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Gene profiling predicts rheumatoid arthritis responsiveness to IL-1Ra (anakinra)

Carine Bansard1, Thierry Lequerré, Céline Derambure

  • 1Department of Rheumatology, University of Rouen, 76031 Rouen Cedex, France.

Abstract

Insights

Predicting rheumatoid arthritis treatment response is crucial. Gene profiling of peripheral blood mononuclear cells can identify patients likely to respond to anakinra and methotrexate combination therapy.

Area of Science:

  • Rheumatology
  • Molecular Biology
  • Genetics

Background:

  • Rheumatoid arthritis (RA) treatment with biologics has a significant non-response rate (30-40%) in methotrexate-resistant patients.
  • Optimizing biologic selection is essential for improving patient outcomes.

Purpose of the Study:

  • To predict responsiveness to the combination therapy of anakinra and methotrexate (MTX) using peripheral blood mononuclear cell gene profiling.
  • To optimize treatment choices for RA patients who are resistant to MTX.

Main Methods:

  • Thirty-two RA patients receiving anakinra (100 mg/day subcutaneously) and MTX were studied.
  • Responders were defined as those with a decrease in Disease Activity Score-28 (DAS-28) of ≥1.2 at 3 months.
  • Pre-treatment peripheral blood mononuclear cell gene expression profiling was performed using microarrays.

Main Results:

  • A set of 52 differentially expressed mRNAs was identified, capable of separating responders from non-responders via hierarchical clustering.
  • Quantitative RT-PCR validation of seven key transcripts accurately classified 15 of 18 additional patients (87.5% specificity, 77.8% negative-predictive value for responders).
  • A significant portion (56%) of the identified genes were associated with Interleukin-1 beta (IL-1β).

Conclusions:

  • A predictive gene expression profile for anakinra-MTX response was developed using a non-invasive method.
  • This profile, after further validation, could be widely implemented for selecting RA patients likely to benefit from this combination therapy.
  • The study provides a potential tool for personalized medicine in RA treatment.

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