Protein biochip array technology for cytokine profiling predicts etanercept responsiveness in rheumatoid arthritis

Towards Personalized Medicine in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, incurable, multisystem, inflammatory disease characterized by synovitis and extra-articular features. Although several advanced therapies targeting inflammatory mechanisms underlying the disease are available, no advanced therapy is universally effective. Therefore, a ceiling of treatment response is currently accepted where no advanced therapy is superior to another. The current challenge for medical research is the discovery and integration of predictive markers of drug response that can be used to personalize medicine so that the patient is started on "the right drug at the right time". This review article summarizes our current understanding of predicting response to anti-rheumatic drugs in RA, obstacles impeding the development of personalized medicine approaches and future research priorities to overcome these barriers.

A proteomics study of rheumatoid arthritis patients on etanercept identifies putative biomarkers associated with clinical outcome measures

OBJECTIVES

Biologic DMARDs (bDMARDs) are widely used in patients with RA, but response to bDMARDs is heterogeneous. The objective of this work was to identify pretreatment proteomic biomarkers associated with RA clinical outcome measures in patients starting bDMARDs.

METHODS

Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to generate spectral maps of sera from patients with RA before and after 3 months of treatment with the bDMARD etanercept. Protein levels were regressed against RA clinical outcome measures, i.e. 28-joint DAS (DAS28) and its subcomponents and DAS28 <2.6 (i.e. remission). The proteins with the strongest evidence for association were analysed in an independent, replication dataset. Finally, subnetwork analysis was carried out using the Disease Module Detection algorithm and biological plausibility of identified proteins was assessed by enrichment analysis.

RESULTS

A total of 180 patients with RA were included in the discovery dataset and 58 in the validation dataset from a UK-based prospective multicentre study. Ten individual proteins were found to be significantly associated with RA clinical outcome measures. The association of T-complex protein 1 subunit η with DAS28 remission was replicated in an independent cohort. Subnetwork analysis of the 10 proteins from the regression analysis identified the ontological theme, with the strongest associations being with acute phase and acute inflammatory responses.

CONCLUSION

This longitudinal study of 180 patients with RA commencing etanercept has identified several putative protein biomarkers of treatment response to this drug, one of which was replicated in an independent cohort.

Tailored therapeutic decision of rheumatoid arthritis using proteomic strategies: how to start and when to stop?

Unpredictable treatment responses have been an obstacle for the successful management of rheumatoid arthritis. Although numerous serum proteins have been proposed, there is a lack of integrative survey to compare their relevance in predicting treatment outcomes in rheumatoid arthritis. Also, little is known about their applications in various treatment stages, such as dose modification, drug switching or withdrawal. Here we present an in-depth exploration of the potential usefulness of serum proteins in clinical decision-making and unveil the spectrum of immunopathology underlying responders to different drugs. Patients with robust autoimmunity and inflammation are more responsive to biological treatments and prone to relapse during treatment de-escalation. Moreover, the concentration changes of serum proteins at the beginning of the treatments possibly assist early recognition of treatment responders. With a better understanding of the relationship between the serum proteome and treatment responses, personalized medicine in rheumatoid arthritis will be more achievable in the near future.

Gene Ontology Analysis Highlights Biological Processes Influencing Non-Response to Anti-TNF Therapy in Rheumatoid Arthritis

Anti-TNF therapy has significantly improved disease control in rheumatoid arthritis, but a fraction of rheumatoid arthritis patients do not respond to anti-TNF therapy or lose response over time. Moreover, the mechanisms underlying non-response to anti-TNF therapy remain largely unknown. To date, many single biomarkers of response to anti-TNF therapy have been published but they have not yet been analyzed as a system of interacting nodes. The aim of our study is to systematically elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis using the gene ontologies of previously published predictive biomarkers. Gene networks were constructed based on published biomarkers and then enriched gene ontology terms were elucidated in subgroups using gene ontology software tools. Our results highlight the novel role of proteasome-mediated protein catabolic processes (p = 2.91 × 10⁻¹⁵) and plasma lipoproteins (p = 4.55 × 10⁻¹¹) in anti-TNF therapy response. The results of our gene ontology analysis help elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis and encourage further study of the highlighted processes.

TNF-α Inhibitors in Combination with MTX Reduce Circulating Levels of Heparan Sulfate/Heparin and Endothelial Dysfunction Biomarkers (sVCAM-1, MCP-1, MMP-9 and ADMA) in Women with Rheumatoid Arthritis

Sulfated glycosaminoglycans (sGAGs) are likely to play an important role in the development and progression of rheumatoid arthritis (RA)-associated atherosclerosis. The present study investigated the effect of anti-tumor necrosis factor-α (anti-TNF-α) therapy in combination with methotrexate on plasma sGAG levels and serum markers of endothelial dysfunction. Among sGAG types, plasma chondroitin/dermatan sulfate (CS/DS) and heparan sulfate/heparin (HS/H) were characterized using electrophoretic fractionation. Serum levels of soluble vascular cell adhesion molecule-1 (sVCAM-1), monocyte chemoattractant protein-1 (MCP-1), matrix metalloproteinase-9 (MMP-9) and asymmetric dimethylarginine (ADMA) were measured by immunoassays. The measurements were carried out four times: at baseline and after 3, 9 and 15 months of anti-TNF-α therapy. All analyzed parameters, excluding ADMA, were significantly elevated in patients with RA before the implementation of biological therapy compared to healthy subjects. Performed anti-TNF-α treatment led to a successive decrease in HS/H levels toward normal values, without any effect on CS/DS levels in female RA patients. The treatment was also effective at lowering the serum levels of sVCAM-1, MCP-1, MMP-9 and ADMA. Moreover, a significant positive correlation was found between the circulating HS/H and the 28 joint disease activity score based on the erythrocyte sedimentation rate (DAS28-ESR, r = 0.408; p <0.05), MCP-1 (r = 0.398; p <0.05) and ADMA (r = 0.396; p <0.05) in patients before the first dose of TNF-α inhibitor. In conclusion, a beneficial effect of anti-TNF-α therapy on cell-surface heparan sulfate proteoglycans (HSPGs)/HS turnover and endothelial dysfunction was observed in this study. This was manifested by a decrease in blood HS/H levels and markers of endothelial activation, respectively. Moreover, the decrease in the concentration of HS/H in the blood of patients during treatment, progressing with the decline in disease activity, indicates that the plasma HS/H profile may be useful for monitoring the efficacy of anti-TNF-α treatment in patients with RA.

Validation in the ESPOIR cohort of vitamin K-dependent protein S (PROS) as a potential biomarker capable of predicting response to the methotrexate/etanercept combination

Background

To validate the ability of PROS (vitamin K-dependent protein S) and CO7 (complement component C7) to predict response to the methotrexate (MTX)/etanercept (ETA) combination in rheumatoid arthritis (RA) patients who received this therapeutic combination in a well-documented cohort.

Method

From the ESPOIR cohort, RA patients having received the MTX/ETA or MTX/adalimumab (ADA) combination as a first-line biologic treatment were included. Serum concentrations of PROS and CO7 were measured by ELISA prior to the initiation of ETA or ADA, at a time where the disease was active (DAS28 ESR > 3.2). The clinical efficacy (response/non-response) of both combinations has been evaluated after at least 6 months of treatment, according to the EULAR response criteria with some modifications.

Results

Thirty-two were treated by MTX/ETA; the numbers of responders and non-responders were 24 and 8, respectively. Thirty-three patients received the MTX/ADA combination; 27 and 5 patients were respectively responders and non-responders. While there were no differences for demographic, clinical, biological, and X-rays data, as well as for CO7, serum levels of PROS tended to be significantly higher in responders to the MTX/ETA combination (p = 0.08) while no difference was observed in the group receiving MTX/ADA. For PROS, the best concentration threshold to differentiate both groups was calculated at 40 μg/ml using ROC curve. The theranostic performances of PROS appeared better for the ETA/MTX combination. When considering the response to this combination, analysis of pooled data from ESPOIR and SATRAPE (initially used to validate PROS and CO7 as potential theranostic biomarkers) cohorts led to a higher theranostic value of PROS that became significant (p = 0.009).

Conclusion

PROS might be one candidate of a combination of biomarkers capable of predicting the response to MTX/ETA combination in RA patients refractory to MTX.

Trial registration

ClinicalTrials.gov identifiers: NCT03666091 and NCT00234234.

Ultra-Low Dose Cytokines in Rheumatoid Arthritis, Three Birds with One Stone as the Rationale of the 2LARTH® Micro-Immunotherapy Treatment

Tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) are two cytokines involved in the perpetuation of the chronic inflammation state characterizing rheumatoid arthritis (RA). Significant advances in the treatment of this pathology have been made over the past ten years, partially through the development of anti-TNF and anti-IL-1 therapies. However, major side effects still persist and new alternative therapies should be considered. The formulation of the micro-immunotherapy medicine (MIM) 2LARTH^® uses ultra-low doses (ULD) of TNF-α, IL-1β, and IL-2, in association with other immune factors, to gently restore the body’s homeostasis. The first part of this review aims at delineating the pivotal roles played by IL-1β and TNF-α in RA physiopathology, leading to the development of anti-TNF and anti-IL-1 therapeutic agents. In a second part, an emphasis will be made on explaining the rationale of using multiple therapeutic targets, including both IL-1β and TNF-α in 2LARTH^® medicine. Particular attention will be paid to the ULD of those two main pro-inflammatory factors in order to counteract their overexpression through the lens of their molecular implication in RA pathogenesis.

Protein array-based companion diagnostics in precision medicine

INTRODUCTION

The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities.

AREA COVERED

This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests.

EXPERT OPINION

Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.

Increased monocyte chemoattractant protein-1 and nitrotyrosine are associated with increased body weight in patients with rheumatoid arthritis after etanercept therapy

OBJECTIVES

Etanercept, a tumor necrosis factor inhibitor, is an effective drug for patients with active rheumatoid arthritis (RA). Monocyte chemoattractant protein-1 (MCP-1) and nitrotyrosine (NT) are pro-inflammatory biomolecules associated with satiety and increased body weight. We evaluated whether MCP-1 and NT are associated with decreased inflammation or increased body mass during etanercept therapy in active RA patients.

METHODS

RA patients with moderate to high disease activity were enrolled to receive add-on etanercept (25 mg subcutaneous injection, biweekly) for at least one year, combined with sustained treatment with conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs).

RESULTS

Forty patients received add-on etanercept and 15 received DMARDs alone. At the end of one year, etanercept significantly reduced the disease activity score of 28 joints, C-reactive protein, and erythrocyte sedimentation rate. Moreover, etanercept significantly increased the body weight, body mass index (BMI), as well as MCP-1 and NT levels, compared to that in the csDMARD-only group.

CONCLUSIONS

Increased serum MCP-1 and NT levels in RA patients with moderate to high disease activity, who underwent one-year etanercept treatment, might be attributed to increase in body weight and BMI rather than induction of more severe autoimmune inflammation.

Contribution of Multiplex Immunoassays to Rheumatoid Arthritis Management: From Biomarker Discovery to Personalized Medicine

Rheumatoid arthritis (RA) is a multifactorial, inflammatory and progressive autoimmune disease that affects approximately 1% of the population worldwide. RA primarily involves the joints and causes local inflammation and cartilage destruction. Immediate and effective therapies are crucial to control inflammation and prevent deterioration, functional disability and unfavourable progression in RA patients. Thus, early diagnosis is critical to prevent joint damage and physical disability, increasing the chance of achieving remission. A large number of biomarkers have been investigated in RA, although only a few have made it through the discovery and validation phases and reached the clinic. The single biomarker approach mostly used in clinical laboratories is not sufficiently accurate due to its low sensitivity and specificity. Multiplex immunoassays could provide a more complete picture of the disease and the pathways involved. In this review, we discuss the latest proposed protein biomarkers and the advantages of using protein panels for the clinical management of RA. Simultaneous analysis of multiple proteins could yield biomarker signatures of RA subtypes to enable patients to benefit from personalized medicine.

Multiple biomarker approach for the diagnosis and therapy of rheumatoid arthritis

The lack of specific clinical symptoms for patients in the early stage of rheumatoid arthritis (RA) has created strong interest in the laboratory diagnosis of RA. The main laboratory markers of RA, rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPAs), can be found in patients with other pathologies and in healthy donors. Even today, there is no single laboratory test that can diagnosis RA with high sensitivity and specificity. To improve the diagnosis and treatment of RA, alternative biomarkers, including 14-3-3η protein, connective tissue growth factor (CTGF), antibodies against PAD4, antibodies against BRAF, and anti-acetylated and anti-carbamylated protein antibodies have been studied extensively. The use of a multiple biomarker approach, the simultaneous measurement of a set of biomarkers, is an alternative strategy for the diagnosis of RA and for predicting the therapeutic effect of biological disease-modifying antirheumatic drugs (DMARDs). However, despite the large number of studies, only a few biomarker combinations have been validated and can be applied in clinical practice. In this article, results of studies focused on the multiple biomarker approach (both multiplex and combined single-analyte assays) to diagnose RA and to predict response to biological drug therapy are reviewed. Additionally, general factors limiting the use of multiplex analysis in RA diagnostics and therapy are discussed.

Anti-TNF Therapy in Spondyloarthritis and Related Diseases, Impact on the Immune System and Prediction of Treatment Responses

Immune-mediated inflammatory diseases (IMIDs), such as spondyloarthritis (SpA), psoriasis, Crohn's disease (CD), and rheumatoid arthritis (RA) remain challenging illnesses. They often strike at a young age and cause lifelong morbidity, representing a considerable burden for the affected individuals and society. Pioneering studies have revealed the presence of a TNF-dependent proinflammatory cytokine cascade in several IMIDs, and the introduction of anti-TNF therapy 20 years ago has proven effective to reduce inflammation and clinical symptoms in RA, SpA, and other IMID, providing unprecedented clinical benefits and a valid alternative in case of failure or intolerable adverse effects of conventional disease-modifying antirheumatic drugs (DMARDs, for RA) or non-steroidal anti-inflammatory drugs (NSAIDs, for SpA). However, our understanding of how TNF inhibitors (TNFi) affect the immune system in patients is limited. This question is relevant because anti-TNF therapy has been associated with infectious complications. Furthermore, clinical efficacy of TNFi is limited by a high rate of non-responsiveness (30–40%) in RA, SpA, and other IMID, exposing a substantial fraction of patients to side-effects without clinical benefit. Despite the extensive use of TNFi, it is still not possible to determine which patients will respond to TNFi before treatment initiation. The recent introduction of antibodies blocking IL-17 has expanded the therapeutic options for SpA, as well as psoriasis and psoriatic arthritis. It is therefore essential to develop tools to guide treatment decisions for patients affected by SpA and other IMID, both to optimize clinical care and contain health care costs. After a brief overview of the biology of TNF, its receptors and currently used TNFi in the clinics, we summarize the progress that has been made to increase our understanding of the action of TNFi on the immune system in patients. We then summarize efforts dedicated to identify biomarkers that can predict treatment responses to TNFi and we conclude with a section dedicated to the recently introduced inhibitors of IL-17A and IL-23 in SpA and related diseases. The focus of this review is on SpA, however, we also refer to RA on topics for which only limited information is available on SpA in the literature.

MicroRNA-132, miR-146a, and miR-155 as potential biomarkers of methotrexate response in patients with rheumatoid arthritis

INTRODUCTION

Rheumatoid arthritis (RA) patients have high expression levels of hsa-miR-132-3p, hsa-miR-146a-5p, and hsa-miR-155-5p in peripheral blood. We studied if baseline blood levels of these microRNAs (miRNAs) could predict response to methotrexate (MTX).

METHODS

RA patients (the American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria) with active disease (disease-modifying anti-rheumatic drug (DMARD)-naïve and Disease Activity Score 28 (DAS28) > 3.2) were enrolled. They were treated with MTX by gradually increasing dose up to 25 mg/week. After 4 months, the DAS28 score was calculated and EULAR response was assessed. The hsa-miR-132-3p, hsa-miR-146a-5p, and hsa-miR-155-5p levels were measured by real-time qPCR in whole-blood RNA at baseline and 4 months after therapy, using hsa-let-7a-5p as housekeeping gene. Results are expressed as median (interquartile range).

RESULTS

The 94 enrolled patients (81 females) had a median age of 40 (17) years, disease duration of (24) months, and DAS28 4.61 (1.11). After 4 months of therapy, 73 were classified as responders and 21 as non-responders. Baseline levels of all three miRNAs were lower in responders than non-responders, hsa-miR-132-3p (- 8.03 (0.70) versus - 7.47 (0.85), P < 0.05), hsa-miR-146a-5p (- 5.11 (0.88) versus - 4.62 (0.90), P < 0.05), and hsa-miR-155-5p (- 7.59 (1.07) versus - 7 (0.72), P = 0.002). Receiver operating characteristic curve analysis showed that all three miRNAs were also good predictors of MTX response, showing the following values: hsa-miR-132-3p (area under curve (AUC) 0.756, P < 0.05), hsa-miR-146a-5p (AUC 0.760, P < 0.05), and hsa-miR-155-5p (AUC 0.728, P = 0.002).

CONCLUSION

hsa-miR-132-3p, hsa-miR-146a-5p, and hsa-miR-155-5p are potential biomarkers of responsiveness to MTX therapy.

Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in rheumatoid arthritis

OBJECTIVES

Tumour necrosis factor-alpha inhibitors (TNFi) are effective treatments for Rheumatoid Arthritis (RA). Responses to treatment are barely predictable. As these treatments are costly and may induce a number of side effects, we aimed at identifying a panel of protein biomarkers that could be used to predict clinical response to TNFi for RA patients.

METHODS

Baseline blood levels of C-reactive protein, platelet factor 4, apolipoprotein A1, prealbumin, α1-antitrypsin, haptoglobin, S100A8/A9 and S100A12 proteins in bDMARD naive patients at the time of TNFi treatment initiation were assessed in a multicentric prospective French cohort. Patients fulfilling good EULAR response at 6 months were considered as responders. Logistic regression was used to determine best biomarker set that could predict good clinical response to TNFi.

RESULTS

A combination of biomarkers (prealbumin, platelet factor 4 and S100A12) was identified and could predict response to TNFi in RA with sensitivity of 78%, specificity of 77%, positive predictive values (PPV) of 72%, negative predictive values (NPV) of 82%, positive likelihood ratio (LR+) of 3.35 and negative likelihood ratio (LR-) of 0.28. Lower levels of prealbumin and S100A12 and higher level of platelet factor 4 than the determined cutoff at baseline in RA patients are good predictors for response to TNFi treatment globally as well as to Infliximab, Etanercept and Adalimumab individually.

CONCLUSION

A multivariate model combining 3 biomarkers (prealbumin, platelet factor 4 and S100A12) accurately predicted response of RA patients to TNFi and has potential in a daily practice personalized treatment.

Right drug, right patient, right time: aspiration or future promise for biologics in rheumatoid arthritis?

Individualising biologic disease-modifying anti-rheumatic drugs (bDMARDs) to maximise outcomes and deliver safe and cost-effective care is a key goal in the management of rheumatoid arthritis (RA). Investigation to identify predictive tools of bDMARD response is a highly active and prolific area of research. In addition to clinical phenotyping, cellular and molecular characterisation of synovial tissue and blood in patients with RA, using different technologies, can facilitate predictive testing. This narrative review will summarise the literature for the available bDMARD classes and focus on where progress has been made. We will also look ahead and consider the increasing use of ‘omics’ technologies, the potential they hold as well as the challenges, and what is needed in the future to fully realise our ambition of personalised bDMARD treatment.

Response to Treatment with TNFα Inhibitors in Rheumatoid Arthritis Is Associated with High Levels of GM-CSF and GM-CSF+ T Lymphocytes

Biologic TNFα inhibitors are a mainstay treatment option for patients with rheumatoid arthritis (RA) refractory to other treatment options. However, many patients either do not respond or relapse after initially responding to these agents. This study was carried out to identify biomarkers that can distinguish responder from non-responder patients before the initiation of treatment. The level of cytokines in plasma and those produced by ex vivo T cells, B cells and monocytes in 97 RA patients treated with biologic TNFα inhibitors was measured before treatment and after 1 and 3 months of treatment by multiplex analyses. The frequency of T cell subsets and intracellular cytokines were determined by flow cytometry. The results reveal that pre-treatment, T cells from patients who went on to respond to treatment with biologic anti-TNFα agents produced significantly more GM-CSF than non-responder patients. Furthermore, immune cells from responder patients produced higher levels of IL-1β, TNFα and IL-6. Cytokine profiling in the blood of patients confirmed the association between high levels of GM-CSF and responsiveness to biologic anti-TNFα agents. Thus, high blood levels of GM-CSF pre-treatment had a positive predictive value of 87.5% (61.6 to 98.5% at 95% CI) in treated RA patients. The study also shows that cells from most anti-TNFα responder patients in the current cohort produced higher levels of GM-CSF and TNFα pre-treatment than non-responder patients. Findings from the current study and our previous observations that non-responsiveness to anti-TNFα is associated with high IL-17 levels suggest that the disease in responder and non-responder RA patients is likely to be driven/sustained by different inflammatory pathways. The use of biomarker signatures of distinct pro-inflammatory pathways could lead to evidence-based prescription of the most appropriate biological therapies for different RA patients.

Proteomics to predict the response to tumour necrosis factor-α inhibitors in rheumatoid arthritis using a supervised cluster-analysis based protein score

OBJECTIVE

In rheumatoid arthritis (RA), it is of major importance to identify non-responders to tumour necrosis factor-α inhibitors (TNFi) before starting treatment, to prevent a delay in effective treatment. We developed a protein score for the response to TNFi treatment in RA and investigated its predictive value.

METHOD

In RA patients eligible for biological treatment included in the BiOCURA registry, 53 inflammatory proteins were measured using xMAP® technology. A supervised cluster analysis method, partial least squares (PLS), was used to select the best combination of proteins. Using logistic regression, a predictive model containing readily available clinical parameters was developed and the potential of this model with and without the protein score to predict European League Against Rheumatism (EULAR) response was assessed using the area under the receiving operating characteristics curve (AUC-ROC) and the net reclassification index (NRI).

RESULTS

For the development step (n = 65 patient), PLS revealed 12 important proteins: CCL3 (macrophage inflammatory protein, MIP1a), CCL17 (thymus and activation-regulated chemokine), CCL19 (MIP3b), CCL22 (macrophage-derived chemokine), interleukin-4 (IL-4), IL-6, IL-7, IL-15, soluble cluster of differentiation 14 (sCD14), sCD74 (macrophage migration inhibitory factor), soluble IL-1 receptor I, and soluble tumour necrosis factor receptor II. The protein score scarcely improved the AUC-ROC (0.72 to 0.77) and the ability to improve classification and reclassification (NRI = 0.05). In validation (n = 185), the model including protein score did not improve the AUC-ROC (0.71 to 0.67) or the reclassification (NRI = -0.11).

CONCLUSION

No proteomic predictors were identified that were more suitable than clinical parameters in distinguishing TNFi non-responders from responders before the start of treatment. As the results of previous studies and this study are disparate, we currently have no proteomic predictors for the response to TNFi.

Application of omics in predicting anti-TNF efficacy in rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by progressive joint erosion. Tumor necrosis factor (TNF) antagonists are the most widely used biological disease-modifying anti-rheumatic drug in RA. However, there continue to be one third of RA patients who have poor or no response to TNF antagonists. Following consideration of the uncertainty of therapeutic effects and the high price of TNF antagonists, it is worthy to predict the treatment responses before anti-TNF therapy. According to the comparisons between the responders and non-responders to TNF antagonists by omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, rheumatologists are eager to find significant biomarkers to predict the effect of TNF antagonists in order to optimize the personalized treatment in RA.

Defining the proteomic landscape of rheumatoid arthritis: progress and prospective clinical applications

INTRODUCTION

The heterogeneity of Rheumatoid Arthritis (RA) and the absence of clinical tests accurate enough to identify the early stages of this disease have hampered its management. Therefore, proteomics research is increasingly focused on the discovery of novel biological markers, which would not only be able make an early diagnosis, but also to gain insight into the different pathological mechanisms underlying the heterogeneity of RA and also to stratify patients, which is critical to enabling effective treatments. Areas covered: The proteomic approaches that have been utilised to provide knowledge about RA pathogenesis, and to identify biomarkers for RA diagnosis, prognosis, disease monitoring and prediction of response to therapy, are summarized. Expert commentary: Although each proteomic study is unique in its design, all of them have contributed to the understanding of RA pathogenesis and the discovery of promising biomarkers for patient stratification, which would improve clinical care of RA patients. Still, efforts need to be made to validate these findings and translate them into clinical practice.

A Multi-Biomarker Disease Activity Score and the Choice of Second-Line Therapy in Early Rheumatoid Arthritis After Methotrexate Failure

Objective

To investigate whether the Multi‐Biomarker Disease Activity (MBDA) score predicts optimal add‐on treatment in patients with early rheumatoid arthritis (RA) who were inadequate responders to MTX (MTX‐IRs).

Methods

We analyzed data from 157 MTX‐IRs (with a Disease Activity Score using the erythrocyte sedimentation rate [DAS28‐ESR] >3.2) from the Swedish Pharmacotherapy (SWEFOT) trial who were randomized to receive triple therapy (MTX plus sulfasalazine plus hydroxychloroquine) versus MTX plus infliximab. The MBDA score as a predictor of the subsequent DAS28‐based response to each second‐line treatment was analyzed at randomization with the Breslow‐Day test for 2 × 2 groups, using both validated categories (low [<30], moderate [30–44], and high [>44]) and dichotomized categories (lower [≤38] versus higher [>38]).

Results

Among the 157 patients, 12% had a low MBDA score, 32% moderate, and 56% high. Of those with a low MBDA score, 88% responded to subsequent triple therapy, and 18% responded to MTX plus infliximab (P = 0.006); for those with a high MBDA score, the response rates were 35% and 58%, respectively (P = 0.040). When using 38 as a cutoff for the MBDA score (29% patients with lower scores versus 71% with higher scores), the differential associations with response to triple therapy versus MTX plus infliximab were 79% versus 44% and 36% versus 58%, respectively (P = 0.001). Clinical and inflammatory markers had poorer predictive capacity for response to triple therapy or MTX plus infliximab.

Conclusion

In patients with RA who had an inadequate response to MTX, the MBDA score categories were differentially associated with response to subsequent therapies. Thus, patients with post‐MTX biochemical improvements (lower MBDA scores) were more likely to respond to triple therapy than to MTX plus infliximab. If confirmed, these results may help to improve treatment in RA.

Identification of 7 Proteins in Sera of RA Patients with Potential to Predict ETA/MTX Treatment Response

Objective: The recent growth of innovating biologics has opened fascinating avenues for the management of patients. In rheumatoid arthritis, many biologics are currently available, the choice of which being mostly determined empirically. Importantly, a given biologic may not be active in a fraction of patients and may even provoke side effects. Here, we conducted a comparative proteomics study in attempt to identify a predictive theranostic signature of non-response in patients with rheumatoid arthritis treated by etanercept/methotrexate combination.

Methods: A serum sample was collected prior to treatment exposure from a cohort of 22 patients with active RA. A proteomic “label free” approach was then designed to quantitate protein biomarkers using mass spectrometry. To verify these results, a relative quantification followed by an absolute quantification of interesting protein candidates were performed on a second cohort. The criterion of judgment was the response to etanercept/methotrexate combination according to the EULAR criteria assessed at 6 months of treatment.

Results: These investigations led to the identification of a set of 12 biomarkers with capacity to predict treatment response. A targeted quantitative analysis allowed to confirm the potential of 7 proteins from the latter combination on a new cohort of 16 patients. Two highly discriminating proteins, PROS and CO7, were further evaluated by ELISA on this second cohort. By combining the concentration threshold of each protein associated to a right classification (responders vs non-responders), the sensitivity and specificity reached 88.9 % and 100 %, respectively.

Conclusion: Prior to methotrexate/etanercept treatment, abundance of several sera proteins, notably PROS and CO7, were associated to response status of RA patients 6 month after treatment initiation.

Infliximab and etanercept have distinct actions but similar effects on cytokine profiles in rheumatoid arthritis

OBJECTIVE

Pro-inflammatory cytokines, especially TNFα, play a central role in the pathogenesis of rheumatoid arthritis (RA). The available TNF inhibitors are only slightly different from one another in terms of clinical efficacy, at least at the group level, but their structures and modes of action are not identical. Infliximab (IFX) and etanercept (ETN) differ in their ability to induce antibody-dependent cellular cytotoxicity and complement-dependent cytotoxicity, and in their ability to bind TNFβ. The purpose of our study was to elucidate the different cytokine pathways through which these two drugs enact their clinical efficacy.

METHODS

Serum from 44 RA patients treated with IFX and 24 patients treated with ETN was studied. All patients had been given these biologics at identical dosages and intervals for one year. The concentrations of 11 inflammatory cytokines and their receptors (IL-1β, IL-2, IL-6, IL-6R, IL-8, IL-10, IL-12, TNFα, TNFβ, IFNγ, and GM-CSF) were measured at weeks 0, 22, and 54 using a high-sensitivity electro-chemiluminescence assay. Cytokine profiles were analyzed along with clinical efficacy.

RESULTS

IL-6 was significantly decreased in the ETN+MTX and IFX+MTX groups, although not in the ETN-only group; this change was consistent with changes in disease activity. IFNγ was gradually increased only in the non-remission subgroup of the IFX group, and not at all in the ETN group. TNFβ increased after starting IFX regardless of clinical efficacy.

CONCLUSION

IL-6 inhibition is a pathway affected by both IFX and ETN. In addition, IFNγ increase is a distinctive feature of the inefficacy of IFX.

Circulating anti-citrullinated peptide antibodies, cytokines and genotype as biomarkers of response to disease-modifying antirheumatic drug therapy in early rheumatoid arthritis

Background

To measure circulating anti-citrullinated peptide antibodies (ACPA) and cytokines pre- and 6 months post-therapy as a strategy to predict and optimize responses to traditional disease-modifying antirheumatic drugs (DMARDs) in early RA, which is an unmet need in developing countries.

Patients and methods

A cohort of 140 predominantly (88.5 %) black female South African patients with early RA was treated with synthetic DMARDs, mostly methotrexate (MTX) alone, or in combination with low-dose oral corticosteroids (CS). Circulating ACPA and a panel of circulating cytokines/chemokines/growth factors were measured at baseline and after 6 months of therapy in relation to disease activity and Shared Epitope (SE).

Results

Following 6 months of therapy, the median simplified disease activity index (SDAI) declined from a baseline of 41.4 to 16.0 (p = 0.0001) for the entire cohort, which was paralleled by significant falls in median serum ACPA levels (516.6 vs. 255.7 units/ml, p = <0.0001) and several of the circulating cytokines (IL-4, IL-7, IL-8, G-CSF, VEGF; p < 0.0010 – p < 0.0001) which were most evident in the subgroup of patients treated with a combination of MTX and CS. Although biomarker concentrations decreased most notably in the low-disease activity group post-therapy, no significant correlations between these biomarkers and disease activity were observed, Baseline ACPA levels, but not SDAI or cytokines, were significantly higher in the subgroup of risk allele-positive patients (561.1 vs. 331.9 units/ml, p < 0.05), while no associations with ACPA and a smoking history were evident.

Conclusions

The use of DMARDs in RA is associated with significant decreases in ACPA and cytokines which did not correlate with changes in SDAI, precluding the utility of serial measurement of these biomarkers to monitor early responses to therapy, but may have prognostic value.

Electronic supplementary material

The online version of this article (doi:10.1186/s12891-015-0587-1) contains supplementary material, which is available to authorized users.

The number of circulating monocytes as biomarkers of the clinical response to methotrexate in untreated patients with rheumatoid arthritis

Background

The aim of this work was to analyze the number and distribution of circulating monocytes, and of their CD14^+highCD16⁻, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subset cells, in treatment-naive patients with rheumatoid arthritis (RA), and to determine their value in predicting the clinical response to methotrexate (MTX) treatment.

Methods

This prospective work investigated the number of circulating monocytes, and the numbers of CD14^+highCD16⁻, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subset cells, in 52 untreated patients with RA before MTX treatment, and at 3 and 6 months into treatment, using flow cytometry.

Results

The absolute number of circulating monocytes, and the numbers of CD14^+highCD16⁻, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subset cells, were significantly higher in MTX non-responders than in responders and healthy controls before starting and throughout treatment. Responders showed normal numbers of monocytes, and of their subset cells, over the study period. The pre-treatment absolute number of circulating monocytes, and the numbers of CD14^+highCD16⁻ and CD14^+highCD16⁺ subset cells, were found to be predictive of the clinical response to MTX, with a sensitivity and specificity of >70% and >88%, respectively.

Conclusions

Treatment-naive patients with RA showed an anomalous distribution of circulating monocyte subsets, and an anomalous number of cells in each subset. A higher pre-treatment number of circulating monocytes, and higher numbers of CD14^+highCD16⁻ and CD14^+highCD16⁺ subset cells, predict a reduced clinical response to MTX in untreated patients with RA.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-014-0375-y) contains supplementary material, which is available to authorized users.

Identification of S100A9 as biomarker of responsiveness to the methotrexate/etanercept combination in rheumatoid arthritis using a proteomic approach

OBJECTIVES

One way to optimize the drug prescription in rheumatoid arthritis (RA) is to identify predictive biomarkers of drug responsiveness. Here, we investigated the potential "theranostic" value of proteins of the S100 family by monitoring levels of both S100A8 and S100A9 in blood samples from RA patients.

DESIGN

For proteomic analysis, peripheral blood mononuclear cells (PBMC) and serum samples were collected in patients prior to initiation of the methotrexate/etanercept (MTX/ETA) combination. Firstly, relative mass spectrometry (MS) quantification focusing on S100A8 and S100A9 proteins was carried out from PBMCs samples to identify potential biomarkers. The same approach was also performed from serum samples from responder (R) and non responder (NR) patients. Finally, to confirm these results, an absolute quantification of S100A8, S100A9 proteins and calprotectin (heterodimer of S100A8/S100A9) was carried out on the serum samples using ELISA.

RESULTS

MS analyses revealed that both S100A8 and S100A9 proteins were significantly accumulated in PBMC from responders. In contrast to PBMC, only the S100A9 protein was significantly overexpressed in the serum of R patients. Absolute quantification by ELISA confirmed this result and pointed out a similar expression level of S100A8 protein and calprotectin in sera from both R and NR groups. Thus, the S100A9 protein revealed to be predictive of MTX/ETA responsiveness, contrarily to parameters of inflammation and auto-antibodies which did not allow significant discrimination.

CONCLUSION

This is the first report of an overexpression of S100A9 protein in both PBMCs and serum of patients with subsequent response to the MTX/ETA combination. This protein thus represents an interesting biomarker candidate of therapeutic response in RA.

Circulating miRNA-125b is a potential biomarker predicting response to rituximab in rheumatoid arthritis

Although biologic therapies have changed the course of rheumatoid arthritis (RA), today's major challenge remains to identify biomarkers to target treatments to selected patient groups. Circulating micro(mi)RNAs represent a novel class of molecular biomarkers whose expression is altered in RA. Our study aimed at quantifying miR-125b in blood and serum samples from RA patients, comparing healthy controls and patients with other forms of rheumatic diseases and arthritis, and evaluating its predictive value as biomarker for response to rituximab. Detectable levels of miR-125b were measured in total blood and serum samples and were significantly elevated in RA patients compared to osteoarthritic and healthy donors. The increase was however also found in patients with other forms of chronic inflammatory arthritis. Importantly, high serum levels of miR-125b at disease flare were associated with good clinical response to treatment with rituximab three months later (P = 0.002). This predictive value was not limited to RA as it was also found in patients with B lymphomas. Our results identify circulating miR-125b as a novel miRNA over expressed in RA and suggest that serum level of miR-125b is potential predictive biomarker of response to rituximab treatment.

Monocyte populations as markers of response to adalimumab plus MTX in rheumatoid arthritis

Introduction

The treatment of rheumatoid arthritis (RA) patients with anti-tumor necrosis factor alpha (TNFα) biological drugs has dramatically improved the prognosis of these patients. However, a third of the treated patients do not respond to this therapy. Thus, the search for biomarkers of clinical response to these agents is currently highly active. Our aim is to analyze the number and distribution of circulating monocytes, and of their CD14^+highCD16^-, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subsets in methotrexate (MTX) non-responder patients with RA, and to determine their value in predicting the clinical response to adalimumab plus MTX treatment.

Methods

This prospective work investigated the number of circulating monocytes, and of their CD14^+highCD16^-, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subsets, in 35 MTX non-responder patients with RA before and after three and six months of anti-TNFα treatment using multiparametric flow cytometry. The number of circulating monocytes in an age- and sex-matched healthy population was monitored as a control.

Results

Non-responder patients with RA show an increased number of monocytes and of their CD14^+highCD16^-, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subsets after three months of adalimumab plus MTX treatment that remained significantly increased at six months. In contrast, significant normalization of the numbers of circulating monocytes was found in responders at three months of adalimumab plus MTX treatment that lasts up to six months. CX3CR1 expression is increased in monocytes in non-responders. At three months of anti-TNFα treatment the number of circulating monocytes and their subsets was associated with at least 80% sensitivity, 84% specificity and an 86% positive predictive value (PPV) in terms of discriminating between eventual early responders and non-responders.

Conclusions

The absolute number of circulating monocytes and of their CD14^+highCD16^-, CD14^+highCD16⁺ and CD14^+lowCD16⁺ subsets at three months of adalimumab plus MTX treatment, have a predictive value (with high specificity and sensitivity) in terms of the clinical response after six months of anti-TNFα treatment in patients with RA.

Inhibition of epidermal growth factor receptor tyrosine kinase ameliorates collagen-induced arthritis

Rheumatoid arthritis (RA) is an autoimmune synovitis characterized by the formation of pannus and the destruction of cartilage and bone in the synovial joints. Although immune cells, which infiltrate the pannus and promote inflammation, play a prominent role in the pathogenesis of RA, other cell types also contribute. Proliferation of synovial fibroblasts, for example, underlies the formation of the pannus, while proliferation of endothelial cells results in neovascularization, which supports the growth of the pannus by supplying it with nutrients and oxygen. The synovial fibroblasts also promote inflammation in the synovium by producing cytokines and chemokines. Finally, osteoclasts cause the destruction of bone. In this study, we show that erlotinib, an inhibitor of the tyrosine kinase epidermal growth factor receptor (EGFR), reduces the severity of established collagen-induced arthritis, a mouse model of RA, and that it does so by targeting synovial fibroblasts, endothelial cells, and osteoclasts. Erlotinib-induced attenuation of autoimmune arthritis was associated with a reduction in number of osteoclasts and blood vessels, and erlotinib inhibited the formation of murine osteoclasts and the proliferation of human endothelial cells in vitro. Erlotinib also inhibited the proliferation and cytokine production of human synovial fibroblasts in vitro. Moreover, EGFR was highly expressed and activated in the synovium of mice with collagen-induced arthritis and patients with RA. Taken together, these findings suggest that EGFR plays a central role in the pathogenesis of RA and that EGFR inhibition may provide benefits in the treatment of RA.

[Pharmacological approaches in immuno-rhumatology]

Biologics have proven to be an effective treatment option for adults with rheumatoid arthritis but their use in clinical practice may be limited by concerns over severe side effects and cost. Pharmacology and development of biomarkers could help to optimize the use of biologics in clinical practice. Biomarkers are surrogate markers and include all diagnostic tests, imaging and technologies and any other objective measure of a person's health status and all pharmacodiagnostic tests. Several studies evaluated interest of biomarkers in RA patients treated with biologics: 1- to optimize doses and frequency of drug administration; 2- to predict response to treatment; 3- to predict tolerance of biologics; 4- to monitor patient who stopped treatment and are in remission, and predict new RA flare.

Toward standardized high-throughput serum diagnostics: multiplex-protein array identifies IL-8 and VEGF as serum markers for colon cancer

Development and progression of colon cancer may be related to cytokines. Cytokines with diagnostic value have been identified individually but have not been implemented into clinical praxis. Using a multiplex protein array, the authors explore a panel of cytokines simultaneously and compared its performance to carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9). Serum concentrations of 12 cytokines were simultaneously determined by multiplex biochip technology in 50 colon cancer patients and 50 healthy controls. Serum levels of interleukin-8 (IL-8) and CEA were significantly higher in cancer patients than in healthy controls. Areas under the receiver operating characteristic curves (AUCs) were largest for IL-8, followed by CEA, vascular endothelial growth factor (VEGF), and CA 19-9. Analyses regarding marker combinations showed an advantage over single marker performance for CEA, VEGF, and CA 19-9 but not for IL-8. Multiplex biochip array technology represents a practical tool in cytokine and cancer research when simultaneous determination of different biomarkers is of interest. The results suggest that the assessment of IL-8, CEA, VEGF, and possibly CA 19-9 serum levels could be useful for colon cancer screening with the potential of also detecting early stage tumors. Further validation studies using these and additional markers on a multiplex array format are encouraged.

Erroneous augmentation of multiplex assay measurements in patients with rheumatoid arthritis due to heterophilic binding by serum rheumatoid factor

OBJECTIVE

Serum rheumatoid factor (RF) and other heterophilic antibodies potentially interfere with antibody-based immunoassays by nonspecifically binding detection reagents. The purpose of this study was to assess whether these factors confound multiplex-based immunoassays, which are used with increasing frequency to measure cytokine and chemokine analytes in patients with rheumatoid arthritis (RA).

METHODS

We performed multiplex immunoassays using different platforms to measure analyte concentrations in RA patient samples. Samples were depleted of RF by column-based affinity absorption or were exposed to agents that block heterophilic binding activity.

RESULTS

In RA patients with high-titer RF, 69% of analytes demonstrated at least a 2-fold stronger multiplex signal in non-RF-depleted samples as compared to RF-depleted samples. This degree of erroneous signal amplification was less frequent in low-titer RF samples (17% of analytes; P < 0.0000001). Signal amplification by heterophilic antibodies was blocked effectively by HeteroBlock (≥ 150 μg/ml). In 35 RA patients, multiplex signals for 14 of 22 analytes were amplified erroneously in unblocked samples as compared to blocked samples (some >100-fold), but only in patients with high-titer RF (P < 0.002). Two other blocking agents, heterophilic blocking reagent and immunoglobulin-inhibiting reagent, also blocked heterophilic activity.

CONCLUSION

All multiplex protein detection platforms we tested exhibited significant confounding by RF or other heterophilic antibodies. These findings have broad-reaching implications in the acquisition and interpretation of data derived from multiplex immunoassay testing of RA patient serum and possibly also in other conditions in which RF or other heterophilic antibodies may be present. Several available blocking agents effectively suppressed this erroneous signal amplification in the multiplex platforms tested.

[Predictors of response to biologic therapies in rheumatoid arthritis]

The advent of biological therapies has revolutionized the management of rheumatoid arthritis, demonstrating effectiveness in controlling clinical and radiological damage. However, 20 to 40% of the patients will not respond to these therapies, which are associated to a very high cost. In addition, non-responder patients are exposed to possible adverse effects. For these reasons, we need to identify predictors of response to these treatments. These predictors are reviewed in this evidence-based paper and classified into genetic and non-genetic. Despite extensive search, nowadays there are no predictors powerful enough to be used in regular clinical practice. Serum factors, the presence of rheumatoid factor and anti-cyclic citrullinated peptide antibodies, are the only factors currently being used to predict the response to specific biological therapy. In the future, probably thanks to new technologies based on genomics, transcriptomics and proteomics, it will be possible to identify genetic predictors of response to biological drugs that will allow us to select suitable patients for a specific biological therapy.

Biomarkers for rheumatoid arthritis: making it personal

Effective treatment of rheumatoid arthritis (RA) has been hampered by the heterogeneity of the disease. Although early intervention can result in disease remission, it requires early diagnosis - and current diagnostic tests are not sufficiently accurate or sensitive in the early stages of RA. As a result, RA is typically diagnosed only once damage to the joints has already begun, a time at which the window for optimal treatment may have been missed. Furthermore, a significant proportion of RA patients do not respond to any given therapeutic. Research efforts are increasingly focused on discovery of biomarkers that enable early diagnosis and stratification of RA, and thus the implementation of timely, targeted therapy. Biomarkers have the potential to transform the management of RA by enabling not only early diagnosis, but also assessment and prediction of disease severity, selection of therapy, and monitoring of response to therapy. In this mini review, we discuss the development of molecular biomarkers for RA.

Synovial effusion and synovial fluid biomarkers in psoriatic arthritis to assess intraarticular tumor necrosis factor-α blockade in the knee joint

INTRODUCTION

The purpose of this study was the evaluation of synovial effusion (SE), synovial fluid (SF) and synovial tissue (ST) biomarkers in relation to disease activity indexes to assess the response to intraarticular (IA) tumor necrosis factor (TNF)-α blockers in psoriatic arthritis (PsA).

METHODS

Systemic and local disease activity indexes (disease activity score (DAS); the Ritchie articular index (mRAI), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP); Thompson articular (THOMP) and joint articular (KJAI)-Index ) and ST samples were assessed at baseline, throughout treatment, and during the follow-up in 14 patients affected with PsA who underwent IA injections (0.5 ml to 12.5 mg) in the knee joint of etanercept (E) or placebo (P) once every two weeks for a 10-week period. Total SF white blood cell (WBC) counts (WBC/μl) and SF cytokine/chemokine (CK/CCK) levels were measured before IA-E at baseline, after IA-E, and as long as there were adequate amounts of SF for knee aspiration (post). Characterization of synovial mononuclear cell infiltration and synovial vessels was carried out in 8 out of 14 knees by staining serial sections of synovial tissue biopsies for CD45, CD3, CD68, CD31 and CD105.

RESULTS

At baseline, CRP and/or ESR were significantly correlated with SF-CK (interleukin- (IL-)1β, IL-1Ra, IL-6, IL-8) and CCK (CCL3). Post-IA injections, there was a decrease in SE in the knees in which aspiration following IA-E injection was possible as well as a significant reduction in SF WBC/μl and in SF-CK (IL-1β, IL-1Ra, IL-6 and IL-22). Pre- and post-IA-E injections, there were significant correlations between ST markers and SF-CK (IL-1β with CD45; IL-1β and IL-6 with CD31) and between SF-CCK (CCL4 and CCL3 with CD3). At the end of the study, there was a significant reduction in disease activity indexes (CRP, DAS, RAI, THOMP, KJAI) as well as in the ST markers (CD45; CD3).

CONCLUSIONS

Synovial effusion regression is a reliable indicator of the response to IA TNF-α blockers in PsA patients as it is confirmed by the correlation between SF biomarkers to disease activity and synovial tissue inflammation.

Patient-tailored therapy in rheumatoid arthritis: an editorial review

PURPOSE OF REVIEW

The list of therapeutic targets for the treatment of rheumatic diseases constantly grows. As a consequence, a growing number of agents that are specifically directed against these targets become clinically available. However, the more diverse (and expensive) the armamentarium, the more its use should be guided by informed decisions for an optimal treatment. Such personalized, patient-tailored therapy is still not a reality in rheumatology practice. However, several important steps have recently been made towards achievement of this important goal.

RECENT FINDINGS

On the basis of the multifactorial nature of the pathogenesis of rheumatic diseases, the quest for single biomarkers that predict treatment response has proven difficult. Instead, biomarker signatures derived from genetic and proteomic expression studies using various biomaterials are being identified and demonstrate predictive value. Research focus has so far been placed on treatment responses to methotrexate and tumor necrosis factor antagonists, but interesting findings are already available for other agents as well.

SUMMARY

Although still in their infancy in rheumatology, personalized treatment approaches offer the potential for improved safety and efficacy for the patient and ultimately have promises to reduce societal costs.

Protein microarrays for personalized medicine

BACKGROUND

Over the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material.

CONTENT

Protein microarrays have become well-established tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine.

SUMMARY

Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

The role of biomarkers in the management of patients with rheumatoid arthritis

In recent years, patient outcomes have improved dramatically with the availability of effective treatments for the management of rheumatoid arthritis (RA). RA, however, is a heterogeneous disease with variable disease progression and treatment response. Whereas some patients respond to a single disease-modifying antirheumatic drug, others require more intensive treatment strategies. Assessing disease severity at diagnosis and monitoring disease activity on an individual level would be a more accurate way of tailoring therapy, ensuring optimal treatment for those at greatest risk of disease progression, long-term disability, and joint damage without unnecessary overtreatment. Assessment of disease activity and severity is currently based on a combination of clinical and laboratory parameters that aid treatment decisions. Use of biomarkers may provide a more accurate means of objectively assessing the disease. This article reviews the role of biomarkers in the management of RA.

Biologic therapy for rheumatoid arthritis: clinical efficacy and predictors of response

Rheumatoid arthritis (RA) is a chronic, disabling disease of the synovial joints, thought to be autoimmune in origin. The emergence of biologic therapies has proven to be highly successful in effectively treating RA in the majority of cases. However, the cost of these agents is high and some patients do not respond to these drugs, or they suffer from adverse events. This article will review the currently available data on efficacy and the clinical, genetic, and biomarkers of response to these biologic therapies in RA. The anti-tumour necrosis factor-alpha (anti-TNFalpha) agents, adalimumab, etanercept and infliximab, act to neutralize the pro-inflammatory cytokine. Response to these agents is higher in patients receiving concurrent disease modifying anti-rheumatic drugs or non-steroidal anti-inflammatory drugs, in those with lesser disability, and in non-smokers. Many genetic predictors of response have been investigated, such as the shared epitope, the TNF gene and its receptors, but none have been absolutely confirmed. Synovial expression of TNFalpha has been suggested as a biomarker of response, while anti-cyclic citrullinated peptide antibody and rheumatoid factor (RF)-positivity predict poor response. Newer biologic agents include the interleukin (IL)-1 receptor antagonist anakinra, the B-cell depleting agent rituximab, the selective costimulation modulator abatacept, and the anti-IL-6 receptor monoclonal antibody tocilizumab. No genetic studies of response to these agents have been performed to date. However, it has been reported that low synovial infiltration of B cells and complete B-cell depletion after the first rituximab infusion are predictors of good response to this agent.

Predicting the future of anti-tumor necrosis factor therapy

Tumor necrosis factor (TNF) antagonists are approved worldwide for the treatment of rheumatoid arthritis (RA). Clinical experience revealed that TNF-blocking therapy is effective for only approximately two thirds of patients, reflecting that there are 'responders' as well as 'nonresponders'. Given the destructive nature of RA, the risk of adverse effects, and considerable costs for therapy, there is a strong need to make predictions on success before the start of therapy. In the current issue of Arthritis Research & Therapy, Hueber and colleagues become the first to present a multi-parameter serum protein biomarker set that has predictive value prior to the start of anti-TNF treatment. Ultimately, this finding may contribute to a personalized form of medicine, whereby a specific therapy will be applied that is best suited to an individual patient.

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.

Protein biochip array technology to monitor rituximab in rheumatoid arthritis

In rheumatoid arthritis (RA) there are currently no good indicators to predict a clinical response to rituximab. The purpose of this study was to monitor and determine the role of peripheral blood cytokine profiling in differentiating between a good versus poor response to rituximab in RA. Blood samples were collected at baseline and at 3 months from 46 RA patients who were treated with rituximab. Responders are defined by the presence of three of four American College of Rheumatology criteria: >or=20% decrease in C-reactive protein, visual analogical score of disease activity, erythrocyte sedimentation rate and improvement of the disease activity score (28) (four values) by >or=1.2 obtained at 3 months. Twelve cytokines were measured from serum collected on days 0 and 90 by proteomic array, including interleukin-6 (IL-6), tumour necrosis factor-alpha, IL-1a, IL-1b, IL-2, IL-8, interferon-gamma, IL-4, IL-10, monocyte chemoattractant protein-1, epidermal growth factor and vascular growth factor. We showed that C-reactive protein and IL-6 levels decrease significantly at 3 months in the responder group compared with baseline. At day 90 we identified a cytokine profile which differentiates responders and non-responders. High serum levels of two proinflammatory cytokines, monocyte chemoattractant protein-1 and epidermal growth factor, were significantly higher in the responder group at day 90 compared with non-responders. However, we were not able to identify a baseline cytokine profile predictive of a good response at 3 months. These findings suggest that cytokine profiling by proteomic analysis may be a promising tool for monitoring rituximab and may help in the future to identify responder RA patients.

Understanding Personalized Medicine in Rheumatoid Arthritis: A Clinician's Guide to the Future

Personalized medicine refers to the utilization of technologies at the molecular level to understand disease processes and improve health outcomes. In rheumatoid arthritis (RA) some factors associated with disease outcome have been identified. These factors have not yet been integrated into a clinically useful tool to predict disease outcome in individual patients. Developments in pharmacogenomics are moving the field forward quite rapidly. Genetic variants, which may have a role in drug metabolism mediating either drug response or toxicity, have been identified for both traditional disease modifying antirheumatic drugs and biologic agents. Choosing a medication based on a patient's characteristics (sociodemographic, clinical, genetic) will result in better utilization of resources and better clinical outcomes. The ethical, political, and legal implications of personalized medicine need to be considered as well.

Recent advances in personalizing rheumatoid arthritis therapy and management

Rheumatoid arthritis (RA) is a chronic, systemic, inflammatory disorder characterized by synovial inflammation in diarthrodial joints. There are significant interindividual variations in the degree of inflammation, disease course and the rate of joint progression in patients with RA. A number of clinical, serological, environmental and genetic severity factors have been identified in patients with RA and can be used to help guide treatment. Therapeutic options for RA have significantly expanded in the last decade and now include both synthetic disease-modifying antirheumatic drugs as well as biologic disease-modifying antirheumatic drugs. Owing to the variety of new drugs, their cost and incomplete information on side effects, markers of treatment response are needed. The study of treatment-specific genetic and protein biomarkers of response and toxicity in RA has produced exciting, yet inconsistent, results. Large scale genetic and proteome studies, which can now be performed at a relatively low cost, will likely broaden the scope and significance of biomarker studies in RA. Integration of these results into clinical practice will vastly improve our ability to provide safe and effective therapy to individuals with RA.