Stratified medicine in rheumatoid arthritis-the MATURA programme

JAK/STAT signaling in rheumatoid arthritis leukocytes is uncoupled from serum cytokines in a subset of patients

OBJECTIVE

Rheumatoid Arthritis (RA) is a systemic autoimmune disease involving pro-inflammatory cytokines that can be therapeutically targeted by antibodies or kinase inhibitors. Nevertheless, these drugs fail in a subset of patients independent of the abundance of the targeted cytokines. We aim to explore the cellular basis of this phenomenon by analyzing the relation of cytokine abundance and activation of downstream signaling pathways in RA.

METHODS

The study included 62 RA patients and 9 healthy controls (HC). Phosphorylation of STAT 1-6 in various immune cell subsets was determined ex vivo using a novel robust flow cytometry-based protocol. Serum concentrations of IL-6, IL-10, IL-12p70, IL-17 A, interferon gamma, and TNFα in the same samples were measured using highly sensitive single molecule array (SIMOA).

RESULTS

We found an increase in circulating cytokines in RA patients, while STAT activity was lower in RA patients compared to HC. Based on STAT activity we determined three endotypes in active RA patients (cDAI>10, n = 28): 1) those with active STAT5a/b signaling in T cells (n = 7/28), 2) those with a low STAT activity in all assessed cell types (n = 14/28), and 3) those with active STAT1 and STAT3 signaling mainly in myeloid cells (n = 7/28). Integrating intracellular STAT activation and cytokine analysis revealed diminished JAK/STAT signaling in a subset of patients (n = 8/20) despite elevated serum cytokine concentrations.

CONCLUSION

Diminished JAK/STAT signaling in active RA may partly explain unresponsiveness to therapy targeting cytokine signaling. Analysis of JAK/STAT phosphorylation may identify patients at risk for non-response to these therapies.

Automated clustering reveals CD4+ T cell subset imbalances in rheumatoid arthritis

Background

Despite the report of an imbalance between CD4+ T helper (Th) cell subsets in rheumatoid arthritis (RA), patient stratification for precision medicine has been hindered by the discovery of ever more Th cell subsets, as well as contradictory association results.

Objectives

To capture previously reported Th imbalance in RA with deep immunophenotyping techniques; to compare hypothesis-free unsupervised automated clustering with hypothesis-driven conventional biaxial gating and explore if Th cell heterogeneity accounts for conflicting association results.

Methods

Unstimulated and stimulated peripheral blood mononuclear cells from 10 patients with RA and 10 controls were immunophenotyped with a 37-marker panel by mass cytometry (chemokine receptors, intra-cellular cytokines, intra-nuclear transcription factors). First, conventional biaxial gating and standard definitions of Th cell subsets were applied to compare subset frequencies between cases and controls. Second, unsupervised clustering was performed with FlowSOM and analysed using mixed-effects modelling of Associations of Single Cells (MASC).

Results

Conventional analytical techniques fail to identify classical Th subset imbalance, while unsupervised automated clustering, by allowing for unusual marker combinations, identified an imbalance between pro- and anti-inflammatory subsets. For example, a pro-inflammatory Th1-like (IL-2+ T-bet+) subset and an unconventional but pro-inflammatory IL-17+ T-bet+ subset were significantly enriched in RA (odds ratio=5.7, p=2.2 x 10-3; odds ratio=9.7, p=1.5x10-3, respectively). In contrast, a FoxP3+ IL-2+ HLA-DR+ Treg-like subset was reduced in RA (odds ratio=0.1, p=7.7x10-7).

Conclusion

Taking an unbiased approach to large dataset analysis using automated clustering algorithms captures non-canonical CD4+ T cell subset imbalances in RA blood.

Perspectives and challenges in patient stratification in Alzheimer’s disease

Background

Patient stratification is the division of a patient population into distinct subgroups based on the presence or absence of particular disease characteristics. As patient stratification can be used to account for the underlying pathology of a disease, it can help physicians to tailor therapeutic interventions to individuals and optimize their care management and treatment regime. Alzheimer’s disease, the most common form of dementia, is a heterogeneous disease and its management benefits from patient stratification in clinical trials, and the development of personalized care and treatment strategies for people living with the disease.

Main body

In this review, we discuss the importance of the stratification of people living with Alzheimer’s disease, the challenges associated with early diagnosis and patient stratification, and the evolution of patient stratification once disease-modifying therapies become widely available.

Conclusion

Patient stratification plays an important role in drug development in clinical trials and may play an even larger role in clinical practice. A timely diagnosis and stratification of people living with Alzheimer’s disease is paramount in determining people who are at risk of progressing from mild cognitive impairment to Alzheimer’s dementia. There are key issues associated with stratifying patients which include the heterogeneity and complex neurobiology behind Alzheimer’s disease, our inadequately prepared healthcare systems, and the cultural perceptions of Alzheimer’s disease. Stratifying people living with Alzheimer’s disease may be the key in establishing precision and personalized medicine in the field, optimizing disease prevention and pharmaceutical treatment to slow or stop cognitive decline, while minimizing adverse effects.

Histopathology of Psoriatic Arthritis Synovium—A Narrative Review

Psoriatic arthritis (PsA) is a phenotypically heterogeneous chronic inflammatory disease associated to type I major histocompatibility complex alleles whose complex pathogenesis is still not completely understood. The psoriatic synovium shares general features of chronic inflammation with rheumatoid arthritis (RA) and other arthritis, such as hyperplasia of the intimal lining layer, sublining influx of inflammatory cells and neoangiogenesis, but recognizing disease-specific histopathologic findings may help in diagnosis and definition of therapeutic targets. Available literature reports conflicting data regarding the extension of lining hyperplasia, that does not allow depiction from RA. Sublining inflammatory cells consist of T and B cells and macrophages, plasma cells, mast cells and follicular dendritic cells, with a higher amount of overall T, mast cell and IL-17 producing CD8+ T lymphocytes and lower proportion of plasma cells when compared to the rheumatoid synovium. The amount of synovium IL17+ CD8+ T cells correlates positively to measures of disease activity. Lymphoid follicles with characteristics of germinal centers have been identified, similar to the ones described in RA. Neoangiogenesis is more prominent in PsA but can also be an outstanding feature in some RA samples, and different molecules involved in the process appear to have different influence in each disease. IL-17 and IL-22 expression in the synovium does not allow depiction between diseases. Among other cytokines and molecules likely implicated in disease physiopathology, only IL-35 is demonstrated to be reduced in PsA when compared to RA.

Psoriatic arthritis: prospects for the future

Psoriatic arthritis (PsA) is a form of chronic inflammatory arthritis associated with psoriasis and a multitude of other symptoms, most commonly arthritis, dactylitis, enthesitis and axial involvement. PsA is significantly heterogeneous, with a highly variable clinical course of PsA. Patients may experience significant or mild skin and joint symptoms, with some patients developing rapidly progressing joint destruction and skin symptoms. Despite the range of symptom severity, PsA is frequently associated with significantly impaired quality of life from joint destruction, as well as chronic pain and a range of comorbidities such as depression and cardiovascular disease. Currently, there are no definitive diagnostic tests for PsA, with diagnosis remaining challenging owing to the heterogeneous presentation and course of the disease. Presently, the CASPAR criteria are often used to aid rheumatologists in distinguishing PsA from other inflammatory arthritides. Treatment options for patients have been expanded over the last two decades with the emerging clinical utility of biological therapies. However, early identification and diagnosis of patients and effective disease control remain unmet medical needs within the PsA community. In addition, predicting response to treatment also remains a challenge to rheumatologists. This review highlights the current hurdles faced by healthcare professionals in the diagnosis and management of PsA patients and provides future action points for consideration by the members of the multidisciplinary team who treat PsA patients.

The histopathological synovitis score is influenced by biopsy location in patients with knee osteoarthritis

INTRODUCTION

Osteoarthritis (OA) and rheumatoid arthritis (RA) represent the most common forms of arthritis, which are mainly caused by mechanical and inflammatory components, respectively. Determination of synovial inflammation in synovial biopsies via the histopathological Krenn score may be crucial for correct diagnosis and treatment. Specifically, it remains unclear whether synovitis scores differ among multiple biopsy locations within a single joint.

MATERIALS AND METHODS

Eighty synovial samples were taken from four standardized regions of the knee in 20 patients (ten primary OA, ten secondary OA) undergoing total knee arthroplasty (TKA) or total synovectomy. The Krenn synovitis score (grade 0-9) was determined in a blinded manner by two expert pathologists in all biopsies. Next to the inter-rater reliability, we evaluated the agreement of the determined scores among the four biopsy locations within each knee.

RESULTS

The inter-rater reliability between the two pathologists was very high (Cohen's kappa = 0.712; r = 0.946; ICC = 0.972). The mean synovitis score was significantly higher in knees with secondary than in primary OA (p = 0.026). Importantly, we found clear differences between the scores of the four different biopsy locations within the individual knee joints, with an average deviation of 10.6%. These deviations were comparable in knees with primary and secondary OA (p = 0.64).

CONCLUSIONS

While we confirmed the synovitis score as a reliable and reproducible parameter to assess the histopathological synovitis grade in the knee, the considerable variability within the joint indicates that multiple synovial biopsies from different regions should be obtained to enable reliable results of the synovitis score.

Synovial Fluid Cytokines, Chemokines and MMP Levels in Osteoarthritis Patients with Knee Pain Display a Profile Similar to Many Rheumatoid Arthritis Patients

Background: There are currently no effective disease-modifying drugs to prevent cartilage loss in osteoarthritis and synovial fluid is a potentially valuable source of biomarkers to understand the pathogenesis of different types of arthritis and identify drug responsiveness. The aim of this study was to compare the differences between SF cytokines and other proteins in patients with OA (n = 21) to those with RA (n = 27) and normal knees (n = 3). Methods: SF was obtained using ultrasound (US) guidance and an external pneumatic compression device. RA patients were categorized as active (n = 20) or controlled (n = 7) based upon SF white blood cell counts (> or <300 cells/mm³). Samples were cryopreserved and analyzed by multiplex fluorescent bead assays (Luminex). Between-group differences of 16 separate biomarker proteins were identified using ANOVA on log10-transformed concentrations with p values adjusted for multiple testing. Results: Only six biomarkers were significantly higher in SF from active RA compared to OA—TNF-α, IL-1-β IL-7, MMP-1, MMP-2, and MMP-3. Only MMP-8 levels in RA patients correlated with SF WBC counts (p < 0.0001). Among OA patients, simultaneous SF IL-4, IL-6, IL-8, and IL-15 levels were higher than serum levels, whereas MMP-8, MMP-9, and IL-18 levels were higher in serum (p < 0.05). Conclusion: These results support the growing evidence that OA patients have a pro-inflammatory/catabolic SF environment. SF biomarker analysis using multiplex testing and US guidance may distinguish OA phenotypes and identify treatment options based upon targeted inflammatory pathways similar to patients with RA.

Which Biologic Therapies to Treat Active Rheumatoid Arthritis and When?

Biological disease-modifying anti-arthritis drugs (bDMARD) have transformed rheumatoid arthritis (RA) treatment and allowed many patients to reach clinical remission. With the huge growth in the development of different bDMARDs, there is now a need to decide on which treatment should be prescribed to achieve optimal patient outcomes. Decisions are made by weighing up the comparative efficacy of each agent against risks, namely the risk of bacterial infections. The most powerful tools for investigating the comparative efficacy of bDMARDs are head-to-head trials that directly compare one therapy to another; however, very few trials of this type exist. Furthermore, the heterogeneity of RA calls for consideration of the comparative efficacy of therapies on an individual basis. Many studies have found associations between specific biomarkers and response to different bDMARDs to enable stratification of patient groups, although many results have not been reproducible in different cohorts. Combining predictors to create models of treatment response may be the ultimate key to finding reliable biomarkers with enough predictive power to enable a personalised medicine approach to treating RA in the clinic.

Precision Medicine for Rheumatoid Arthritis: The Right Drug for the Right Patient-Companion Diagnostics

Despite the growing number of biologic and JAK inhibitor therapeutic agents available to treat various systemic autoimmune illnesses, the lack of a validated companion diagnostic (CDx) to accurately predict drug responsiveness for an individual results in many patients being treated for years with expensive, ineffective, or toxic drugs. This review will focus primarily on rheumatoid arthritis (RA) therapeutics where the need is greatest due to poor patient outcomes if the optimum drug is delayed. We will review current FDA-approved biologic and small molecule drugs and why RA patients switch these medications. We will discuss the sampling of various tissues for potential CDx and review early results from studies investigating drug responsiveness utilizing advanced technologies including; multiplex testing of cytokines and proteins, autoantibody profiling, genomic analysis, proteomics, miRNA analysis, and metabolomics. By using these new technologies for CDx the goal is to improve RA patient outcomes and achieve similar successes like those seen in oncology using precision medicine guided therapeutics.

Novel approaches to develop biomarkers predicting treatment responses to TNF-blockers

Introduction: Chronic inflammatory diseases (CIDs) cause significant morbidity and are a considerable burden for the patients in terms of pain, impaired function, and diminished quality of life. Important progress in CID treatment has been obtained with biological therapies, such as tumor-necrosis-factor blockers. However, more than a third of the patients fail to respond to these inhibitors and are exposed to the side effects of treatment, without the benefits. Therefore, there is a strong interest in developing tools to predict response of patients to biologics. Areas covered: The authors searched PubMed for recent studies on biomarkers for disease assessment and prediction of therapeutic responses, focusing on the effect of TNF blockers on immune responses in spondyloarthritis (SpA), and other CID, in particular rheumatoid arthritis and inflammatory bowel disease. Conclusions will be drawn about the possible development of predictive biomarkers for response to treatment. Expert opinion: No validated biomarker is currently available to predict treatment response in CID. New insight could be generated through the development of new bioinformatic modeling approaches to combine multidimensional biomarkers that explain the different genetic, immunological and environmental determinants of therapeutic responses.

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.

Investigation of genetically regulated gene expression and response to treatment in rheumatoid arthritis highlights an association between IL18RAP expression and treatment response

Objectives

In this study, we sought to investigate whether there was any association between genetically regulated gene expression (as predicted using various reference panels) and anti-tumour necrosis factor (anti-TNF) treatment response (change in erythrocyte sedimentation rate (ESR)) using 3158 European ancestry patients with rheumatoid arthritis.

Methods

The genetically regulated portion of gene expression was estimated in the full cohort of 3158 subjects (as well as within a subcohort consisting of 1575 UK patients) using the PrediXcan software package with three different reference panels. Estimated expression was tested for association with anti-TNF treatment response. As a replication/validation experiment, we also investigated the correlation between change in ESR with measured gene expression at the Interleukin 18 Receptor Accessory Protein (IL18RAP) gene in whole blood and synovial tissue, using an independent replication data set of patients receiving conventional synthetic disease modifying anti-rheumatic drugs, with directly measured (via RNA sequencing) gene expression.

Results

We found that predicted expression of IL18RAP showed a consistent signal of association with treatment response across the reference panels. In our independent replication data set, IL18RAP expression in whole blood showed correlation with the change in ESR between baseline and follow-up (r=−0.35, p=0.0091). Change in ESR was also correlated with the expression of IL18RAP in synovial tissue (r=−0.28, p=0.02).

Conclusion

Our results suggest that IL18RAP expression is worthy of further investigation as a potential predictor of treatment response in rheumatoid arthritis that is not specific to a particular drug type.

Using the Immunophenotype to Predict Response to Biologic Drugs in Rheumatoid Arthritis

Tumour necrosis factor (TNF)-α is a key mediator of inflammation in rheumatoid arthritis, and its discovery led to the development of highly successful anti-TNF therapy. Subsequently, other biologic drugs targeting immune pathways, namely interleukin-6 blockade, B cell depletion, and T cell co-stimulation blockade, have been developed. Not all patients respond to a biologic drug, leading to a knowledge gap between biologic therapies available and the confident prediction of response. So far, genetic studies have failed to uncover clinically informative biomarkers to predict response. Given that the targets of biologics are immune pathways, immunological study has become all the more pertinent. Furthermore, advances in single-cell technology have enabled the characterization of many leucocyte subsets. Studying the blood immunophenotype may therefore, define biomarker profiles relevant to each individual patient's disease and treatment outcome. This review summarises our current understanding of how immune biomarkers might be able to predict treatment response to biologic drugs.

Precision medicine in psoriatic arthritis: how should we select targeted therapies?

Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis associated with psoriasis. Patients manifest variable presentations with potential involvement of peripheral joints, spine, tendons, skin, and nails. There has been a rapid expansion in targeted treatment options for patients with PsA, but typically less than half of those who receive therapy achieve optimal treatment targets. Many patients respond to second-line or third-line biological therapies, but little evidence exists to guide the choice of therapeutics for each individual. At present, choice of therapy is driven by active clinical disease domains, clinician familiarity with existing treatments, and cost. Here, we review recent data that highlight the potential for personalised, or precision, medicine in PsA and other forms of inflammatory arthritis, noting that this research is still at a preliminary stage. In the future, a combination of detailed immunophenotyping and sophisticated statistical analyses should help to facilitate a personalised medicine approach in PsA, following examples from other clinical areas, such as oncology. This change in approach to the treatment of PsA has the potential to maximise outcomes for patients and to provide optimal therapies without delay.

Association of response to TNF inhibitors in rheumatoid arthritis with quantitative trait loci for CD40 and CD39

OBJECTIVES

We sought to investigate whether genetic effects on response to TNF inhibitors (TNFi) in rheumatoid arthritis (RA) could be localised by considering known genetic susceptibility loci for relevant traits and to evaluate the usefulness of these genetic loci for stratifying drug response.

METHODS

We studied the relation of TNFi response, quantified by change in swollen joint counts ( Δ SJC) and erythrocyte sedimentation rate ( Δ ESR) with locus-specific scores constructed from genome-wide assocation study summary statistics in 2938 genotyped individuals: 37 scores for RA; scores for 19 immune cell traits; scores for expression or methylation of 93 genes with previously reported associations between transcript level and drug response. Multivariate associations were evaluated in penalised regression models by cross-validation.

RESULTS

We detected a statistically significant association between Δ SJC and the RA score at the CD40 locus (p=0.0004) and an inverse association between Δ SJC and the score for expression of CD39 on CD4 T cells (p=0.00005). A previously reported association between CD39 expression on regulatory T cells and response to methotrexate was in the opposite direction. In stratified analysis by concomitant methotrexate treatment, the inverse association was stronger in the combination therapy group and dissipated in the TNFi monotherapy group. Overall, ability to predict TNFi response from genotypic scores was limited, with models explaining less than 1% of phenotypic variance.

CONCLUSIONS

The association with the CD39 trait is difficult to interpret because patients with RA are often prescribed TNFi after failing to respond to methotrexate. The CD39 and CD40 pathways could be relevant for targeting drug therapy.

Standardisation of synovial biopsy analyses in rheumatic diseases: a consensus of the EULAR Synovitis and OMERACT Synovial Tissue Biopsy Groups

Background

The aim of this global collaboration was to develop a consensual set of items for the analysis of synovial biopsies in clinical practice and translational research through the EULAR Synovitis Study Group (ESSG) and OMERACT Synovial Tissue Biopsy Group.

Methods

Participants were consulted through a modified Delphi method. Three sequential rounds occurred over 12 months. Members were sent a written questionnaire containing items divided into two parts. Items were identified and formulated based on a scoping review. The first part of the questionnaire referred to synovial biopsies in clinical practice including five subsections, and the second part to translational research with six subsections. Every participant was asked to score each item on a 5-point Likert scale. Items with a median score above 3.5 and a ≥ 70% agreement were selected for the next round. The last round was conducted orally at EULAR in June 2017.

Results

Twenty-seven participants from 19 centers were contacted by email. Twenty participants from 17 centers answered. Response rates for next rounds were 100%. For the first part relating to clinical practice, 20/44 items (45.5%) were selected. For the second part relating to translational research, 18/43 items (41.9%) were selected for the final set.

Conclusions

We herein propose a consensual set of analysis items to be used for synovial biopsies conducted in clinical practice and translational research.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1762-1) contains supplementary material, which is available to authorized users.

Prediction of treatment response in rheumatoid arthritis patients using genome-wide SNP data

Although a number of treatments are available for rheumatoid arthritis (RA), each of them shows a significant nonresponse rate in patients. Therefore, predicting a priori the likelihood of treatment response would be of great patient benefit. Here, we conducted a comparison of a variety of statistical methods for predicting three measures of treatment response, between baseline and 3 or 6 months, using genome-wide SNP data from RA patients available from the MAximising Therapeutic Utility in Rheumatoid Arthritis (MATURA) consortium. Two different treatments and 11 different statistical methods were evaluated. We used 10-fold cross validation to assess predictive performance, with nested 10-fold cross validation used to tune the model hyperparameters when required. Overall, we found that SNPs added very little prediction information to that obtained using clinical characteristics only, such as baseline trait value. This observation can be explained by the lack of strong genetic effects and the relatively small sample sizes available; in analysis of simulated and real data, with larger effects and/or larger sample sizes, prediction performance was much improved. Overall, methods that were consistent with the genetic architecture of the trait were able to achieve better predictive ability than methods that were not. For treatment response in RA, methods that assumed a complex underlying genetic architecture achieved slightly better prediction performance than methods that assumed a simplified genetic architecture.

Genome-wide association study of response to tumour necrosis factor inhibitor therapy in rheumatoid arthritis

Rheumatoid arthritis (RA) is characterised by chronic synovial joint inflammation. Treatment has been revolutionised by tumour necrosis factor alpha inhibitors (TNFi) but each available drug shows a significant non-response rate. We conducted a genome-wide association study of 1752 UK RA TNFi-treated patients to identify predictors of change in the Disease Activity Score 28 (DAS28) and subcomponents over 3–6 months. The rs7195994 variant at the FTO gene locus was associated with infliximab response when looking at a change in the swollen joint count (SJC28) subcomponent (p = 9.74 × 10⁻⁹). Capture Hi-C data show chromatin interactions in GM12878 cells between rs2540767, in high linkage disequilibrium with rs7195994 (R² = 0.9) and IRX3, a neighbouring gene of FTO. IRX3 encodes a transcription factor involved in adipocyte remodelling and is regarded as the obesity gene at the FTO locus. Importantly, the rs7195994 association remained significantly associated following adjustment for BMI. In addition, using capture Hi-C data we showed interactions between TNFi-response associated variants and 16 RA susceptibility variants.

Genome-wide association study of response to methotrexate in early rheumatoid arthritis patients

Methotrexate (MTX) monotherapy is a common first treatment for rheumatoid arthritis (RA), but many patients do not respond adequately. In order to identify genetic predictors of response, we have combined data from two consortia to carry out a genome-wide study of response to MTX in 1424 early RA patients of European ancestry. Clinical endpoints were change from baseline to 6 months after starting treatment in swollen 28-joint count, tender 28-joint count, C-reactive protein and the overall 3-component disease activity score (DAS28). No single nucleotide polymorphism (SNP) reached genome-wide statistical significance for any outcome measure. The strongest evidence for association was with rs168201 in NRG3 (p = 10^-7 for change in DAS28). Some support was also seen for association with ZMIZ1, previously highlighted in a study of response to MTX in juvenile idiopathic arthritis. Follow-up in two smaller cohorts of 429 and 177 RA patients did not support these findings, although these cohorts were more heterogeneous.

Prediction of response to methotrexate in rheumatoid arthritis

INTRODUCTION

Methotrexate (MTX) is the first-line disease-modifying drug of choice in controlling active inflammation of the synovium that characterises rheumatoid arthritis, a chronic autoimmune inflammatory condition. However, many patients do not respond to treatment with MTX or cannot tolerate the medication. Pre-treatment characteristics that predict response to MTX are, therefore, of particular interest and potential clinical utility. Areas covered: This narrative review seeks to cover various genotypic and phenotypic characteristics that have been investigated as predictors of treatment response to MTX in RA. Ovid Medline searches (1946 to January 2018) were carried out for 'methotrexate' and 'rheumatoid arthritis', in combination with relevant terms. All papers identified were English language, with abstracts. Relevant references were also reviewed. Expert commentary: Despite the introduction of biologic medication and targeted therapies, MTX is likely to remain the mainstay of RA treatment, largely due to its much cheaper cost. Development of a multifactorial predictive algorithm for response to MTX may be of clinical utility, as well as routine MTX drug level testing to improve medication adherence and persistence.