Evaluation of particle-based multi-analyte technology for autoantibody detection in systemic sclerosis: concordance with conventional methods and clinical associations.

OBJECTIVES

To evaluate the clinical performance of particle-based multi-analyte technology (PMAT) for the detection of systemic sclerosis (SSc)-associated autoantibodies and to explore correlations between antibody profiles and disease manifestations.

METHODS

We assessed PMAT performance in 124 SSc patients fulfilling the 2013 ACR/EULAR criteria, 205 disease controls, and 25 healthy individuals. All samples were tested for a broad autoantibody panel, including both classification and non-criteria autoantibodies. Concordance with conventional methods (chemiluminescence and ELISA) and associations with clinical features were analysed.

RESULTS

PMAT showed excellent agreement with established techniques for anti-centromere autoantibodies (ACA) (κ=0.95) and anti-topoisomerase I (anti-Topo I) (κ=0.95), and good agreement for anti-RNA polymerase III autoantibodies (anti-RNApol III) (κ=0.78), confirming its reliability in detecting major SSc autoantibodies. The most prevalent autoantibodies were ACA (54.0%), anti-Topo I (21.0%), and anti-RNApol III (5.7%), each associated with distinct clinical phenotypes: ACA with limited cutaneous SSc and absence of interstitial lung disease (ILD); anti-Topo I with diffuse cutaneous SSc, ILD, and scleroderma renal crisis; and anti-RNApol III with digital ulcers and calcinosis. Importantly, novel associations were identified between PUF60 isoform 6 and severe ILD, and between PUF60 isoform 1 and the sine scleroderma phenotype, suggesting their potential as emerging biomarkers.

CONCLUSIONS

These findings support the diagnostic and clinical utility of comprehensive serological profiling and the integration of PMAT into routine diagnostic workflows. The identification of novel autoantibody-phenotype associations underscore the value of multiplex technologies in advancing precision medicine for SSc.