Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients

Abstract

OBJECTIVE: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools. METHODS: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE). RESULTS: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%. CONCLUSION: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients.