Shared and unique molecular signatures across different autoantibody groups in systemic sclerosis: a multiomics analysis.

OBJECTIVES

Each autoantibody associated with systemic sclerosis (SSc) is linked to distinct clinical features, suggesting underlying molecular heterogeneity. Although studies have characterised molecular signatures in anticentromere (ACA), antitopoisomerase I (ATA), and anti-RNA polymerase III (ARA) antibodies in patients who are SSc-positive, less frequent autoantibody groups remain unexplored. Our study employed multiomics analysis to identify shared and unique molecular profiles across SSc-associated autoantibody subgroups.

METHODS

We enrolled 166 patients with SSc stratified by antibody status (ACA = 55, ATA = 58, ARA = 24, anti-U1 ribonucleoprotein [U1RNP] = 12, anti-U3 ribonucleoprotein [U3RNP] = 8, anti-Ku [Ku] = 4, and anti-Th/To [Th/To] = 5). We performed multiomics profiling, including plasma proteomics, peripheral blood mononuclear cells (PBMCs) transcriptomics, immune cell phenotyping, and plasma metabolomics to identify shared and distinct features across groups.

RESULTS

All SSc subsets demonstrated common pathogenic features, including endothelial injury, extracellular matrix deposition identified by plasma proteomics, upregulated type I interferon (IFN) signalling revealed by transcriptomic analysis, and decreased regulatory B cells observed by immune cell profiling. Meanwhile, each autoantibody subgroup exhibited unique disease mechanisms, such as calcinosis in ACA-positive patients, metabolic oxidative stress in ATA-positive patients, activation of oncogenic signalling in ARA-positive patients, enhanced chromatin remodelling activity in U1RNP-positive patients, muscle involvement in U3RNP/Ku groups, and unique metabolic signalling related to pulmonary hypertension in Th/To-positive cases.

CONCLUSIONS

Our study addresses a critical gap by providing a comprehensive multiomics characterisation of both common and rare SSc-associated autoantibody groups, revealing shared and distinct molecular signatures that correlate with clinical features. Our findings highlight the potential for autoantibody-based stratification to guide precision management of SSc, paving the way for biomarker-driven approaches in SSc care.