ReviewBiomarkers for prediction of TNFα blockers response in rheumatoid arthritis
Introduction
Rheumatoid arthritis (RA) is a chronic inflammatory disease, which predominantly involves synovial tissues and affects roughly 0.5% of the French population. The last 10 years have led us to recognize tumor necrosis factor alpha (TNFα) as one of the key cytokines involved in the pathogenesis of RA. Such results have provided the basis for the development of TNFα blockers for treating RA when methotrexate fails. Currently, three TNFα blockers are available in clinical practice: infliximab (a chimeric monoclonal antibody), adalimumab (a human monoclonal antibody), and etanercept (a fusion protein consisting of a dimer of the extracellular portion of p75 TNFα receptor linked to the Fc portion of human IgG1). Etanercept is also able to bind to lymphotoxin α (LTA). Roughly all TNFα blockers are efficient in two-thirds of patients, but this means that one-third of patients fail to respond to TNFα blocker therapy. In addition to the clinical effect, it was observed that TNFα blockers prevent joint [1] and bone destruction [2]. Despite their efficiency, the use of TNFα blockers exposes patients to some risks (infectious, neoplastic, allergic, etc.) that seem disproportional, especially if the patient might not respond to the therapy. Therefore, identifying biomarkers that predict responses to TNFα blockers are crucial for optimizing patient selection and increasing the balance between benefit and risk. This personalized form of medicine will also become increasingly advantageous as the number of available drugs grows. In addition, this prediction is also an economic issue at this time where costs need to be reduced.
As the prediction of response to TNFα blockers is a key issue, extensive biomarker analysis was performed using several complex methods to identify one or more biomarkers, which should be then easy to assess in the daily practice. Here we will review these studies performed to predict the response to TNFα blockers in RA. We will order this review according the following markers: demographic, clinical and radiological parameters; blood biomarkers; genetic markers and synovial markers.
Section snippets
Demographic, clinical and radiological predictive factors
Disease duration, age of onset, baseline DAS28, presence of rheumatoid nodules, and the baseline number of radiographic erosions failed to correlate with TNFα blocker response in RA [3], [4]. Only high disease activity, functional ability or smoking status were found to predict TNFα blocker response [5], [6]. However, results for functional ability are contradictory [5], [6]. Despite some controversial results, these results would suggest that severe arthritis is less susceptible to TNFα
Usual biologic parameters
Most of the usual laboratory parameters investigated failed to predict clinical response. The available set of biological parameters commonly used for RA diagnosis or prognosis (such as baseline C-reactive protein [CRP], rheumatoid factor [RF] and anticyclic citrullinated peptide [anti-CCP]) were assessed with heterogeneous results. For some studies, these biomarkers failed to predict a response to TNFα blockers [3], [4], [5], [7], [8]. Few studies found that, the presence of RF, high level of
HLA-DRB1 and the shared epitope
HLA-DRB1 is localized on this area and some HLA-DRB1 alleles encode a common structural element designated as the shared epitope (SE), which is strongly associated with susceptibility and severity of RA patients [31], [32]. Only one study found an association between two copies of the SE and a good clinical response to etanercept [33], whereas many other studies failed to replicate these results in several RA populations [11], [31], [34], [35], [36], [37], [38] (Table 4). Clearly, the SE is not
Synovial biopsy
The synovial approach is stressed in the perspective that RA is not a systemic disease. The inflammatory mechanisms targeted by TNFα blockers are located in the synovium and gene expression profiles of RA circulating blood may not be representative of these synovial tissue-specific pathways. This approach is usually justified by its ability to discriminate RA from other joint disorders [53], and the power to observe some changes in the number of macrophages under therapy. Synovial samples were
Conclusion
Since RA patients show large heterogeneity in their response to TNFα blockers, prediction of response remains an essential challenge. Since response prediction to TNFα blockers is a multifactorial event, which requires a multiparameter biomarker, the research focus is multidisciplinary, including clinometric, cytometric, metabolic, genomic, and proteomic biomarkers.
However, results from studies on this topic are heterogeneous. This heterogeneity of the results is also related to a variety of
Conflict of interest statement
None of the authors has any conflicts of interest to declare.
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Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in rheumatoid arthritis
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