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Targeting JAK/STAT pathway in Takayasu’s arteritis
  1. Paul Régnier1,2,
  2. Alexandre Le Joncour1,2,3,
  3. Anna Maciejewski-Duval1,2,
  4. Anne-Claire Desbois1,2,3,
  5. Cloé Comarmond1,2,3,
  6. Michelle Rosenzwajg1,2,
  7. David Klatzmann1,2,
  8. Patrice Cacoub1,2,3,
  9. David Saadoun1,2,3
  1. 1 UPMC Université Paris 6, INSERM, UMR S 959, Immunology-Immunopathology-Immunotherapy (i3), Sorbonne Université, Paris, France
  2. 2 Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (DHU i2B), Groupe Hospitalier de la Pitié-Salpêtrière, Assistance Publique - Hôpitaux de Paris, Paris, France
  3. 3 Département de médecine interne et d'immunologie clinique, Centre national de référence Maladies Autoimmunes et Systémiques Rares et Centre national de référence Maladies Auto-inflammatoires, Assistance Publique - Hôpitaux de Paris, Groupe Hospitalier de la Pitié-Salpêtrière, Paris, France
  1. Correspondence to Dr David Saadoun, Médecine Interne et Immunologie clinique, APHP, Hopital Pitie Salpétrière, Paris 75013, France; david.saadoun{at}


Objective Takayasu’s arteritis (TAK) is a large vessel vasculitis with important infiltration of proinflammatory T cells in the aorta and its main branches, but its aetiology is still unknown. Our work aims to explore the involvement of Janus Kinase/Signal Transducers and Activators of Transcription (JAK/STAT) signalling pathway in proinflammatory T cells differentiation and disease activity of TAK.

Methods We analysed transcriptome and interferons gene signatures of fluorescence-activated cell sorting (FACS-sorted) CD4+ and CD8+ T cells from healthy donors (HD) and in 25 TAK (median age of 37.6 years including 21 active TAK with National Institutes of Health (NIH) score >1). Then we tested, in vitro and in vivo, the effects of JAK inhibitors (JAKinibs) in TAK.

Results Transcriptome analysis showed 248 and 432 significantly dysregulated genes for CD4+ and CD8+ samples between HD and TAK, respectively. Among dysregulated genes, we highlighted a great enrichment for pathways linked to type I and type II interferons, JAK/STAT and cytokines/chemokines-related signalling in TAK. We confirmed by Real Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) the upregulation of type I interferons gene signature in TAK as compared with HD. JAKinibs induced both in vitro and in vivo a significant reduction of CD25 expression by CD4+ and CD8+ T cells, a significant decrease of type 1 helper T cells (Th1) and Th17 cells and an increase of Tregs cells in TAK. JAKinibs also decreased C reactive protein level, NIH score and corticosteroid dose in TAK patients.

Conclusions JAK/STAT signalling pathway is critical in the pathogenesis of TAK and JAKinibs may be a promising therapy.

  • systemic vasculitis
  • cytokines
  • chemokines
  • inflammation
  • T cells

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  • Handling editor Josef S Smolen

  • PC and DS contributed equally.

  • Contributors PR, ALJ and AM-D equally contributed to perform experiments, to write and review the manuscript and to conduct the study. A-CD, CC, MR, DK, PC and DS equally contributed to redact and review the manuscript and to supervise the study.

  • Funding The research was funded by IMI (European Project) Safe-T.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available on reasonable request. Transcriptome data from FACS-sorted CD4+ and CD8+ T cells from healthy donors and Takayasu’s arteritis-affected patients are available on request to Pr. DS: They are presented as deidentified patient tabular data (rows = normalised gene expression and columns = patients) in a plain text format. Reuse is permitted if data are not altered in any way and if original authors are correctly cited in the subsequent publications. Raw CEL files were standardised and normalised using limma R package and standard methods (notably RMA normalisation).