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

Abstract

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.