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Kinetic analysis of synovial signaling and gene expression in animal models of arthritis
  1. Akihisa Fukushima (afukushima{at}
  1. University of California, San Diego, United States
    1. David L Boyle (dboyle{at}
    1. University of California, San Diego, United States
      1. Maripat Corr (mcorr{at}
      1. University of California, San Diego, United States
        1. Gary S Firestein (gfirestein{at}
        1. UCSD School of Medicine, United States


          Objectives: Animal models of arthritis are frequently used to evaluate novel therapeutic agents. However, their ability to predict responses in humans is variable. We examined the time course of signaling molecule and gene expression in two models of arthritis to assist with selection of the model and timing of drug administration.

          Methods: The passive K/BxN serum transfer and collagen-induced arthritis (CIA) models were studied. Activation of MAP kinase and IFN-response pathways was evaluated by Q-PCR and Western blot analysis of ankle joints at various time points during the models.

          Results: The kinetics of gene expression and kinase phosphorylation were strikingly different in passive K/BxN and CIA. All three MAP kinases (ERK, JNK, and p38) and upstream kinases were activated within days in passive K/BxN and, except for p38, declined as arthritis severity decreased. Surprisingly, IFN-regulated genes, including IRF7, were not induced in the model. In CIA, activation of ERK and JNK was surprisingly low, and p38 phosphorylation mainly peaked late in disease. IFN-response genes were activated during CIA, with especially prominent peaks at the onset of clinical arthritis.

          Conclusions: Timing of treatment and selection of CIA or passive K/BxN could have an important impact on therapeutic response. p38, in particular, increases during the late stages of disease. ERK and JNK patterns are similar in passive K/BxN and RA, while IFN-response genes in CIA and RA were similar. The dichotomy between RA and animal models could help explain the poor correlation between efficacy in RA and pre-clinical studies.

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