Insights into the detection of AMPA cross-reactivity: comparing cyclic peptide- to protein-based assays.

BACKGROUND

Autoantibodies targeting antigens carrying distinct post-translational modifications (PTMs), including citrullinated, carbamylated, and acetylated residues, are characteristic for rheumatoid arthritis (RA). These anti-modified protein antibodies (AMPAs) are typically detected using enzyme-linked immunosorbent assays (ELISAs), with peptides or protein antigens carrying these modifications. AMPAs exhibit significant cross-reactivity towards multiple PTMs, and increased cross-reactivity before disease onset may serve as a biomarker of disease progression. However, the impact of antigen backbone variations on cross-reactivity detection remains unclear. Therefore, we investigated how PTM-backbone variations affect AMPA-reactivity detection.

METHODS

Sera of 608 RA patients from the Early Arthritis Clinic (EAC) were measured for AMPA reactivity using modified fetal calf serum (FCS)- and cyclic peptide (CXP2)-based ELISAs. To investigate cross-reactivity patterns, we isolated AMPAs from serum using either modified FCS or peptides and assessed the reactivity of the isolated antibodies towards three different PTMs.

RESULTS

CXP2-based assays reveal a higher proportion of patients with serum reactivity against multiple PTM residues, while FCS-based assays exhibit a more restricted serological profile. When comparing responses to citrullinated versus carbamylated backbones, 61.2% of samples reacted to both PTM-residues on CXP2, while on FCS this percentage significantly decreased to 54.0%. The antigen backbone also influences AMPA isolation, as modified FCS captures AMPAs with a more restricted, less cross-reactive epitope recognition profile compared to those captured with modified peptides.

CONCLUSION

Antigen backbones influence the detection of AMPA cross-reactivity. Gaining a better understanding of how PTM backbones affect this detection could provide insights into the structural basis of AMPA reactivity, and refine data interpretation by highlighting how assay choice influences results.