SUMMARYBackgroundClinical heterogeneity, a hallmark of systemic autoimmune diseases (SADs) impedes early diagnosis and effective treatment, issues that may be addressed if patients could be grouped into a molecular defined stratification.MethodsWith the aim of reclassifying SADs independently of the clinical diagnoses, unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data of 918 patients with 7 SADs and 263 healthy controls was undertaken. In addition, an inception cohort was prospectively followed for 6 and 14 months to validate the results and analyze if cluster assignment changed or not with time.ResultsFour clusters were identified. Three clusters were aberrant, representing ‘inflammatory’, ‘lymphoid’, and ‘interferon’ patterns each including all diagnoses and defined by genetic, clinical, serological and cellular features. A fourth cluster showed no specific molecular pattern and accumulated also healthy controls. An independent inception cohort showed that with time, the molecular clusters remain stable, showing that single aberrant molecular signatures characterize each individual patient.ConclusionsPatients with SADs can be jointly stratified into three stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of therapy non-responsiveness marking a paradigm shift in the view of SADs.