative early-stage patients.
Results
Bioinformatic analysis combined with machine learning resulted in a peptide biomarker combination, which allowed the diagnosis of early seronegative RA vs. healthy controls with an accuracy of 87% and early seropositive RA vs. healthy controls with an accuracy of 94%, respectively. The validation of the marker set using well-characterized patient samples (n=1027) by Aptiva particle-based multi-analyte technology (Werfen) revealed highly significant peptides for discriminating RA vs. controls. Logistic regression modeling demonstrated a higher sensitivity but slightly lower specificity when analyzing CCP3 in combination with the marker set as compared to CCP3 alone.
Conclusions
Hence, the novel marker set has the potential to improve the early diagnosis of RA.