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The demand for personalised healthcare: Identifying the ‘B cell patient’

The demand for personalised healthcare: Identifying the ‘B cell patient’. Dr Philippe Dieudé Rheumatology Department, University Bichat Hospital, Paris, France. Background. CTDs and autoimmune diseases (AIDs) share a common genetic background: HLA II

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The demand for personalised healthcare: Identifying the ‘B cell patient’

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  1. The demand for personalised healthcare: Identifying the ‘B cell patient’ Dr Philippe Dieudé Rheumatology Department, University Bichat Hospital, Paris, France

  2. Background CTDs and autoimmune diseases (AIDs) share a common genetic background: HLA II Non-HLA genes: PTPN22, IRF5, STAT4, BANK1…and more A common genetic background could lead to an overlap of different autoimmune phenotypes Frequency of overlap syndrome in other AIDs: Sjögren: 25% Type 1 diabetes: 5-20% SSc : 23% Alarcon Segovia M. Curr Rheumatol Rep 2004;6(3):171-4 Hemminki K Arthritis Rheum 2009 (3):661-668 Garcia-Carrasco M. Medicine (Baltimore) 2002; 81 (4):270-280 Somers EC. Epidemiology 2006;17(2):202-217 Liao KP. Arthritis & Rheumatism 2009; 60(3):653-660 Avouac J. Arthritis & Rheumatism 2008: 58 (9-suppl): S826

  3. Objectives To determine: Frequency of overlap syndrome in the RA population Whether overlap syndromes are restricted to a particular RA subset

  4. Study # 1: Frequency of an « enriched » immunological phenotype in the RA population Prospective study 6 months /114 patients with RA (ACR 1987 criteria) Screening of all RA patients for an « enriched » immunological phenotype: Anti-CCP, RF Anti-SSA,anti-SSB AI Thyroiditis Anti-parietal cells Anti-smooth muscle Anti-DNAn ACA, anti-Topo I, anti-RNP Non-RA specific autoantibodies

  5. Frequency of non-RA specific autoantibodies in the RA population

  6. Characteristics of the 55 patients with RA with enriched immunological phenotype

  7. Immunological phenotypes in RA patients % 80.8 30.7 15.4 11.5

  8. RA phenotype according to non-RA- specific autoantibody status p<0.003 p<0.001 Anti-CCP+

  9. Frequency of overlapping autoimmune diseases 38% Frequency of overlapping AID in the global RA sample: 18%

  10. Study # 2: Screening patients with RA for overlapping autoimmune diseases Prospective study (18 months) 334 patients with RA 2 Rheumatology Departments (Cochin & Bichat University Hospital, Paris) 117 patients included (35%) RA ACR 1987 criteria Diagnosis criteria for another AID 21% currently treated with rituximab

  11. Characteristics of the 117 patients with RA with overlapping AID

  12. Distribution of overlapping AID in the RA population %

  13. Distribution of overlapping AID in the RA population

  14. RA phenotype according to the overlap syndrome P<0.001 P<0.004

  15. Summary Co-occurrence of other AIDs with RA is frequent (18–35%) A particular RA phenotype: No statistical significant difference between RA patients with overlapping AIDs and those without Erosions Mean age at onset Mean disease duration Significant difference: Anti-CCP and RF positive status High anti-CCP production +++

  16. Questions and Perspective (1)… Do these RA patients have a « strong » B cell-driven disease? Anti-CCP+ and RF+ High anti-CCP production Other autoantibodies

  17. Questions and Perspective (2)… • Influence of anti-CCP status in RTX response? • Unclear • Which isotype? • Low anti-CCP IgM patients responded better to RTX • Anti-CCP IgM production is related to CD20-, CD79a+ B cell • Re-analyse RTX responses according to • Anti-CCP status • Qualitative anti-CCP status (isotype) • Quantitative anti-CCP status… Tak PP.et al Arthritis Rheum 2006 54 Supl9: S368 Teng YKO et al. Arthritis Rheum 2007; 56(12):3909-3918)

  18. Questions and Perspective (3)… Is rituximab more efficient in this particular RA patient segment? Our studies were not designed to detect such effect… Re-analyse RTX response according to : Enriched immunological phenotype Overlapping AIDs Personal experience of overlapping AIDs with RA : All were responders (EULAR) 79% received a 2nd course of RTX, 54% a 3rd course

  19. What does this mean for Ed’s patient? There is not enough biomarker data for this patient to suggest an overlapping AID

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