Mass spectrometry based immunoprofiling in rheumatoid arthritis patients

Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting 2,9 million patients in Europe. If left untreated, severe joint destruction leading to impaired physical function is inevitable. Specific biomarkers such as anti-citrullinated peptide (ACPA) and rheumatoid factor (RF) can support a diagnosis of RA. However, in one third of RA patients, these biomarkers are absent. This percentage increases in the early stages of RA. Furthermore, it is now widely accepted that identification of RA in its earliest stages, assessment of disease severity at diagnosis, and implementation of an effective treatment strategy significantly improves a patient’s prognosis. This highlights the need for new complementary markers that will improve (early) diagnostic sensitivity. Likewise current markers only account for 32% of the total variance in predicting joint destruction. Additionally for prediction of the long-term evolution of disease activity and for prediction of response to targeted therapy new markers are needed to prevent trial and error to find the right drug for the right patient. Three hypervariable amino acid sequence variations, situated on the variable domains of the heavy and light chain of immunoglobulins, determine antigen specificity by forming a surface complementary to the antigen and are more commonly termed complementarity-determining regions (CDR’s). Due to selection pressure for the best binding variants during antibody development, the observed diversity in the variable epitope binding regions of immunoglobulins is significantly less than the total potential diversity. This causes antigen-specific IgG-derived peptides to be shared between individuals, who have serum autoantibodies which react with the same antigen. Mass spectrometry (MS) based platforms have recently been optimized to detect antibody molecules in patients and controls without prior knowledge of the antigen. As such, this MS-based immunoprofiling has the potential to identify novel antibody-derived peptide biomarkers useful for diagnosis of RA patients in which ACPA and RF are undetectable. This project aims to apply MS-based analyses of CDR’s to immunoprofile patients with RA and diseased controls, evaluate whether CDR-based immunoprofiles are useful for RA diagnosis and patient stratification, whether CDR-based immunoprofiles change over time with the goal to verify and validate these CDR-based immunoprofiles for diagnosis. Finally, we hope to develop and validate RA-specific CDR peptide biomarker panels that can be used in a clinical setting to simplify diagnosis, prognosis and therapy prediction in patients with RA.