4.7 Article

Integrated, multicohort analysis reveals unified signature of systemic lupus erythematosus

Journal

JCI INSIGHT
Volume 5, Issue 4, Pages -

Publisher

AMER SOC CLINICAL INVESTIGATION INC
DOI: 10.1172/jci.insight.122312

Keywords

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Funding

  1. National Science Foundation [DGE-114747]
  2. NIH NLM [T15 LM 007033]
  3. NIH [K08-AI-080945, 1 U19-AI090019, NIAID 1 R01 AI125197-01]
  4. Stanford Child Health Research Institute
  5. Arthritis Foundation
  6. Stanford Gabilan Graduate Fellowship in Science and Engineering
  7. Stanford Women and Sex Differences in Medicine (WSDM) Seed Grant
  8. Stanford Medical Scientist Training Program (NIGMS) [5T32GM007365-43]
  9. Bill and Melinda Gates Foundation [OPP1113682]
  10. National Institute of Allergy and Infectious Diseases (NIAID) [1U19AI109662, U19AI057229, 5R01AI125197]
  11. Department of Defense [W81XWH-18-1-0253, W81XWH1910235]
  12. Ralph & Marian Falk Medical Research Trust
  13. Henry Gustav Floren Family Trust
  14. NIH, Stanford Autoimmunity Center of Excellence (ACE) [NIAID U19-AI1110491]
  15. NIH, ACE Collaborative Project [NIAID 1 UM1AI110498-01]

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Systemic lupus erythematosus (SLE) is a complex autoimmune disease that follows an unpredictable disease course and affects multiple organs and tissues. We performed an integrated, multicohort analysis of 7,471 transcriptomic profiles from 40 independent studies to identify robust gene expression changes associated with SLE. We identified a 93-gene signature (SLE MetaSignature) that is differentially expressed in the blood of patients with SLE compared with healthy volunteers; distinguishes SLE from other autoimmune, inflammatory, and infectious diseases; and persists across diverse tissues and cell types. The SLE MetaSignature correlated significantly with disease activity and other clinical measures of inflammation. We prospectively validated the SLE MetaSignature in an independent cohort of pediatric patients with SLE using a microfluidic quantitative PCR (qPCR) array. We found that 14 of the 93 genes in the SLE MetaSignature were independent of IFN-induced and neutrophil-related transcriptional profiles that have previously been associated with SLE. Pathway analysis revealed dysregulation associated with nucleic acid biosynthesis and immunometabolism in SLE. We further refined a neutropoiesis signature and identified underappreciated transcripts related to immune cells and oxidative stress. In our multicohort, transcriptomic analysis has uncovered underappreciated genes and pathways associated with SLE pathogenesis, with the potential to advance clinical diagnosis, biomarker development, and targeted therapeutics for SLE.

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