O08 Proteomic investigation of the progressive nature of systemic sclerosis from presystemic sclerosis to skin fibrosis

Abstract Introduction and aims Systemic sclerosis (SSc) is a rare, severe rheumatological disease with high morbidity and mortality, with a life expectancy of 10 years after diagnosis. Early symptoms overlap with more common skin conditions, delaying diagnosis. This study aimed to identify biomarkers within the skin proteome linked to disease progression, in patients meeting the Very Early Diagnosis of Systemic Sclerosis (VEDOSS) criteria who lack visible skin involvement or presentation. Methods Skin biopsies from the forearm of healthy controls, VEDOSS and patients with SSc split by local skin stiffness (n = 3–4 per group, N = 13) were analysed using SomaSCAN proteomic platform. Disease severity was assessed via the modified Rodnan skin score (mRSS) and patient characteristics. Bioinformatic analysis, including Limma, Pearson’s correlation, gene ontology, and pathway analyses, was conducted on over 7000 proteins. Serum and tissue sections were also collected for validation, and dermal fibroblasts were cultured from biopsies for disease modelling. Results Pearson’s correlation analysis identified strong links between total MRSS and protein for SERPINE2 (R² = 0.94), CCL18 (R² = 0.92) and THBS1 (R² = 0.85). MATN4 and CFD underexpression was measured across all SSc stages, including VEDOSS, while ERAP1 was measured overexpressed. Differential expression analysis highlighted overexpression of FABP9, GPX3, and GSTZ1 in VEDOSS skin, along with a reduction in matricellular proteins. While gene ontology analysis revealed disruptions in extracellular matrix (ECM) remodelling and matricellular proteins with increased metabolic and reactive oxygen species-associated proteins. Markers of patient progression to SSc included coagulation and wound healing proteins. Conclusions Overall, proteomic analysis of stratified stages of SSc skin revealed dynamic ECM protein turnover at early stages, before visible skin presentation. Known SSc biomarkers were validated for advanced stages of SSc, while novel biomarkers were identified at preclinical stages. Pathway analysis has identified targetable pathways to prevent patient progression to an SSc diagnosis.