Systemic lupus erythematosus (SLE) is an autoimmune condition that involves multiple organs and has an unpredictable disease course. To understand this heterogeneity, the authors used transcriptomics to profile 27 distinct immune cell types from 136 patients with SLE and 89 healthy controls. A key design of the study was to determine two gene signatures for each immune cell population: these ‘disease state’ and ‘disease activity’ signatures were compiled by comparing gene expression in healthy controls to inactive SLE, and comparing inactive SLE to highly active SLE, respectively. The authors showed that the disease activity (rather than disease state) signatures most accurately reflect organ involvement and responsiveness to therapy. By contrast, disease state scores more closely aligned with SLE risk alleles previously identified through GWAS. These findings suggest the relevance of focusing on disease activity (rather than the disease state) gene signatures to identify better biomarkers and therapeutic targets for SLE.

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