Literature DB >> 23989988

An immunological biomarker to predict MTX response in early RA.

Frederique Ponchel1, Vincent Goëb2, Rekha Parmar1, Yasser El-Sherbiny1, Marjorie Boissinot1, Jehan El Jawhari1, Agata Burska1, Edward M Vital1, Stephanie Harrison1, Philip G Conaghan1, Elizabeth Hensor1, Paul Emery1.   

Abstract

OBJECTIVES: The therapeutic goal for patients with rheumatoid arthritis (RA) is clinical remission. This is best achieved by early diagnosis and appropriate therapeutic intervention. RA is associated with dysregulation of T-cell subsets (naïve, regulatory (Treg) and inflammation-related cells (IRC)) early in the disease. Our aim was to test the hypothesis that T-cell subset quantification can predict the achievement of clinical remission with early treatment in RA.
METHODS: T-cell subsets were quantified in 108 drug-naïve, early RA patients commencing methotrexate (MTX) or MTX+antitumor necrosis factor (anti-TNF) and in 105 healthy controls (HC). The primary outcome assessed was remission (DAS28<2.6). A pilot study used frozen cells (38 patients and 35 HCs, see online supplementary material) and was validated with fresh blood (70 patients and 70 HCs).
RESULTS: Immune dysregulation in early RA was confirmed with an association between age and reduced naïve cells compared with HCs (p=0.006), a lower age-adjusted Treg and higher IRC frequency (p=0.001). Anticitrullinated peptide antibody (ACPA) positivity was associated with lower naïve (p=0.031) and Treg frequencies (p=0.039). In 50 patients treated with MTX, ACPA/age-adjusted analysis demonstrated that higher naïve cell frequency (relative to HC) was associated with remission (OR 5.90 (1.66 to 20.98), p=0.006, sensitivity/specificity 62%/79%, Positive Predictive Value (PPV)/Negative Predictive Value (NPV) 66%/76%). Remission with MTX+anti-TNF (n=20) was not found to be associated with naïve cell frequency, and for patients with reduced naïve cells the remission rate increased from 24% (MTX) to 42% (MTX+anti-TNF).
CONCLUSIONS: Baseline T-cell subset analysis has a value in predicting early RA remission with first therapy with MTX. Immunological analysis could be used in conjunction with clinical/serological features to predict response to MTX and help select the most appropriate therapy at disease presentation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Entities:  

Keywords:  Naïve T-cell; regulatory T-cells Rheumatoid arthritis; remission

Mesh:

Substances:

Year:  2013        PMID: 23989988     DOI: 10.1136/annrheumdis-2013-203566

Source DB:  PubMed          Journal:  Ann Rheum Dis        ISSN: 0003-4967            Impact factor:   19.103


  23 in total

1.  Genetics: a new interpretation of genetic studies in RA.

Authors:  Michel Neidhart; Emmanuel Karouzakis
Journal:  Nat Rev Rheumatol       Date:  2014-02-25       Impact factor: 20.543

2.  Response to methotrexate predicts long-term patient-related outcomes in rheumatoid arthritis.

Authors:  Dietmar Krause; Bernadette Gabriel; Gertraud Herborn; Juergen Braun; Rolf Rau
Journal:  Clin Rheumatol       Date:  2016-02-26       Impact factor: 2.980

Review 3.  Remission-induction therapies for early rheumatoid arthritis: evidence to date and clinical implications.

Authors:  Francisco Espinoza; Sylvie Fabre; Yves-Marie Pers
Journal:  Ther Adv Musculoskelet Dis       Date:  2016-06-13       Impact factor: 5.346

Review 4.  Predicting methotrexate resistance in rheumatoid arthritis patients.

Authors:  Mary Beth Yu; Anthony Firek; William H R Langridge
Journal:  Inflammopharmacology       Date:  2018-03-12       Impact factor: 4.473

Review 5.  Lymphocytes as Biomarkers of Therapeutic Response in Rheumatic Autoimmune Diseases, Is It a Realistic Goal?

Authors:  Kristina Schreiber; Gaetane Nocturne; Divi Cornec; Claire I Daïen
Journal:  Clin Rev Allergy Immunol       Date:  2017-10       Impact factor: 8.667

Review 6.  The advances of methotrexate resistance in rheumatoid arthritis.

Authors:  Jun Yu; Peng Zhou
Journal:  Inflammopharmacology       Date:  2020-08-05       Impact factor: 4.473

Review 7.  cDNA phage display for the discovery of theranostic autoantibodies in rheumatoid arthritis.

Authors:  Patrick Vandormael; Patrick Verschueren; Liesbeth De Winter; Veerle Somers
Journal:  Immunol Res       Date:  2017-02       Impact factor: 2.829

8.  Prevention of disease flares by risk-adapted stratification of therapy withdrawal in juvenile idiopathic arthritis: results from the PREVENT-JIA trial.

Authors:  Joachim Gerss; Monika Tedy; Ariane Klein; Gerd Horneff; Maria Miranda-Garcia; Christoph Kessel; Dirk Holzinger; Valda Stanevica; Joost F Swart; David A Cabral; Hermine I Brunner; Dirk Foell
Journal:  Ann Rheum Dis       Date:  2022-03-08       Impact factor: 27.973

9.  Changes in peripheral blood immune cell composition in osteoarthritis.

Authors:  F Ponchel; A N Burska; E M A Hensor; R Raja; M Campbell; P Emery; P G Conaghan
Journal:  Osteoarthritis Cartilage       Date:  2015-07-08       Impact factor: 6.576

Review 10.  Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis.

Authors:  Chamith Y Fonseka; Deepak A Rao; Soumya Raychaudhuri
Journal:  Curr Opin Immunol       Date:  2017-09-06       Impact factor: 7.486

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