Longitudinal autoantibody profiling in systemic sclerosis uncovers biomarkers associated with disease progression 2309123

Abstract

Abstract Introduction To evaluate dynamic changes in autoantibody profiles in naïve systemic sclerosis (nSSc) patients under treatment and to identify biomarkers associated with disease progression. Methods Serum samples from 50 nSSc patients at baseline and follow-up after treatment for 5 years, along with 50 controls, were analyzed. Autoantibody profiles were assessed using an autoantigen microarray targeting 120 autoantigens. Proteomic analysis was conducted via liquid chromatography—mass spectrometry in data-independent acquisition mode. Cox proportional hazards models were used to assess associations with disease progression, and Spearman’s correlation was applied to analyze antibody-protein interactions. Results Baseline autoantibody profiling identified 20 significant elevated autoantibodies which divided the patients into two subgroups: SSc-high and SSc-low, with the SSc-high patients showed more severe clinical characteristics. Longitudinal analysis revealed that 85% of patients with increasing autoantibody titers experienced disease progression, while 65% of those with decreasing titers showed clinical improvement. Notably, increased anti-Topoisomerase I, anti-CENPB and anti-TPO antibody titters were strongly linked to disease progression. Proteomic analysis identified 117 proteins involved in tissue repair and immune modulation in patients with declining titters and clinical improvement, whereas 42 proteins linked to lipid metabolism and oxidative stress were enriched in those with rising titers and disease progression. Antibody-protein correlations highlighted key molecular interactions, including SERPINE1 and muscarinic receptor antibodies, were identified. Conclusion Dynamic changes in autoantibody titers, rather than baseline levels, were more strongly associated with SSc trajectory. Proteomic signatures suggest lipid metabolism and oxidative stress as potential drivers, highlighting novel biomarkers and therapeutic targets for personalized SSc management. Funding Source n/a Topic Categories Immune Mechanisms of Human Disease (HUM)