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Abstract Number: 41

A Fine Bioinformatical Analysis of Lymphocyte Distribution Predicts the Diagnosis of Systemic Autoimmune Diseases

Quentin Simon1, Bénédicte Rouvière1, Tifenn Martin1, Lucas Le Lann1, Alain Saraux1, Valérie Devauchelle-Pensec1, Concepcion Marañón2, Nieves Varela Hernández2, Aleksandra Dufour3, Carlo Chizzolini4, Ellen de Langhe5, Nuria Barbarroja6, Chary Lopez-Pedrera7, Velia Gerl8, Aurelie Degroof9, Julie Ducreux10, Elena Trombetta11, Tianlu Li12, Marta Alarcón-Riquelme13, Christophe Jamin1 and Jacques-Olivier Pers1, 1U1227, Université de Brest, Inserm, Labex IGO, CHU de Brest, Brest, France, 2GENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain, 3Immunology & Allergy, University Hospital and School of Medicine, Geneva, Switzerland, 4University hospital of Geneva, Geneva, Switzerland, 5Rheumatology, University Hospital KU Leuven, Leuven, Belgium, 6Rheumatology service, IMIBIC/Reina Sofia Hospital/University of Cordoba, Cordoba, Spain, 7IMIBIC/Reina Sofia Hospital/ University of Cordoba, Cordoba, Spain, 8Department of Rheumatology and Clinical Immunology, Charité University Hospital, Berlin, Germany, 9Pôle de Maladies Rhumatismales, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels, Belgium, 10Pôle de pathologies rhumatismales inflammatoires et systémiques, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels, Belgium, 11Laboratorio di Analisi Chimico Cliniche e Microbiologia - Servizio di Citofluorimetria, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milano, Italy, 12Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain, 13GENYO. Center for Genomics and Oncological Research, Granada, Spain

Meeting: 2017 ACR/ARHP Annual Meeting

Date of first publication: September 18, 2017

Keywords: autoimmune diseases, Bioinformatics, diagnosis and lymphocytes

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Session Information

Date: Sunday, November 5, 2017

Session Title: B Cell Biology and Targets in Autoimmune Disease Poster

Session Type: ACR Poster Session A

Session Time: 9:00AM-11:00AM

Background/Purpose : We investigated 194 individuals with SADs (38 primary Sjögren’s syndrome (pSS), 47 rheumatoid arthritis (RA), 46 systemic lupus erythematosus (SLE), 42 systemic sclerosis (SSc) and 21 undifferentiated connective tissue disease (UCTD) patients) 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 diagnosis.

Methods: Two flow cytometry panels were designed. The first panel was dedicated to T cells and combined CD57, CD45RA, CD62L, CD27, CD38, CD3, CD4 and CD8 mAbs. The second panel was dedicated to B cells and combined IgD, TACI, CD27, CD5, CD38, CD19 and CD24 mAbs. A classical manual gating strategy and the Flow-clustering without K (FLOCK) investigation, a density-based clustering approach to algorithmically identify relevant cell populations from multiple samples in an unbiased fashion, were used.

Results: The manual gating strategy allows the identification of 17 distinct lymphocyte subsets. The prediction of the different SADs was determined by discriminant function analysis (DFA). No clustering was found. The FLOCK exploration of the merged HCs identifies 85 distinct subsets of lymphocytes used as reference when compared to SADs . The DFA analysis clearly clusters the HCs and the patients according to each SAD (see figure below).

When compared to HCs, the pSS signature was discriminated by an increase in IgDhiCD24hiCD38hiCD27–TACI–CD5hi transitional B cells, and an increase of CD45RA+CD27–CD62Llo/-CD57hi effector CD8+ T cells.

The SLE signature was discriminated by an increase in IgD–CD24loCD38–CD27–TACI+CD5– memory like B cells, an increase in CD45RA–CD62L+CD38hi activated central memory CD4+ T cells.

The RA signature was discriminated by an increase in IgDhiCD24loCD38–CD27–TACI+CD5– unactivated mature naïve B cells and a decrease in CD45RA+CD62L+CD38hi naïve CD8+ T cells.

The SSc signature was discriminated by a decrease in CD45RA+CD62L+CD38hi naïve CD8+ T cells.

Interestingly, patients with UCTD were distributed among the different clusters (28% with HC, 29% with SLE, 29% with SSc, 9% with RA and 5% with pSS clusters).

Conclusion: A fine bioinformatical flow cytometry analysis of T and B cell subsets clusterizes patients and HCs suggesting that each SAD can be associated with abnormal specific phenotypical distributions that could be helpful in the diagnosis.

This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking PRECISESADS grant n° 115565.www.precisesads.eu


Disclosure: Q. Simon, EFPIA, 2; B. Rouvière, None; T. Martin, None; L. Le Lann, EFPIA, 2; A. Saraux, None; V. Devauchelle-Pensec, Roche-Chugai provided me tocilizumab for the SEMAPHORER study, 2; C. Marañón, EFPIA, 2; N. Varela Hernández, EFPIA, 2; A. Dufour, EFPIA, 2; C. Chizzolini, EFPIA, 2; E. de Langhe, None; N. Barbarroja, None; C. Lopez-Pedrera, EFPIA, 2; V. Gerl, EFPIA, 2; A. Degroof, EFPIA, 2; J. Ducreux, EFPIA, 2; E. Trombetta, EFPIA, 2; T. Li, EFPIA, 2; M. Alarcón-Riquelme, Genzyme/Sanofi Corporation, 2; C. Jamin, EFPIA, 2; J. O. Pers, EFPIA, 2.

To cite this abstract in AMA style:

Simon Q, Rouvière B, Martin T, Le Lann L, Saraux A, Devauchelle-Pensec V, Marañón C, Varela Hernández N, Dufour A, Chizzolini C, de Langhe E, Barbarroja N, Lopez-Pedrera C, Gerl V, Degroof A, Ducreux J, Trombetta E, Li T, Alarcón-Riquelme M, Jamin C, Pers JO. A Fine Bioinformatical Analysis of Lymphocyte Distribution Predicts the Diagnosis of Systemic Autoimmune Diseases [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/a-fine-bioinformatical-analysis-of-lymphocyte-distribution-predicts-the-diagnosis-of-systemic-autoimmune-diseases/. Accessed December 11, 2019.
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