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05.06 Specific t cell and b cell distributions characterise subgroups of patients with primary sjögren’s syndrome and are associated with disease activity and pro-inflammatory cytokine expression
  1. Lucas Le Lann1,
  2. Quentin Simon1,
  3. Christophe Jamin1,
  4. Divi Cornec1,
  5. Maria-Oriette Borghi2,
  6. Lorenzo Beretta3,
  7. Ricard Cervera4,
  8. Alain Saraux1,
  9. Rik Lories5,
  10. Carlo Chizzolini6,
  11. Marta Alarcón-Riquelme7,
  12. Jacques-Olivier Pers1
  1. 1INSERM U1227, Université de Brest, Labex IGO, CHRU Morvan, Brest, France
  2. 2Department of Clinical Science and Community Health, University of Milan, and Istituto Auxologico Italiano, Laboratory of Immunorheumatology, Cusano Milanino, Italy
  3. 3Referral Centre for Systemic Autoimmune Diseases, Fondazione IRCCS Ca’ Granda Ospedale Maggiore[JM1] Policlinico di Milano, Italy
  4. 4Autoinflammatory Diseases Clinical Unit, Department of Autoimmune Diseases, Working Group of Adult Rare Diseases, Hospital Clínic, University of Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain [JM2]
  5. 5Laboratory of Tissue Homeostasis and Disease, Skeletal Biology and Engineering Research Centre, KU Leuven and Division of Rheumatology, University Hospitals Leuven, Belgium
  6. 6Division of immunology and allergy, department of medical specialties, Geneva university hospitals and school of medicine, Geneva, Switzerland
  7. 7GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, PTS GRANADA, Granada, Spain


Background The goal of the IMI PRECISESADS project is to reclassify individuals affected by systemic autoimmune diseases (SADs) into clusters of molecular, instead of clinical entities. In this project, we investigated 40 individuals with primary Sjögren’s syndrome (pSS), as diagnosed by the revised American-European classification criteria and 53 healthy controls (HCs) to determine whether a fine flow cytometry analysis of T and B cell distribution in whole blood could cluster individuals according to disease activity.

Methods Two flow cytometry panels were designed. The first panel was dedicated to T cells and combined CD57, CD45RA, CD62L, CD27, CD38, CD3, CD4, CD8 mAbs. The second panel was dedicated to B cells and combined IgD, TACI, CD5, CD24, CD27, CD38, CD19, CD11b mAbs. Disease activity was determined according to ESSDAI. A Luminex-based system was used to analyse up to 88 cytokines, chemokines and soluble factors in serum of pSS patients and HCs.

Results A combined analysis of T and B cell distribution highlighted two groups of individuals with a strong cluster of pSS patients in one of them. Indeed, the first cluster (group A) gathers together 24 pSS patients and 5 HCs while group B consists in 16 pSS patients and 49 HCs. Group A was characterised by the association of an increase of activated naïve B cells (IgD+ CD24+ CD38+ CD27-), a decrease of memory B cells (IgD- CD38- CD27+), an increase of central memory CD4+ T cells (CD45RA- CD62L+ CD27+), an increase of effector memory CD8+ T cells (CD45RA- CD62L- CD27-) and a decrease of central memory CD8+ T cells (CD45RA- CD62L+ CD27+) compared to group B and 91% of HCs. Interestingly, group A patients have a higher disease activity score when compared to group B (Mean ESSDAI score 5.0±1.9 versus 3.2±0.9 respectively). Finally, serum pro-inflammatory molecules were markedly up-regulated in group A patients compared to HCs and group B patients.

Conclusions A fine flow cytometry analysis of T and B cell subsets characterises pSS patients with a higher disease activity score and a pro-inflammatory signature. Similar approaches are ongoing in the context of the PRECISESADS project for other SADs.

This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking PRECISESADS grant n°

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