A personalized medicine approach to biologic treatment of rheumatoid arthritis: a preliminary treatment algorithm

Prognostic models of drug-induced neutralizing antibody formation in patients with rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis treated with TNF-α blockersockers

AIM

This study aimed to construct prognostic mathematical models utilizing multifactorial regression analysis to assess the risk of developing drug-induced neutralizing antibodies in patients with rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis treated with tumor necrosis factor alpha blockers.

Circulating and Synovial Monocytes in Arthritis and Ex-Vivo Model to Evaluate Therapeutic Modulation of Synovial Monocytes

Monocytes are innate immune cells that play a dual role in protection of host against pathogens and initiation and perpetuation of inflammatory disorders including joint diseases. During inflammation, monocytes migrate from peripheral blood to tissues via chemokine receptors where they produce inflammatory factors. Monocytes are classified into three subsets, namely: classical, intermediate and non-classical, each subset has particular function. Synovium of patients with inflammatory joint diseases, such as rheumatoid arthritis and psoriatic arthritis as well as osteoarthritis, is enriched by monocytes that differ from circulatory ones by distinct subsets distribution. Several therapeutic agents used systemically or locally through intra-articular injections in arthritis management modulate monocyte subsets. This scoping review summarized the existing literature delineating the effect of common therapeutic agents used in arthritis management on circulating and synovial monocytes/macrophages. As certain agents have an inhibitory effect on monocytes, we propose to test their potential to inhibit synovial monocytes via an ex-vivo platform based on cultured synovial fluid mononuclear cells derived from patients with rheumatic diseases. Information obtained from the ex-vivo platform can be applied to explore the therapeutic potential of medications in clinical practice.

Imaging in inflammatory arthritis: progress towards precision medicine

Imaging techniques such as ultrasonography and MRI have gained ground in the diagnosis and management of inflammatory arthritis, as these imaging modalities allow a sensitive assessment of musculoskeletal inflammation and damage. However, these techniques cannot discriminate between disease subsets and are currently unable to deliver an accurate prediction of disease progression and therapeutic response in individual patients. This major shortcoming of today's technology hinders a targeted and personalized patient management approach. Technological advances in the areas of high-resolution imaging (for example, high-resolution peripheral quantitative computed tomography and ultra-high field MRI), functional and molecular-based imaging (such as chemical exchange saturation transfer MRI, positron emission tomography, fluorescence optical imaging, optoacoustic imaging and contrast-enhanced ultrasonography) and artificial intelligence-based data analysis could help to tackle these challenges. These new imaging approaches offer detailed anatomical delineation and an in vivo and non-invasive evaluation of the immunometabolic status of inflammatory reactions, thereby facilitating an in-depth characterization of inflammation. By means of these developments, the aim of earlier diagnosis, enhanced monitoring and, ultimately, a personalized treatment strategy looms closer.

Association between the functional FCGR3A F158V and FCGR2A R131H polymorphisms and responsiveness to biologics in rheumatoid arthritis patients: A meta-analysis

OBJECTIVES

This study aimed to investigate the association between functional Fc gamma receptor 3A (FCGR3A) V158F and FCGR2A R131H polymorphisms and biologic therapy in rheumatoid arthritis (RA) patients.

METHODS

We searched Medline, Embase, and Cochran databases for available articles. This study is a meta-analysis of the association between the FCGR3A V158F and FCGR2A R131H polymorphisms and their responsiveness to biologics in RA patients.

RESULTS

Seventeen studies involving RA patients with FCGR3A V158F (n = 1884) and FCGR2A R131H (n = 1118) polymorphisms were considered. This meta-analysis showed that the FCGR3A V allele was associated with responsiveness to rituximab (odds ratio [OR] = 1.431, 95% CI = 1.081-1.894, P = 0.012), but not with tumor necrosis factor (TNF) blockers, tocilizumab, or abatacept. A significant association was also found between the FCGR3A V158F polymorphism and responsiveness to biologics using the dominant-recessive model. Additionally, the FCGR3A V158F polymorphism was associated with responsiveness to TNF blockers in the homozygous contrast model. Meta-analysis revealed an association between the FCGR2A RR + RH genotype and responsiveness to biologics (OR = 1.385, 95% CI = 1.007-1.904, P = 0.045).

CONCLUSIONS

This meta-analysis demonstrates that FCGR3A V allele carriers show better responsiveness to rituximab, and FCGR2A R allele carriers may show a better response to biologics in RA treatment. Genotyping of these polymorphisms could be a useful tool to find associations with the responsiveness of personalized medicine to biologics.

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis

Background

The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) according to trajectory groups.

Methods

We analyzed the data from a nationwide RA cohort from the Korean College of Rheumatology Biologics and Targeted Therapy registry. Patients treated with second-line biologic and targeted synthetic DMARDs were included. Trajectory modeling for clustering was used to group the disease activity trend. The contributing factors using the machine learning model of SHAP (SHapley Additive exPlanations) values for each trajectory were investigated.

Results

The trends in the disease activity of 688 RA patients were clustered into 4 groups: rapid decrease and stable disease activity (group 1, n = 319), rapid decrease followed by an increase (group 2, n = 36), slow and continued decrease (group 3, n = 290), and no decrease in disease activity (group 4, n = 43). SHAP plots indicated that the most important features of group 2 compared to group 1 were the baseline erythrocyte sedimentation rate (ESR), prednisolone dose, and disease activity score with 28-joint assessment (DAS28) (SHAP value 0.308, 0.157, and 0.103, respectively). The most important features of group 3 compared to group 1 were the baseline ESR, DAS28, and estimated glomerular filtration rate (eGFR) (SHAP value 0.175, 0.164, 0.042, respectively). The most important features of group 4 compared to group 1 were the baseline DAS28, ESR, and blood urea nitrogen (BUN) (SHAP value 0.387, 0.153, 0.144, respectively).

Conclusions

The trajectory-based approach was useful for clustering the treatment response of biologic and targeted synthetic DMARDs in patients with RA. In addition, baseline DAS28, ESR, prednisolone dose, eGFR, and BUN were important contributing factors for 4-year trajectories.

Lymphocyte activation gene-3 (LAG-3) regulatory T cells: An evolving biomarker for treatment response in autoimmune diseases

Regulatory T cells (Tregs) comprise a CD4⁺CD25⁺Foxp3⁺ T cell subset for maintaining immune tolerance, and their deficits and/or dysfunction are observed in autoimmune diseases. The lymphocyte activation gene 3 (LAG-3, also known as CD223), which is an immunoglobulin superfamily member expressed on peripheral immune cells, is recognized as an inhibitory regulator of Tregs. LAG-3⁺ T cells represent a novel protective Tregs subset that produces interleukin-10. Alterations in LAG-3⁺ Tregs have been reported in several autoimmune diseases, suggesting their potential pathogenic role. Recent studies have indicated that LAG-3⁺ Tregs may be associated not only with immunopathology but also with response to therapy in several autoimmune and autoinflammatory diseases, such as rheumatoid arthritis, psoriasis, psoriatic arthritis and others. We present a review of Tregs phenotypes and functions, with a focus on LAG-3⁺ Tregs, and discuss their potential role as biomarkers for treatment response in autoimmune diseases.

Real-world effectiveness and safety of golimumab in rheumatoid arthritis treatment: A two-center study in Taiwan

BACKGROUND

The real-world outcomes of golimumab (GLM) use have been rarely studied in Asian patients with rheumatoid arthritis (RA). This study assessed the real-world effectiveness and safety of GLM in a Taiwanese cohort.

METHODS

One hundred and eight GLM-treated RA patients were enrolled. Predictors of a good European League Against Rheumatism (EULAR) response at 24 months and drug retention were identified through multivariate analyses.

RESULTS

After 24 months of GLM treatment, the mean Disease Activity Score using 28 joint counts with the erythrocyte sedimentation rate (DAS28-ESR) decreased from 6.7 to 3.1 (p < 0.001). Up to 58.9% of patients achieved a good EULAR response at 24 months. Multivariate logistic regression analysis revealed that after adjustment for other variables, a higher baseline C-reactive protein was an independent negative predictor of good EULAR responses (odds ratio, 0.82; 95% confidence interval [CI], 0.67-0.99; p = 0.043). During the mean follow-up period of 38.3 months, 15 (13.9%) patients discontinued GLM due to treatment failure. In multivariate analysis, high baseline ESR level, high DAS28-ESR, and the experience of biologic therapy were independent risk factors for GLM discontinuation (adjusted hazard ratio [HR], 1.03; 95% CI, 1.01-1.05; p = 0.003; adjusted HR, 2.93; 95% CI, 1.42-6.08; p = 0.004; and adjusted HR, 5.00; 95% CI, 1.75-14.26; p = 0.003, respectively). In receiver operator characteristic curve analysis, the optimal cutoff values of baseline ESR and DAS28-ESR for predicting drug survival were 52 mm/h (sensitivity: 60.0% and specificity: 77.4%) and 7.7 (sensitivity: 46.7% and specificity: 94.3%), respectively. During the follow-up period, 22 patients (20.4%) developed adverse events. The safety profile of GLM in this study was comparable with that in previous clinical trials.

CONCLUSION

GLM was effective and safe for the real-life management of Taiwanese RA patients and showed a high retention rate in biologic-naive patients compared with biologic-experienced patients.

Factors determining the treatment ineffectiveness in multiple sclerosis

BACKGROUND

In patients with multiple sclerosis (MS), the suboptimal response should be well evaluated at every step of treatment.

REVIEW SUMMARY

Determining patients with moderate or high activity and suboptimal response to treatment (clinical variables, MRI activity, perception of the patient and physician, side effects, serious risks, etc.) and timely intervention in the treatment are very important in achieving the desired effectiveness in the long term. Within the early stages, there is a limited time interval for effective treatment of MS patients. During this time, intervention is critical to achieve long-term positive results. After diagnosis, an early and individualized specific treatment for MS, depending on the severity of the disease, can prevent radiological and physical disability in the medium/long term.

CONCLUSIONS

With the emergence of a number of new treatments each with their own benefits and risks, a change in the nature of interactions between patients and MS physicians has been anticipated and will be required in the patient-related clinical decision-making process in the developing MS landscape.

Machine learning model for identifying important clinical features for predicting remission in patients with rheumatoid arthritis treated with biologics

Background

We developed a model to predict remissions in patients treated with biologic disease-modifying anti-rheumatic drugs (bDMARDs) and to identify important clinical features associated with remission using explainable artificial intelligence (XAI).

Methods

We gathered the follow-up data of 1204 patients treated with bDMARDs (etanercept, adalimumab, golimumab, infliximab, abatacept, and tocilizumab) from the Korean College of Rheumatology Biologics and Targeted Therapy Registry. Remission was predicted at 1-year follow-up using baseline clinical data obtained at the time of enrollment. Machine learning methods (e.g., lasso, ridge, support vector machine, random forest, and XGBoost) were used for the predictions. The Shapley additive explanation (SHAP) value was used for interpretability of the predictions.

Results

The ranges for accuracy and area under the receiver operating characteristic of the newly developed machine learning model for predicting remission were 52.8–72.9% and 0.511–0.694, respectively. The Shapley plot in XAI showed that the impacts of the variables on predicting remission differed for each bDMARD. The most important features were age for adalimumab, rheumatoid factor for etanercept, erythrocyte sedimentation rate for infliximab and golimumab, disease duration for abatacept, and C-reactive protein for tocilizumab, with mean SHAP values of − 0.250, − 0.234, − 0.514, − 0.227, − 0.804, and 0.135, respectively.

Conclusions

Our proposed machine learning model successfully identified clinical features that were predictive of remission in each of the bDMARDs. This approach may be useful for improving treatment outcomes by identifying clinical information related to remissions in patients with rheumatoid arthritis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02567-y.

Towards Personalising the Use of Biologics in Rheumatoid Arthritis: A Discrete Choice Experiment

Introduction

There have been promising developments in technologies and associated algorithm-based prescribing (‘stratified approach’) to target biologics to sub-groups of people with rheumatoid arthritis (RA). The acceptability of using an algorithm-guided approach in practice is likely to depend on various factors.

Objective

This study quantified preferences for an algorithm-guided approach to prescribing biologics (termed ‘biologic calculator’).

Methods

An online discrete choice experiment (DCE) was designed to elicit preferences from patients and the public for using a ‘biologic calculator’ compared with conventional prescribing. Treatment approaches were described by five attributes: delay to starting treatment; positive and negative predictive value (PPV/NPV); risk of infection; and cost saving to the UK national health service. Each survey contained six choice sets asking respondents to select their preferred option from two hypothetical biologic calculators or conventional prescribing. Background questions included sociodemographics, health status and healthcare experiences. DCE data were analysed using mixed logit models.

Results

Completed choice data were collected from 292 respondents (151 patients with RA and 142 members of the public). PPV, NPV and risk of infection were the most highly valued attributes to respondents deciding between prescribing strategies.

Conclusion

Respondents were generally receptive to personalised medicine in RA, but researchers developing personalised approaches should pay close attention to generating evidence on both the PPV and the NPV of their technologies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-021-00533-z.

Transforming clinical trials in rheumatology: towards patient-centric precision medicine

Despite the success of targeted therapies in the treatment of inflammatory arthritides, the lack of predictive biomarkers drives a 'trial and error' approach to treatment allocation, leading to variable and/or unsatisfactory responses. In-depth characterization of the synovial tissue in rheumatoid arthritis, as well as psoriatic arthritis and spondyloarthritis, is bringing new insights into the diverse cellular and molecular features of these diseases and their potential links with different clinical and treatment-response phenotypes. Such progress raises the tantalizing prospect of improving response rates by matching the use of specific agents to the cognate target pathways that might drive particular disease subtypes in specific patient groups. Innovative patient-centric, molecular pathology-driven clinical trial approaches are needed to achieve this goal. Whilst progress is clearly being made, it is important to emphasize that this field is still in its infancy and there are a number of potential barriers to realizing the premise of patient-centric clinical trials.

Design of an algorithm for the diagnostic approach of patients with joint pain

BACKGROUND

Rheumatic diseases are a reason for frequent consultation with primary care doctors. Unfortunately, there is a high percentage of misdiagnosis.

OBJECTIVE

To design an algorithm to be used by primary care physicians to improve the diagnostic approach of the patient with joint pain, and thus improve the diagnostic capacity in four rheumatic diseases.

METHODS

Based on the information obtained from a literature review, we identified the main symptoms, signs, and paraclinical tests related to the diagnosis of rheumatoid arthritis, spondyloarthritis with peripheral involvement, systemic lupus erythematosus with joint involvement, and osteoarthritis. We conducted 3 consultations with a group of expert rheumatologists, using the Delphi technique, to design a diagnostic algorithm that has as a starting point "joint pain" as a common symptom for the four diseases.

RESULTS

Thirty-nine rheumatologists from 18 countries of Ibero-America participated in the Delphi exercise. In the first consultation, we presented 94 items to the experts (35 symptoms, 31 signs, and 28 paraclinical tests) candidates to be part of the algorithm; 74 items (25 symptoms, 27 signs, and 22 paraclinical tests) were chosen. In the second consultation, the decision nodes of the algorithm were chosen, and in the third, its final structure was defined. The Delphi exercise lasted 8 months; 100% of the experts participated in the three consultations.

CONCLUSION

We present an algorithm designed through an international consensus of experts, in which Delphi methodology was used, to support primary care physicians in the clinical approach to patients with joint pain. Key Points • We developed an algorithm with the participation of rheumatologists from 18 countries of Ibero-America, which gives a global vision of the clinical context of the patient with joint pain. • We integrated four rheumatic diseases into one tool with one common symptom: joint pain. It is a novel tool, as it is the first algorithm that will support the primary care physician in the consideration of four different rheumatic diseases. • It will improve the correct diagnosis and reduce the number of paraclinical tests requested by primary care physicians, in the management of patients with joint pain. This point was verified in a recently published study in the journal Rheumatology International (reference number 31).

Identification of Novel Native Autoantigens in Rheumatoid Arthritis

The majority of patients diagnosed with rheumatoid arthritis (RA) have developed autoantibodies against neoepitopes in proteins that have undergone post-translational modification, e.g., citrullination or carbamylation. There is growing evidence of their molecular relevance and their potential utility to improve diagnosis, patient stratification, and prognosis for precision medicine. Autoantibodies reacting to native proteins may also have a role in RA pathogenesis, however, their reactivity patterns remain much less studied. We hypothesized that a high-density protein array technology could shed light onto the normal and disease-related autoantibodies produced in healthy and RA patient subgroups. In an exploratory study, we investigated the global reactivity of autoantibodies in plasma pools from 15 anti-cyclic citrullinated peptide (CCP)-positive and 10 anti-CCP-negative RA patients and 10 healthy donors against more than 1600 native and unmodified human proteins using a high-density protein array. A total of 102 proteins recognized by IgG autoantibodies were identified, hereof 86 were recognized by antibodies from CCP-positive RA patients and 76 from anti-CCP-negative RA patients, but not by antibodies from healthy donors. Twenty-four of the identified autoantigens have previously been identified in synovial fluid. Multiple human proteins in their native conformation are recognized by autoantibodies from anti-CCP-positive as well as anti-CCP-negative RA patients.

Assessing prognosis and prediction of treatment response in early rheumatoid arthritis: systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, debilitating disease associated with reduced quality of life and substantial costs. It is unclear which tests and assessment tools allow the best assessment of prognosis in people with early RA and whether or not variables predict the response of patients to different drug treatments.

OBJECTIVE

To systematically review evidence on the use of selected tests and assessment tools in patients with early RA (1) in the evaluation of a prognosis (review 1) and (2) as predictive markers of treatment response (review 2).

DATA SOURCES

Electronic databases (e.g. MEDLINE, EMBASE, The Cochrane Library, Web of Science Conference Proceedings; searched to September 2016), registers, key websites, hand-searching of reference lists of included studies and key systematic reviews and contact with experts.

STUDY SELECTION

Review 1 - primary studies on the development, external validation and impact of clinical prediction models for selected outcomes in adult early RA patients. Review 2 - primary studies on the interaction between selected baseline covariates and treatment (conventional and biological disease-modifying antirheumatic drugs) on salient outcomes in adult early RA patients.

RESULTS

Review 1 - 22 model development studies and one combined model development/external validation study reporting 39 clinical prediction models were included. Five external validation studies evaluating eight clinical prediction models for radiographic joint damage were also included. c-statistics from internal validation ranged from 0.63 to 0.87 for radiographic progression (different definitions, six studies) and 0.78 to 0.82 for the Health Assessment Questionnaire (HAQ). Predictive performance in external validations varied considerably. Three models [(1) Active controlled Study of Patients receiving Infliximab for the treatment of Rheumatoid arthritis of Early onset (ASPIRE) C-reactive protein (ASPIRE CRP), (2) ASPIRE erythrocyte sedimentation rate (ASPIRE ESR) and (3) Behandelings Strategie (BeSt)] were externally validated using the same outcome definition in more than one population. Results of the random-effects meta-analysis suggested substantial uncertainty in the expected predictive performance of models in a new sample of patients. Review 2 - 12 studies were identified. Covariates examined included anti-citrullinated protein/peptide anti-body (ACPA) status, smoking status, erosions, rheumatoid factor status, C-reactive protein level, erythrocyte sedimentation rate, swollen joint count (SJC), body mass index and vascularity of synovium on power Doppler ultrasound (PDUS). Outcomes examined included erosions/radiographic progression, disease activity, physical function and Disease Activity Score-28 remission. There was statistical evidence to suggest that ACPA status, SJC and PDUS status at baseline may be treatment effect modifiers, but not necessarily that they are prognostic of response for all treatments. Most of the results were subject to considerable uncertainty and were not statistically significant.

LIMITATIONS

The meta-analysis in review 1 was limited by the availability of only a small number of external validation studies. Studies rarely investigated the interaction between predictors and treatment.

SUGGESTED RESEARCH PRIORITIES

Collaborative research (including the use of individual participant data) is needed to further develop and externally validate the clinical prediction models. The clinical prediction models should be validated with respect to individual treatments. Future assessments of treatment by covariate interactions should follow good statistical practice.

CONCLUSIONS

Review 1 - uncertainty remains over the optimal prediction model(s) for use in clinical practice. Review 2 - in general, there was insufficient evidence that the effect of treatment depended on baseline characteristics.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042402.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Alternative tumour necrosis factor inhibitors (TNFi) or abatacept or rituximab following failure of initial TNFi in rheumatoid arthritis: the SWITCH RCT

BACKGROUND

Rheumatoid arthritis (RA), the most common autoimmune disease in the UK, is a chronic systemic inflammatory arthritis that affects 0.8% of the UK population.

OBJECTIVES

To determine whether or not an alternative class of biologic disease-modifying antirheumatic drugs (bDMARDs) are comparable to rituximab in terms of efficacy and safety outcomes in patients with RA in whom initial tumour necrosis factor inhibitor (TNFi) bDMARD and methotrexate (MTX) therapy failed because of inefficacy.

DESIGN

Multicentre, Phase III, open-label, parallel-group, three-arm, non-inferiority randomised controlled trial comparing the clinical and cost-effectiveness of alternative TNFi and abatacept with that of rituximab (and background MTX therapy). Eligible consenting patients were randomised in a 1 : 1 : 1 ratio using minimisation incorporating a random element. Minimisation factors were centre, disease duration, non-response category and seropositive/seronegative status.

SETTING

UK outpatient rheumatology departments.

PARTICIPANTS

Patients aged ≥ 18 years who were diagnosed with RA and were receiving MTX, but had not responded to two or more conventional synthetic disease-modifying antirheumatic drug therapies and had shown an inadequate treatment response to a first TNFi.

INTERVENTIONS

Alternative TNFi, abatacept or rituximab (and continued background MTX).

MAIN OUTCOME MEASURES

The primary outcome was absolute reduction in the Disease Activity Score of 28 joints (DAS28) at 24 weeks post randomisation. Secondary outcome measures over 48 weeks were additional measures of disease activity, quality of life, cost-effectiveness, radiographic measures, safety and toxicity.

LIMITATIONS

Owing to third-party contractual issues, commissioning challenges delaying centre set-up and thus slower than expected recruitment, the funders terminated the trial early.

RESULTS

Between July 2012 and December 2014, 149 patients in 35 centres were registered, of whom 122 were randomised to treatment (alternative TNFi, n = 41; abatacept, n = 41; rituximab, n = 40). The numbers, as specified, were analysed in each group [in line with the intention-to-treat (ITT) principle]. Comparing alternative TNFi with rituximab, the difference in mean reduction in DAS28 at 24 weeks post randomisation was 0.3 [95% confidence interval (CI) -0.45 to 1.05] in the ITT patient population and -0.58 (95% CI -1.72 to 0.55) in the per protocol (PP) population. Corresponding results for the abatacept and rituximab comparison were 0.04 (95% CI -0.72 to 0.79) in the ITT population and -0.15 (95% CI -1.27 to 0.98) in the PP population. General improvement in the Health Assessment Questionnaire Disability Index, Rheumatoid Arthritis Quality of Life and the patients' general health was apparent over time, with no notable differences between treatment groups. There was a marked initial improvement in the patients' global assessment of pain and arthritis at 12 weeks across all three treatment groups. Switching to alternative TNFi may be cost-effective compared with rituximab [incremental cost-effectiveness ratio (ICER) £5332.02 per quality-adjusted life-year gained]; however, switching to abatacept compared with switching to alternative TNFi is unlikely to be cost-effective (ICER £253,967.96), but there was substantial uncertainty in the decisions. The value of information analysis indicated that further research would be highly valuable to the NHS. Ten serious adverse events in nine patients were reported; none were suspected unexpected serious adverse reactions. Two patients died and 10 experienced toxicity.

FUTURE WORK

The results will add to the randomised evidence base and could be included in future meta-analyses.

CONCLUSIONS

How to manage first-line TNFi treatment failures remains unresolved. Had the trial recruited to target, more credible evidence on whether or not either of the interventions were non-inferior to rituximab may have been provided, although this remains speculative.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN89222125 and ClinicalTrials.gov NCT01295151.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 34. See the NIHR Journals Library website for further project information.

Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue

Background

Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.

Methods

Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq.

Results

Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4⁺ and CD8⁺ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.

Conclusions

We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1631-y) contains supplementary material, which is available to authorized users.

Effectiveness of biologics in Australian patients with rheumatoid arthritis: a large observational study: REAL

BACKGROUND

The comparative effectiveness of biologic treatment regimens in a real world Australian population is unknown.

AIM

To assess the effectiveness of biological disease-modifying anti-rheumatic drugs (bDMARD) as monotherapy or in combination with methotrexate and/or other conventional DMARD (cDMARD) for the treatment of rheumatoid arthritis (RA).

METHODS

A retrospective, non-interventional study was conducted that investigated the use of bDMARD in adult patients with RA in routine clinical practice. Data were extracted from the Optimising Patient Outcomes in Australian Rheumatology - Quality Use of Medicines Initiative database. Real-world effectiveness was measured using the 28-joint disease activity score (DAS28) and clinical disease activity index (CDAI) by treatment group at baseline, weeks 12 and 24.

RESULTS

A total of 2970 patients was included with a median (min-max) age of 60.0 (19.0-94.0) years and median (min-max) duration of RA before first bDMARD treatment of 6.0 (0.2-58.3) years. A total of 1177 patients received more than one bDMARD during the analysis period of 1 January 1997 to 15 August 2015. Patients had 4922 treatment 'episodes' (defined as a cycle of continuous individual bDMARD prescribing in a single patient). Patients received a mean (SD) of 1.7 (1.0) episodes of treatment with median (min-max) treatment duration of 0.7 (0-11.8) years; median treatment duration was higher with the first treatment episode. bDMARD were most commonly initiated in combination with methotrexate (73.9% of episodes) and least commonly as monotherapy (9.9% of episodes). Median (min-max) baseline DAS28 decreased from 5.3 (0-8.7) with the first bDMARD to 3.7 (0-8.8) with the second. Median baseline CDAI similarly decreased.

CONCLUSIONS

Patients tended to persist longer on their first bDMARD treatment. bDMARD as monotherapy or in combination appear to be accepted treatment strategies in the real world.

Association between IL-6 production in synovial explants from rheumatoid arthritis patients and clinical and imaging response to biologic treatment: A pilot study

Introduction

The need for biomarkers which can predict disease course and treatment response in rheumatoid arthritis (RA) is evident. We explored whether clinical and imaging responses to biologic disease modifying anti-rheumatic drug treatment (bDMARD) were associated with the individual’s mediator production in explants obtained at baseline.

Methods

RA Patients were evaluated by disease activity score 28 joint C-reactive protein (DAS 28-)), colour Doppler ultrasound (CDUS) and 3 Tesla RA magnetic resonance imaging scores (RAMRIS). Explants were established from synovectomies from a needle arthroscopic procedure prior to initiation of bDMARD. Explants were incubated with the bDMARD in question, and the productions of interleukin-6 (IL-6), monocyte chemo-attractive protein-1 (MCP-1) and macrophage inflammatory protein-1-beta (MIP-1b) were measured by multiplex immunoassays. The changes in clinical and imaging variables following a minimum of 3 months bDMARD treatment were compared to the baseline explant results. Mixed models and Spearman’s rank correlations were performed. P-values below 0.05 were considered statistically significant.

Results

16 patients were included. IL-6 production in bDMARD-treated explants was significantly higher among clinical non-responders compared to responders (P = 0.04), and a lack of suppression of IL-6 by the bDMARDS correlated to a high DAS-28 (ρ = 0.57, P = 0.03), CDUS (ρ = 0.53, P = 0.04) and bone marrow oedema (ρ = 0.56, P = 0.03) at follow-up. No clinical association was found with explant MCP-1 production. MIP-1b could not be assessed due to a large number of samples below the detection limit.

Conclusions

Synovial explants appear to deliver a disease-relevant output testing which when carried out in advance of bDMARD treatment can potentially pave the road for a more patient tailored treatment approach with better treatment effects.

Efficacy and safety of monotherapy with sirukumab compared with adalimumab monotherapy in biologic-naïve patients with active rheumatoid arthritis (SIRROUND-H): a randomised, double-blind, parallel-group, multinational, 52-week, phase 3 study

Objective

This randomised, double-blind, parallel-group, phase 3 study compared monotherapy with sirukumab, an anti–interleukin-6 cytokine monoclonal antibody, with adalimumab monotherapy in patients with rheumatoid arthritis (RA).

Methods

Biologic-naïve patients with active RA who were inadequate responders or were intolerant to, or inappropriate for, methotrexate were randomised to subcutaneous sirukumab 100 mg every 2 weeks (n=187), sirukumab 50 mg every 4 weeks (n=186) or adalimumab 40 mg every 2 weeks (n=186). Primary endpoints at week 24 were change from baseline in Disease Activity Score in 28 joints (DAS28) using erythrocyte sedimentation rate (ESR) and proportion of patients achieving an American College of Rheumatology (ACR) 50 response; these endpoints were tested in sequential order. This study is registered at EudraCT (number: 2013-001417-32) and ClinicalTrials.gov (number: NCT02019472).

Results

Significantly greater improvements from baseline in mean (SD) DAS28 (ESR) were observed at week 24 with sirukumab 100 mg every 2 weeks (−2.96 (1.580)) versus adalimumab 40 mg every 2 weeks (−2.19 (1.437); P<0.001). Sirukumab 50 mg every 4 weeks also showed significantly greater improvement from baseline at week 24 in DAS28 (ESR) (−2.58 (1.524)) compared with adalimumab (P=0.013). The ACR50 response rates with the 100 mg (35.3%) and 50 mg (26.9%) doses of sirukumab were comparable to that with adalimumab (31.7%) at week 24. The safety profile of sirukumab was consistent with that observed with anti–interleukin-6 receptor antibodies. A dose-related effect on the incidence of injection-site reactions was observed with sirukumab.

Conclusion

Sirukumab monotherapy showed greater improvements in DAS28 (ESR), but similar ACR50 response rates, versus adalimumab monotherapy.

Prediction of Response to Targeted Treatment in Rheumatoid Arthritis

Rheumatoid arthritis is an autoimmune syndrome presenting with chronic inflammation of the joints. Patients with the same diagnosis can present with different phenotypes. In some patients severe joint inflammation and early joint destruction are observed, whereas a milder phenotype can be seen in others. Conversely, patients with the same signs and symptoms may exhibit different immunological and molecular abnormalities. Since the introduction of early treatment in clinical practice, the treat to target principle, and new medicines such as biologic disease-modifying antirheumatic drugs, clinical remission can be achieved early in the disease course, albeit not in all patients. The clinical response and efficacy of biologic disease-modifying antirheumatic drugs vary among different individuals. Therefore, there is a need to develop a more personalized approach toward treatment to achieve rapid remission in every patient to prevent disability and restore and maintain quality of life, without unnecessary adverse effects, in a cost-effective manner. The latest data from explorative studies of predictive markers of response are discussed here, together with a preliminary treatment algorithm based on currently available knowledge.

Biologics registers in RA: methodological aspects, current role and future applications

The beginning of the 21st century saw a biopharmaceutical revolution in the treatment of inflammatory rheumatic diseases, particularly rheumatoid arthritis. The fast-evolving use of biologic therapies highlighted the need to develop registers at national and international levels with the aim of collecting long-term data on patient outcomes. Over the past 15 years, many biologics registers have contributed a wealth of data and provided robust and reliable evidence on the use, effectiveness and safety of these therapies. The unavoidable challenges posed by the continuous introduction of new therapies, particularly with regard to understanding their long-term safety, highlights the importance of learning from experience with established biologic therapies. In this Perspectives article, the role of biologics registers in bridging the evidence gap between efficacy in clinical trials and real-world effectiveness is discussed, with a focus on methodological aspects of registers, their unique features and challenges and their role going forward.

Differential activation of endocrine-immune networks by arthritis challenge: Insights from colony-specific responses

Rheumatoid arthritis (RA) is a chronic inflammatory condition with variable clinical presentation and disease progression. Importantly, animal models of RA are widely used to examine disease pathophysiology/treatments. Here, we exploited known vendor colony-based differences in endocrine/immune responses to gain insight into inflammatory modulators in arthritis, utilizing the adjuvant-induced arthritis (AA) model. Our previous study found that Sprague-Dawley (SD) rats from Harlan develop more severe AA, have lower corticosteroid binding globulin, and have different patterns of cytokine activation in the hind paw, compared to SD rats from Charles River. Here, we extend these findings, demonstrating that Harlan rats show reduced hypothalamic cytokine responses to AA, compared to Charles River rats, and identify colony-based differences in cytokine profiles in hippocampus and spleen. To go beyond individual measures, probing for networks of variables underlying differential responses, we combined datasets from this and the previous study and performed constrained principal component analysis (CPCA). CPCA revealed that with AA, Charles River rats show activation of chemokine and central cytokine networks, whereas Harlan rats activate peripheral immune/hypothalamic-pituitary-adrenal networks. These data suggest differential underlying disease mechanism(s), highlighting the power of evaluating multiple disease biomarkers, with potential implications for understanding differential disease profiles in individuals with RA.

Methotrexate Reduced TNF Bioactivity in Rheumatoid Arthritis Patients Treated with Infliximab

Objectives. To evaluate methotrexate effect on tumor necrosis factor (TNF) alpha bioactivity during infliximab (IFX) therapy in rheumatoid arthritis (RA) patients and to correlate TNF bioactivity with antibody towards IFX (ATI) development and RA clinical response. Materials and Methods. Thirty-nine active women RA patients despite conventional synthetic disease modifying antirheumatic drugs (csDMARDs) requiring IFX therapy were enrolled, and clinical data and blood samples were recorded at baseline (W0) and at 6 weeks (W6), W22, and W54 of IFX treatment. TNF bioactivity as well as IFX trough and ATI concentrations were assessed on blood samples. Results. TNF bioactivity decreased from W0 to W54 with a large range from W22 at the time of ATI detection. From W22, TNF bioactivity was lower in presence of methotrexate as csDMARD compared to other csDMARDs. IFX trough concentration increased from W0 to W54 with a large range from W22, similarly to TNF bioactivity. Methotrexate therapy prevented ATI presence at W22 and reduced TNF bioactivity compared to other csDMARDs (p = 0.002). Conclusion. This suggests that methotrexate plays a key role in TNF bioactivity and against ATI development.

Efficacy and safety of sirukumab in patients with active rheumatoid arthritis refractory to anti-TNF therapy (SIRROUND-T): a randomised, double-blind, placebo-controlled, parallel-group, multinational, phase 3 study

BACKGROUND

Sirukumab, a human monoclonal antibody that selectively binds to the interleukin-6 cytokine with high affinity, is under development for the treatment of rheumatoid arthritis and other diseases. We aimed to assess the efficacy and safety of sirukumab for rheumatoid arthritis in a phase 3 study (SIRROUND-T).

METHODS

We did a randomised, double-blind, placebo-controlled, parallel-group, multicentre study at 183 hospitals and private rheumatology clinics in 20 countries (Argentina, Australia, Austria, Belgium, Canada, France, Germany, Italy, Japan, Lithuania, Mexico, Netherlands, Poland, Portugal, Russia, South Korea, Spain, Taiwan, UK, and USA). Eligible participants were patients with active rheumatoid arthritis aged at least 18 years, with four or more of 68 tender joints and four or more of 66 swollen joints, who were refractory or intolerant to previous treatment with at least one anti-TNF drug. We randomly assigned patients (1:1:1) via a central interactive voice or web response system to either placebo every 2 weeks, 50 mg sirukumab every 4 weeks, or 100 mg sirukumab every 2 weeks, all given for 52 weeks or less. We allowed participants to continue using any concomitant disease-modifying antirheumatic drugs (DMARDs). We based the randomisation on a computer-generated, permuted-block schedule stratified by use of methotrexate at baseline (0, >0 to <12·5 mg/week, or ≥12·5 mg/week). Masking was achieved with the use of multipart labels on the study drug containers which contained directions for use and other information, but not the drug's identity. Treatments were administered by subcutaneous injection; patients assigned to 50 mg sirukumab given every 4 weeks also received a placebo injection every 2 weeks to maintain masking. At week 18, placebo-treated patients meeting early escape criteria (<20% improvement in swollen and tender joint counts) were randomly reassigned to either 50 mg or 100 mg of sirukumab. All remaining placebo-treated patients were subsequently randomly reassigned at week 24 to either sirukumab dose (crossover). The primary outcome was the proportion of patients who achieved a response of at least 20% improvement at week 16 according to American College of Rheumatology criteria (ACR20) in the intention-to-treat population (all randomly assigned participants). Safety analyses included all participants who received at least one dose (partial or complete) of study drug. This study is registered at EudraCT (number: 2010-022243-38) and ClinicalTrials.gov (number: NCT01606761).

FINDINGS

Between July 25, 2012, and Jan 12, 2016, we randomly assigned 878 patients to treatment: 294 to placebo, 292 to 50 mg sirukumab every 4 weeks, and 292 to 100 mg sirukumab every 2 weeks. 523 (60%) of 878 patients had previously received two or more biological treatments including non-TNF drugs, and 166 (19%) of 878 were not taking a DMARD at baseline. The proportions of patients who achieved an ACR20 response at week 16 were 117 (40%) of 292 with 50 mg sirukumab every 4 weeks, and 132 (45%) of 292 with 100 mg sirukumab every 2 weeks versus 71 (24%) of 294 with placebo; differences compared with placebo were 0·16 (95% CI 0·09-0·23) for 50 mg sirukumab every 4 weeks and 0·21 (0·14-0·29) for 100 mg sirukumab every 2 weeks (both p<0·0001). Adverse event incidences in the 24-week placebo-controlled period were similar across groups (at least one event occurred for 182 patients assigned to placebo [62%, including early escape patients switched to sirukumab at week 18] of 294; 194 [66%] of 292 with 50 mg sirukumab every 4 weeks; and 207 [71%] of 292 with 100 mg sirukumab every 2 weeks). The most common adverse events in this period were injection-site erythema (four [1%] with placebo, 22 [8%] with 50 mg sirukumab every 4 weeks, and 41 [14%] with 100 mg sirukumab every 2 weeks). At week 52, of all patients receiving sirukumab including those reassigned from placebo, the most common adverse events were again injection-site erythema (33 [8%] of 416 with 50 mg sirukumab every 4 weeks and 66 [16%] of 418 with 100 mg sirukumab every 2 weeks).

INTERPRETATION

In patients with active rheumatoid arthritis who were refractory or intolerant to anti-TNF drugs and other biological treatments, both dosing regimens of sirukumab were well tolerated and significantly improved signs and symptoms of the disease, compared with placebo, in this difficult-to-treat population.

FUNDING

Janssen Research & Development, LLC, and GlaxoSmithKline.

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h²=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

Rheumatoid arthritis patients respond differently to anti-TNF treatment. Using community-based challenge, the authors show that currently available data does not reveal meaningful genetic predictors of response to anti-TNF therapy, thus confirming clinical observations.

Associations between PTPRC rs10919563 A/G and FCGR2A R131H polymorphisms and responsiveness to TNF blockers in rheumatoid arthritis: a meta-analysis

We aimed to investigate whether the PTPRC rs10919563 A/G and Fc gamma receptor 2A (FCGR2A) R131H polymorphisms can predict the response to anti-TNF therapy in rheumatoid arthritis (RA) patients. We conducted a meta-analysis of studies on the association between the PTPRC rs10919563 A/G or the FCGR2A R131H polymorphism and responsiveness to anti-TNF therapy in RA patients. Eighteen studies (twelve on PTPRC and six on FCGR2A) from eight articles involving 3058 patients were considered in this meta-analysis. The meta-analysis showed a significant association between the PTPRC rs10919563 A allele and response to TNF-α blockers in RA. The OR of the PTPRC A allele was significantly lower in responders (OR = 0.584, 95 % CI = 0.409-0.835, P = 0.003). Meta-analysis revealed no association between the FCGR2A HH + HR genotype and responsiveness to TNF blockers in all study subjects (OR = 0.762, 95 % CI = 0.543-1.068, P = 0.115). However, stratification by TNF inhibitor type showed that the FCGR2A HH + HR genotype was associated with responsiveness to adalimumab (OR = 0.591, 95 % CI = 0.369-0.947, P = 0.029), but not infliximab and etanercept (OR = 0.929, 95 % CI = 0.354-2.440, P = 0.881; OR = 0.804, 95 % CI = 0.293-2.207, P = 0.673). The PTPRC rs10919563 A allele shows a poor response to anti-TNF therapy, and the FCGR2A HH + HR genotype shows a poor response to adalimumab for RA. Genotyping for these polymorphisms may be useful for predicting the response to TNF-α blockers with respect to personalized medicine.

A Personalized Approach to Biological Therapy Using Prediction of Clinical Response Based on MRP8/14 Serum Complex Levels in Rheumatoid Arthritis Patients

Objectives

Measurement of MRP8/14 serum levels has shown potential in predicting clinical response to different biological agents in rheumatoid arthritis (RA). We aimed to develop a treatment algorithm based on a prediction score using MRP8/14 measurements and clinical parameters predictive for response to different biological agents.

Methods

Baseline serum levels of MRP8/14 were measured in 170 patients starting treatment with infliximab, adalimumab or rituximab. We used logistic regression analysis to develop a predictive score for clinical response at 16 weeks. MRP8/14 levels along with clinical variables at baseline were investigated. We also investigated how the predictive effect of MRP8/14 was modified by drug type. A treatment algorithm was developed based on categorizing the expected response per drug type as high, intermediate or low for each patient and optimal treatment was defined. Finally, we present the utility of using this treatment algorithm in clinical practice.

Results

The probability of response increased with higher baseline MRP8/14 complex levels (OR = 1.39), differentially between the TNF-blockers and rituximab (OR of interaction term = 0.78), and also increased with higher DAS28 at baseline (OR = 1.28). Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response. Based on the treatment algorithm 80 patients would have been recommended for anti-TNF treatment, 8 for rituximab, 13 for another biological treatment (other than TNFi or rituximab) and for 69 no recommendation was made. The predicted response rates matched the observed response in the cohort well. On group level the predicted response based on the algorithm resulted in a modest 10% higher response rate in our cohort with much higher differences in response probability in individual patients treated contrary to treatment recommendation.

Conclusions

Prediction of response using MRP8/14 levels along with clinical predictors has potential in personalizing treatment for RA patients starting biological anti-rheumatic treatment, and might increase cost-effectiveness.

Neo-Epitopes--Fragments of Cartilage and Connective Tissue Degradation in Early Rheumatoid Arthritis and Unclassified Arthritis

OBJECTIVE

Tissue destruction in rheumatoid arthritis (RA) is predominantly mediated by matrix metalloproteinases (MMPs), thereby generating protein fragments. Previous studies have revealed that these fragments include MMP-mediated collagen type I, II, and III degradation, citrullinated and MMP-degraded vimentin and MMP degraded C-reactive protein. We evaluated if biomarkers measuring serum levels of specific sequences of the mentioned fragments would provide further information of diagnostic and/or prognostic processes in early arthritis.

METHODS

Ninety-two early arthritis patients (arthritis duration<1 year, DMARD naïve) were enrolled. Patients either fulfilled the ACR/EULAR2010 criteria for RA (n = 60) or had unclassified arthritis (UA) (n = 32). Patients fulfilling the RA criteria after 2 years follow-up were classified into non-erosive (n = 25), or erosive disease (n = 13). Concentrations of the biomarkers: C1M, C2M, C3M, VICM and CRPM were measured in baseline serum.

RESULTS

C1M, C3M and CRPM were able to discriminate between the UA and RA baseline diagnosis in 92 patients with an AUROC of 0.64 (95%CI 0.517 to 0.762), 0.73 (95%CI 0.622 to 0.838) and 0.68 (95%CI 0.570 to 0.795). C2M showed a potential for discrimination between non-erosive and erosive disease in 38 patients with an AUROC of 0.75 (95%CI 0.597 to 0.910). All of the applied biomarkers correlated with one or more of the disease activity parameters: DAS28, ESR, CRP, SJC66, TJC68 and/or HAQ.

CONCLUSION

This is the first study evaluating the applied biomarkers at this early stage of arthritis. C1M, C3M, CRPM might be the best diagnostic marker, whereas high levels of C2M indicated progression of disease at follow-up in early RA patients.

A clinically based protein discovery strategy to identify potential biomarkers of response to anti-TNF-α treatment of psoriatic arthritis

PURPOSE

Psoriatic arthritis (PsA) can be treated using biologic therapies targeting biomolecules such as tumor necrosis factor alpha, interleukins (IL)-17 and IL-23. Although 70% PsA patients respond well to therapy, 30% patients show no or limited clinical improvement. Biomarkers that predict response to therapy would help to avoid unnecessary use of expensive biologics in nonresponding patients and enable alternative treatments to be explored.

EXPERIMENTAL DESIGN

Patient synovial tissue samples from two clinical studies were analysed using difference in-gel electrophoresis-based proteomics to identify protein expression differences in response to anti-TNF-α treatment. Subsequent multiplexed MRM measurements were used to verify potential biomarkers.

RESULTS

A total of 119 proteins were differentially expressed (p<0.05) in response to anti-TNF-α treatment and 25 proteins were differentially expressed (p<0.05) between "good responders" and "poor responders". From these differentially expressed proteins, MRM assays were developed for four proteins to explore their potential as treatment predictive biomarkers.

CONCLUSION AND CLINICAL RELEVANCE

Gel-based proteomics strategy has demonstrated differential protein expression in synovial tissue of PsA patients, in response to anti-TNF-α treatment. Development of multiplex MRM assays to these differentially expressed proteins has the potential to predict response to therapy and allow alternative, more effective treatments to be explored sooner.

Personalizing Treatment Targets in Rheumatoid Arthritis by Using a Simple Prediction Model

Objective.

To develop a personalized treatment target approach in patients with rheumatoid arthritis (RA) based on baseline risk factors for joint damage progression in combination with disease activity over time.

Methods.

Data were used from the Nijmegen early RA cohort. Presence or absence of anticyclic citrullinated peptide antibodies (anti-CCP), high erythrocyte sedimentation rate, and erosions were translated into 4 risk profiles: 0, 1, 2, and 3. Joint damage progression was assessed with the Ratingen score, and disease activity with the original Disease Activity Score (DAS) over 3 years. The probability for joint damage progression was calculated for each risk profile and each DAS category using logistic regression models. The probabilities were translated into personalized disease activity treatment targets.

Results.

More risk factors at baseline as well as a higher DAS level resulted in a higher probability for joint damage progression in a dose-dependent way. Low DAS corresponded with a probability of 0.0, 0.08, 0.20, and 0.58 in patients with 0, 1, 2, and 3 risk factors, respectively. Moderate DAS corresponded with a probability of 0.06 in patients with 0 risk factors and 0.35 with 1 risk factor. High DAS resulted in a probability of 0.50 with no risk factors present at baseline.

Conclusion.

Presence of anti-CCP, acute-phase response, and erosions at baseline can be used to set individual treatment targets in RA. In patients without these risk factors, a moderate DAS as a target is sufficient, while for patients with all 3 risk factors, a low DAS is not strict enough to limit the risk for joint damage.

Small-molecule therapeutics in rheumatoid arthritis: scientific rationale, efficacy and safety

Rheumatoid arthritis (RA) remains a formidable clinical challenge. This is despite remarkable recent advances in our understanding of pathogenesis and the introduction of a variety of novel agents, particularly biologic therapeutics that are potent inhibitors of extracellular immune pathways. Whereas the latter have brought substantial improvements in efficacy and thus outcomes, there remain significant numbers of non- or partial responders to current standard of care. The discovery of key intracellular pathways, particularly kinases that subserve the function of these pivotal cytokine and immune cell receptors implicated in RA pathogenesis, has facilitated the advent of a new phase of RA drug development. Thus, a range of kinase inhibitors has entered clinical trials and one agent has been licenced for use in some regions. Herein we summarise the chequered history of kinase inhibitor development in RA, describing successes and failures alike, and thereafter examine future trends in this exciting field.

Collagen II antibody-induced arthritis in Tg1278TNFko mice: optimization of a novel model to assess treatments targeting human TNFα in rheumatoid arthritis

Background

Novel molecules that specifically target human TNFα in rheumatoid arthritis pose problems for preclinical assessment of efficacy. In this study collagen antibody-induced arthritis (CAIA) has been induced in human TNFα transgenic mice to provide a novel model that has been optimised for the evaluation of molecules targeting human TNFα.

Methods

Tg1278TNFko mice lack murine TNFα and are heterozygous for multiple copies of the human TNFα transgene that is expressed under normal physiological control. To establish CAIA, a collagen II monoclonal antibody cocktail (CAb) at 2, 4 or 8 mg was injected i.p. on Day 0 followed by a lipopolysaccharide (LPS) boost (10 or 100 μg) i.p. on Day 1 or Day 4. Animals were assessed for arthritis symptoms using a clinical score, cytokine levels (human TNFα, IL-1β and IL-6) in sera and joints, and histopathology. The dependence of the model on human TNFα was determined by dosing animals with etanercept.

Results

Tg1278TNFko animals treated with 2, 4 or 8 mg CAb on Day 0, with 100μg LPS on Day 4, had more severe arthritis and earlier symptoms than wild type animals at all doses of CAb tested. Subsequently it was found that the transgenic model did not require LPS at all for arthritis development but a lower dose of LPS (10 μg) was found necessary for reproducible and robust disease (close to 100% incidence, well-synchronised, with high arthritis scores). Furthermore the LPS challenge could be brought forward to Day 1 so that its’ actions to facilitate disease could be separated temporally from the arthritis phase (beginning about Day 4). Etanercept, administered immediately after the serum spike of cytokines associated with LPS had subsided, was able to dose-dependently inhibit arthritis development and this was associated with a marked protection of the joints histologically on Day 14. Etanercept was also able to reverse the signs of arthritis when given therapeutically allowing animals to be matched for disease burden before dosing begins.

Conclusions

The features of CAIA in Tg1278TNFko animals make the model well-suited to testing the next generation of therapeutics that will target human TNFα in rheumatoid arthritis.

Accelerating translational research by clinically driven development of an informatics platform--a case study

Translational medicine is becoming increasingly dependent upon data generated from health care, clinical research, and molecular investigations. This increasing rate of production and diversity in data has brought about several challenges, including the need to integrate fragmented databases, enable secondary use of patient clinical data from health care in clinical research, and to create information systems that clinicians and biomedical researchers can readily use. Our case study effectively integrates requirements from the clinical and biomedical researcher perspectives in a translational medicine setting. Our three principal achievements are (a) a design of a user-friendly web-based system for management and integration of clinical and molecular databases, while adhering to proper de-identification and security measures; (b) providing a real-world test of the system functionalities using clinical cohorts; and (c) system integration with a clinical decision support system to demonstrate system interoperability. We engaged two active clinical cohorts, 747 psoriasis patients and 2001 rheumatoid arthritis patients, to demonstrate efficient query possibilities across the data sources, enable cohort stratification, extract variation in antibody patterns, study biomarker predictors of treatment response in RA patients, and to explore metabolic profiles of psoriasis patients. Finally, we demonstrated system interoperability by enabling integration with an established clinical decision support system in health care. To assure the usefulness and usability of the system, we followed two approaches. First, we created a graphical user interface supporting all user interactions. Secondly we carried out a system performance evaluation study where we measured the average response time in seconds for active users, http errors, and kilobits per second received and sent. The maximum response time was found to be 0.12 seconds; no server or client errors of any kind were detected. In conclusion, the system can readily be used by clinicians and biomedical researchers in a translational medicine setting.

Local synovial engagement of angiogenic TIE-2 is associated with the development of persistent erosive rheumatoid arthritis in patients with early arthritis

OBJECTIVE

To examine the role of vascular endothelial growth factor (VEGF) and angiopoietin signaling in the diagnosis and disease outcome of patients with early arthritis.

METHODS

Fifty patients with early arthritis (disease duration <1 year) who had not been treated with disease-modifying antirheumatic drugs (DMARDs) were monitored prospectively and were classified at baseline and after 2 years as having undifferentiated arthritis (UA), rheumatoid arthritis (RA), or spondyloarthritis (SpA). All patients underwent arthroscopic synovial biopsy at baseline. Synovial expression of VEGF, VEGF receptor, angiopoietin 1 (Ang-1), Ang-2, TIE-2, and activated p-TIE-2 was evaluated by immunohistochemistry. Serum levels of VEGF, Ang-1, and Ang-2 were measured by enzyme-linked immunosorbent assay. Secreted products of macrophages stimulated with Ang-1 and Ang-2 were measured using a multiplex system.

RESULTS

Expression of Ang-1 was comparable between the patients with RA at baseline and patients with UA who fulfilled the criteria for RA over time (UA/RA), and it was significantly higher in patients with RA (P < 0.05) or UA/RA (P < 0.005) than in patients with SpA. TIE-2 and p-TIE-2 were more highly expressed in patients with RA (P < 0.005) or UA/RA (P < 0.05) than in patients with SpA. Ang-1 significantly enhanced the tumor necrosis factor-dependent macrophage production of cytokines and chemokines that are known to be elevated in the synovial fluid of patients with early RA. In RA, relative TIE-2 activation predicted the development of erosive disease (R(2) = 0.35, P < 0.05).

CONCLUSION

Local engagement of synovial TIE-2 is observed during the earliest phases of RA, suggesting that TIE-2 signaling may contribute to disease development and progression or may indicate an attempt to protect against these processes. Early therapeutic targeting of TIE-2 signaling may be useful in improving outcome in arthritis.

European League against rheumatism - selected presentation and poster a highlights June 11th to 13th 2013

INTRODUCTION

The heterogeneous pathology of many autoimmune diseases warrants the continual discovery and development of new drugs. Drawing on selected oral presentations and selected poster displays, this article highlights some new developments in the pharmacological validation of molecular targets implicated in inflammatory autoimmune disease and may be of direct importance to scientists working in this field.

AREAS COVERED

This report describes the current state of the pharmacology of selected drugs and targets which may have utility in modulating immune function and autoimmune inflammatory disease.

EXPERT OPINION

Many new molecules are progressing through clinical development for the treatment of rheumatological diseases. The value of the basic nonclinical and clinical research presented is to further pharmacological knowledge of the molecule, better understand the benefit-risk associated with clinical development and to assist in supporting the potential position of a new drug in the current treatment paradigm.

Reflections on Lupus 2013: butterflies, wolves and prophecies

The recently concluded Tenth International Congress on Systemic Lupus Erythematosus (SLE) held in Buenos Aires was a resounding success. This overview summarizes some of the origins of the First International Congress held in Calgary, Canada in 1986, predictions offered by past Congress Presidents, and a perspective on the trends in autoantibody testing, which remains one of the key approaches to the early and accurate diagnosis of SLE. The last few decades have witnessed a remarkable proliferation of new diagnostic technologies including addressable laser bead immunoassays and, more recently, chemiluminescence and lateral flow technologies that could find a clinical niche in point-of-care diagnostics. Against the backdrop of these constantly emerging technologies, indirect immunofluorescence has remained the platform of choice for many laboratories and diagnosticians. The notion that autoantibodies are pathogenic has been challenged by evidence that some autoantibodies are protective, some may have catalytic capacity while others may be neutral or have no function at all. The latter notion of functionless or "junk" autoantibodies needs to be taken under some advisement, because there was a time when a great proportion of the human genome was considered to include "junk DNA". The butterfly as a symbol of hope and progress in SLE research over the past 27 years since the First International Congress on SLE is almost certainly to be even more appropriate when future Congresses are held in Geneva (2015), Melbourne (2017) and eventually one in 2050.

[Personalized medicine in cytokine-targeted therapy]

Personalized healthcare tries to predict the effectiveness and safety in individual therapeutic approaches by defining individual patient characteristics (biomarkers), while stratification uses diagnostic patterns for groups of patients for prediction of therapeutic response with less adverse reactions caused by the drugs applied. Both methods are implemented in oncology and infectiology and in the therapy of rheumatological diseases there is a need for both. Cytokine-directed therapies are important for the treatment of rheumatological diseases, especially when therapy with conventional disease-modifying antirheumatic drugs (DMARD) has failed. Despite the high potency of these drugs for inhibiting pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), interleukin 1 (IL-1) and IL-6, sufficient responses are only seen in some of the patients. Therefore, stratification and personalized medicine are ways to optimize efficacy and tolerability of biologic therapies. Some initial evidence is available for potential future strategies using molecular and genetic markers for stratified cytokine inhibition.

Location of CD4+ T cell priming regulates the differentiation of Th1 and Th17 cells and their contribution to arthritis

Th cytokines IFN-γ and IL-17 are linked to the development of autoimmune disease. In models of rheumatoid arthritis, that is, proteoglycan (PG)-induced arthritis, IFN-γ is required, whereas in collagen-induced arthritis, IL-17 is necessary for development of arthritis. In this study we show that the route of immunization determines the requirement for either IFN-γ or IL-17 in arthritis. Intraperitoneal immunization with PG induces a CD4(+) T cell IFN-γ response with little IL-17 in the spleen and peripheral lymph nodes. However, s.c. immunization induces both an IFN-γ and an IL-17 CD4(+) T cell response in spleen and lymph nodes. The failure to induce a CD4(+) T cell IL-17 response after i.p. immunization is associated with T cell priming, as naive T cells activated in vitro were fully capable of producing IL-17. Moreover, PG-induced arthritis is converted from an IFN-γ to an IL-17-mediated disease by altering the route of immunization from i.p. to s.c. The histological appearance of joint inflammation (cellular inflammation and bone erosion) is similar in the i.p. versus s.c. immunized mice despite the presence of CD4(+) T cells producing IL-17 in joint tissues only after s.c. immunization. These data indicate a critical role for the site of initial T cell priming and the Th cytokines required for susceptibility to arthritis. Our findings suggest that T cell activation at different anatomical sites in rheumatoid arthritis patients may skew the T cells toward production of either IFN-γ or IL-17.

Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis

BACKGROUND

Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach.

METHODS

We conducted a multistage, genome-wide association study with a primary analysis of 2 557 253 single-nucleotide polymorphisms (SNPs) in 882 patients with RA receiving anti-TNF therapy included through the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry and the database of Apotheekzorg. Linear regression analysis of changes in the Disease Activity Score in 28 joints after 14 weeks of treatment was performed using an additive model. Markers with p<10(-3) were selected for replication in 1821 patients from three independent cohorts. Pathway analysis including all SNPs with p<10(-3) was performed using Ingenuity.

RESULTS

772 markers showed evidence of association with treatment outcome in the initial stage. Eight genetic loci showed improved p value in the overall meta-analysis compared with the first stage, three of which (rs1568885, rs1813443 and rs4411591) showed directional consistency over all four cohorts studied. We were unable to replicate markers previously reported to be associated with anti-TNF outcome. Network analysis indicated strong involvement of biological processes underlying inflammatory response and cell morphology.

CONCLUSIONS

Using a multistage strategy, we have identified eight genetic loci associated with response to anti-TNF treatment. Further studies are required to validate these findings in additional patient collections.