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Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics

Glynn Dennis, Cécile T J Holweg, Sarah K Kummerfeld

    Arthritis Research & Therapy
    |August 29, 2014
    PubMed
    Abstract

    Insights

    Rheumatoid arthritis (RA) patients with a myeloid phenotype respond best to anti-TNFα therapy. Identifying serum biomarkers like sICAM1 and CXCL13 can predict treatment response in RA and other autoimmune diseases.

    Area of Science:

    • Immunology
    • Rheumatology
    • Genomics

    Background:

    • Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease with poorly understood molecular drivers impacting therapeutic response.
    • Understanding RA heterogeneity is crucial for developing targeted treatments.

    Purpose of the Study:

    • To investigate the relationship between synovial tissue phenotypes and clinical response to targeted therapies in RA.
    • To identify serum biomarkers predicting treatment outcomes in RA patients.

    Main Methods:

    • Analysis of synovial tissue gene expression, histology, and cellularity in RA cohorts.
    • Biomarker analysis in serum samples from the ADACTA trial comparing tocilizumab (anti-IL-6R) and adalimumab (anti-TNFα).

    Main Results:

    • Four RA synovium phenotypes identified: lymphoid, myeloid, low inflammatory, and fibroid, each with distinct gene expression profiles.
    • Higher baseline myeloid gene signature expression correlated with better response to anti-TNFα therapy.
    • Serum sICAM1 (myeloid) and CXCL13 (lymphoid) levels differentially predicted response to anti-TNFα versus anti-IL-6R therapies.

    Conclusions:

    • RA molecular heterogeneity influences clinical outcomes, with the myeloid phenotype showing superior response to anti-TNFα.
    • Serum biomarkers can potentially predict treatment response in RA and other autoimmune conditions.

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