Precision Proteomic Profiling of Systemic Lupus Erythematosus—Correlating Disease Activity and Complement Levels with Clinical Phenotypes

Background/Objectives: Systemic lupus erythematosus (SLE) is characterized by diverse clinical presentations and complex immunological mechanisms. This study aimed to characterize patient serology associated with disease activity scored using the systemic lupus erythematosus disease activity index (SLEDAI) and investigate the molecular signature of complement activation (measured through C3dg, a complement breakdown product) in SLE patients utilizing high-throughput mass spectrometry and autoantibody profiling. Methods: Plasma samples from 39 SLE patients in four mutually exclusive groups based on either disease activity scores (high/low SLEDAI) or complement activation levels (high/low C3dg) were analyzed using rapid LC-MS/MS, followed by unsupervised and supervised protein expression analysis. Complement activation was evaluated by measuring C3dg levels, and disease activity was scored using SLEDAI. Autoantibody reactivities were profiled using global autoantibody protein microarrays. Data are available via ProteomeXchange with identifier PXD066214. Results: Differential proteomic analyses revealed 25 proteins associated with SLE disease activity (high vs. low SLEDAI scores) and 25 proteins linked to complement activation levels (high vs. low C3dg). Enriched pathways indicated that adaptive immune response, classical complement activation, and immunoglobulin production correlated with disease activity, while complement activation and coagulation cascades were primarily associated with complement activation levels. Autoantibody profiling highlighted distinct reactivity patterns between subgroups, suggesting varying degrees of immune-mediated tissue damage. Conclusions: In this study, disease activity and complement activation markers were associated with overlapping yet non-identical plasma proteomic patterns in SLE. These findings support the feasibility of rapid mass spectrometry-based proteomics and autoantibody profiling for generating candidate molecular signatures in SLE. These findings serve as exploratory signatures that require validation in larger independent cohorts before they can be considered for clinical stratification and decision-making.