The need for prognosticators in rheumatoid arthritis. Biological and clinical markers: where are we now?

Genomics and proteomics: Applications in autoimmune diseases

Tremendous progress has been made over the past decade in the development and refinement of genomic and proteomic technologies for the identification of novel drug targets and molecular signatures associated with clinically important disease states, disease subsets, or differential responses to therapies. The rapid progress in high-throughput technologies has been preceded and paralleled by the elucidation of cytokine networks, followed by the stepwise clinical development of pathway-specific biological therapies that revolutionized the treatment of autoimmune diseases. Together, these advances provide opportunities for a long-anticipated personalized medicine approach to the treatment of autoimmune disease. The ever-increasing numbers of novel, innovative therapies will need to be harnessed wisely to achieve optimal long-term outcomes in as many patients as possible while complying with the demands of health authorities and health care providers for evidence-based, economically sound prescription of these expensive drugs. Genomic and proteomic profiling of patients with autoimmune diseases holds great promise in two major clinical areas: (1) rapid identification of new targets for the development of innovative therapies and (2) identification of patients who will experience optimal benefit and minimal risk from a specific (targeted) therapy. In this review, we attempt to capture important recent developments in the application of genomic and proteomic technologies to translational research by discussing informative examples covering a diversity of autoimmune diseases.

Blood autoantibody and cytokine profiles predict response to anti-tumor necrosis factor therapy in rheumatoid arthritis

INTRODUCTION

Anti-TNF therapies have revolutionized the treatment of rheumatoid arthritis (RA), a common systemic autoimmune disease involving destruction of the synovial joints. However, in the practice of rheumatology approximately one-third of patients demonstrate no clinical improvement in response to treatment with anti-TNF therapies, while another third demonstrate a partial response, and one-third an excellent and sustained response. Since no clinical or laboratory tests are available to predict response to anti-TNF therapies, great need exists for predictive biomarkers.

METHODS

Here we present a multi-step proteomics approach using arthritis antigen arrays, a multiplex cytokine assay, and conventional ELISA, with the objective to identify a biomarker signature in three ethnically diverse cohorts of RA patients treated with the anti-TNF therapy etanercept.

RESULTS

We identified a 24-biomarker signature that enabled prediction of a positive clinical response to etanercept in all three cohorts (positive predictive values 58 to 72%; negative predictive values 63 to 78%).

CONCLUSIONS

We identified a multi-parameter protein biomarker that enables pretreatment classification and prediction of etanercept responders, and tested this biomarker using three independent cohorts of RA patients. Although further validation in prospective and larger cohorts is needed, our observations demonstrate that multiplex characterization of autoantibodies and cytokines provides clinical utility for predicting response to the anti-TNF therapy etanercept in RA patients.

Progression in early rheumatoid arthritis

Rheumatoid arthritis (RA) is a very heterogeneous disease, the outcome of which is difficult to predict. The vast majority of the patients will have disease progression with bone erosions and cartilage breakdown resulting in joint destruction, functional impairment, and increased mortality. The management of RA to prevent and control disease progression has changed considerably in the past few years. The treatment goal should now be to achieve clinical remission in order to prevent structural damage and long-term disability. A very early use of effective disease-modifying anti-rheumatic drugs (DMARDs) is a key point in patients at risk of developing persistent and erosive arthritis. Intensive treatment such as combination DMARDs plus steroids or mainly biological therapies can induce high rates of remission and control of radiological progression, and can provide better outcomes than DMARD monotherapy in early RA, and should be considered very early in at-risk patients. In addition, close monitoring of disease activity and radiographic progression is mandatory in order to adapt DMARD therapy and strategy if necessary.

Developments in the clinical understanding of rheumatoid arthritis

The changes occurring in the field of rheumatoid arthritis (RA) over the past decade or two have encompassed new therapies and, in particular, a new look at the clinical characteristics of the disease in the context of therapeutic improvements. It has been shown that composite disease activity indices have special merits in following patients, that disease activity governs the evolution of joint damage, and that disability can be dissected into several components--among them disease activity and joint damage. It has also been revealed that aiming at any disease activity state other than remission (or, at worst, low disease activity) is associated with significant progression of joint destruction, that early recognition and appropriate therapy of RA are important facets of the overall strategy of optimal clinical control of the disease, and that tight control employing composite scores supports the optimization of the therapeutic approaches. Finally, with the advent of novel therapies, remission has become a reality and the treatment algorithms encompassing all of the above-mentioned aspects will allow us to achieve the rigorous aspirations of today and tomorrow.

Six and 12 Weeks Treatment Response Predicts Continuation of Tumor Necrosis Factor Blockade in Rheumatoid Arthritis: An Observational Cohort Study from Southern Sweden

Objective.

To investigate if treatment response predicts continuation of anti-tumor necrosis factor (TNF) treatment in patients with rheumatoid arthritis (RA).

Methods.

We investigated if treatment response and/or achieving a certain activity state at 6 weeks or 3 months predicts continuation of treatment in an observational cohort of 1789 anti-TNF-naive patients with established RA disease from southern Sweden.

Results.

Response to treatment at 6 weeks at overall/American College of Rheumatology (ACR20) or good/major level (except ACR70) significantly predicted drug continuation. Response according to all criteria sets at overall/ACR20 and at good/major/ACR70 level predicted drug continuation at 3 months, as did achieving low disease activity at 3 months irrespective of activity index applied. Remaining in a high disease activity state predicted drug discontinuation at both timepoints and according to all criteria sets.

Conclusion.

Response criteria may be useful aids in deciding on continuation of TNF blockade in RA as early as after 6 weeks of treatment. The various criteria sets perform similarly.