Early treatment with, and time receiving, first disease-modifying antirheumatic drug predicts long-term function in patients with inflammatory polyarthritis

Molecular signature of methotrexate response among rheumatoid arthritis patients

Background

Methotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but failure of satisfying treatment response occurs in a significant proportion of patients. Here we present a longitudinal multi-omics study aimed at detecting molecular and cellular processes in peripheral blood associated with a successful methotrexate treatment of rheumatoid arthritis.

Methods

Eighty newly diagnosed patients with RA underwent clinical assessment and donated blood before initiation of MTX, and 3 months into treatment. Flow cytometry was used to describe cell types and presence of activation markers in peripheral blood, the expression of 51 proteins was measured in serum or plasma, and RNA sequencing was performed in peripheral blood mononuclear cells (PBMC). Response to treatment after 3 months was determined using the EULAR response criteria. We assessed the changes in biological phenotypes during treatment, and whether these changes differed between responders and non-responders with regression analysis. By using measurements from baseline, we also tried to find biomarkers of future MTX response or, alternatively, to predict MTX response.

Results

Among the MTX responders, (Good or Moderate according to EULAR treatment response classification, n = 60, 75%), we observed changes in 29 partly overlapping cell types proportions, levels of 13 proteins and expression of 38 genes during treatment. These changes were in most cases suppressions that were stronger among responders compared to non-responders. Within responders to treatment, we observed a suppression of FOXP3 gene expression, reduction of immunoglobulin gene expression and suppression of genes involved in cell proliferation. The proportion of many HLA-DR expressing T-cell populations were suppressed in all patients irrespective of clinical response, and the proportion of many IL21R+ T-cells were reduced exclusively in non-responders. Using only the baseline measurements we could not detect any biomarkers or prediction models that could predict response to MTX.

Conclusion

We conclude that a deep molecular and cellular phenotyping of peripheral blood cells in RA patients treated with methotrexate can reveal previously not recognized differences between responders and non-responders during 3 months of treatment with MTX. This may contribute to the understanding of MTX mode of action and explain non-responsiveness to MTX therapy.

Methotrexate Treatment of Newly Diagnosed RA Patients Is Associated With DNA Methylation Differences at Genes Relevant for Disease Pathogenesis and Pharmacological Action

Background

Methotrexate (MTX) is the first line treatment of rheumatoid arthritis (RA), and methylation changes in bulk T cells have been reported after treatment with MTX. We have investigated cell-type specific DNA methylation changes across the genome in naïve and memory CD4⁺ T cells before and after MTX treatment of RA patients. DNA methylation profiles of newly diagnosed RA patients (N=9) were assessed by reduced representation bisulfite sequencing.

Results

We found that MTX treatment significantly influenced DNA methylation levels at multiple CpG sites in both cell populations. Interestingly, we identified differentially methylated sites annotated to two genes; TRIM15 and SORC2, previously reported to predict treatment outcome in RA patients when measured in bulk T cells. Furthermore, several of the genes, including STAT3, annotated to the significant CpG sites are relevant for RA susceptibility or the action of MTX.

Conclusion

We detected CpG sites that were associated with MTX treatment in CD4⁺ naïve and memory T cells isolated from RA patients. Several of these sites overlap genetic regions previously associated with RA risk and MTX treatment outcome.

Possibilities for personalised medicine in rheumatoid arthritis: hype or hope

Knowledge of pathophysiology of rheumatoid arthritis (RA) has improved over the past decades, which resulted in new treatment options and strategies that led to better clinical outcomes. At the same time, we have come to understand that RA is a heterogeneous disease on a clinical as well as a pathophysiological level. Despite this heterogeneity, current management recommendations still adopt a ‘one-size-fits-all’ treatment approach, where ideally individualised treatment, or personalised medicine, is preferred. The first step towards personalised medicine in RA would be to designate different treatment strategies to distinct clinical or molecular phenotypes of patients. This viewpoint discusses current evidence and elaborates on future possibilities for personalised medicine in RA.

What Is the Persistence to Methotrexate in Rheumatoid Arthritis, and Does Machine Learning Outperform Hypothesis-Based Approaches to Its Prediction?

OBJECTIVE

The objectives of this study were to assess the 1-year persistence to methotrexate (MTX) initiated as the first ever conventional synthetic disease-modifying antirheumatic drug in new-onset rheumatoid arthritis (RA) and to investigate the marginal gains and robustness of the results by increasing the number and nature of covariates and by using data-driven, instead of hypothesis-based, methods to predict this persistence.

METHODS

Through the Swedish Rheumatology Quality Register, linked to other data sources, we identified a cohort of 5475 patients with new-onset RA in 2006-2016 who were starting MTX monotherapy as their first disease-modifying antirheumatic drug. Data on phenotype at diagnosis and demographics were combined with increasingly detailed data on medical disease history and medication use in four increasingly complex data sets (48-4162 covariates). We performed manual model building using logistic regression. We also performed five different machine learning (ML) methods and combined the ML results into an ensemble model. We calculated the area under the receiver operating characteristic curve (AUROC) and made calibration plots. We trained on 90% of the data, and tested the models on a holdout data set.

RESULTS

Of the 5475 patients, 3834 (70%) remained on MTX monotherapy 1 year after treatment start. Clinical RA disease activity and baseline characteristics were most strongly associated with the outcome. The best manual model had an AUROC of 0.66 (95% confidence interval [CI] 0.60-0.71). For the ML methods, Lasso regression performed best (AUROC = 0.67; 95% CI 0.62-0.71).

CONCLUSION

Approximately two thirds of patients with early RA who start MTX remain on this therapy 1 year later. Predicting this persistence remains a challenge, whether using hypothesis-based or ML models, and may yet require additional types of data.

The Pretreatment Gut Microbiome Is Associated With Lack of Response to Methotrexate in New-Onset Rheumatoid Arthritis

OBJECTIVE

Although oral methotrexate (MTX) remains the anchor drug for rheumatoid arthritis (RA), up to 50% of patients do not achieve a clinically adequate outcome. In addition, there is a lack of prognostic tools for treatment response prior to drug initiation. This study was undertaken to investigate whether interindividual differences in the human gut microbiome can aid in the prediction of MTX efficacy in new-onset RA.

METHODS

We performed 16S ribosomal RNA gene and shotgun metagenomic sequencing on the baseline gut microbiomes of drug-naive patients with new-onset RA (n = 26). Results were validated in an additional independent cohort (n = 21). To gain insight into potential microbial mechanisms, we conducted ex vivo experiments coupled with metabolomics analysis to evaluate the association between microbiome-driven MTX depletion and clinical response.

RESULTS

Our analysis revealed significant associations of the abundance of gut bacterial taxa and their genes with future clinical response (q < 0.05), including orthologs related to purine and MTX metabolism. Machine learning techniques were applied to the metagenomic data, resulting in a microbiome-based model that predicted lack of response to MTX in an independent group of patients. Finally, MTX levels remaining after ex vivo incubation with distal gut samples from pretreatment RA patients significantly correlated with the magnitude of future clinical response, suggesting a possible direct effect of the gut microbiome on MTX metabolism and treatment outcomes.

CONCLUSION

Taken together, these findings are the first step toward predicting lack of response to oral MTX in patients with new-onset RA and support the value of the gut microbiome as a possible prognostic tool and as a potential target in RA therapeutics.

The Prospective Study of Epigenetic Regulatory Profiles in Sport and Exercise Monitored Through Chromosome Conformation Signatures

The integration of genetic and environmental factors that regulate the gene expression patterns associated with exercise adaptation is mediated by epigenetic mechanisms. The organisation of the human genome within three-dimensional space, known as chromosome conformation, has recently been shown as a dynamic epigenetic regulator of gene expression, facilitating the interaction of distal genomic regions due to tight and regulated packaging of chromosomes in the cell nucleus. Technological advances in the study of chromosome conformation mean a new class of biomarker-the chromosome conformation signature (CCS)-can identify chromosomal interactions across several genomic loci as a collective marker of an epigenomic state. Investigative use of CCSs in biological and medical research shows promise in identifying the likelihood that a disease state is present or absent, as well as an ability to prospectively stratify individuals according to their likely response to medical intervention. The association of CCSs with gene expression patterns suggests that there are likely to be CCSs that respond, or regulate the response, to exercise and related stimuli. The present review provides a contextual background to CCS research and a theoretical framework discussing the potential uses of this novel epigenomic biomarker within sport and exercise science and medicine.

Association of a Type 2-Polarized T Cell Phenotype With Methotrexate Nonresponse in Patients With Rheumatoid Arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a chronic inflammatory disease mediated through complex immunologic pathways. Among RA patients receiving low-dose methotrexate (MTX) monotherapy, approximately one-half exhibit a meaningful clinical response within the first 6 months of starting treatment. Whether baseline immune phenotypes differ between subsequent MTX responders and nonresponders is unknown. This study utilized comprehensive T cell immunophenotyping to identify specific immunologic pathways associated with MTX-nonresponsive joint inflammation in patients with RA.

METHODS

In total, 32 patients with recent-onset RA were treated with MTX therapy. After 6 months, 15 patients were categorized as responders and 17 as nonresponders. Comprehensive blood T cell immunophenotyping, using multiparameter immunofluorescence flow cytometry analyses, was performed at baseline and following 6 months of treatment.

RESULTS

Baseline measures of disease activity (Disease Activity Score in 28 joints [DAS28], C-reactive protein level, and erythrocyte sedimentation rate) did not differ between MTX responders and nonresponders following MTX treatment. Frequencies of CD4+ and CD8+ T cells were skewed to favor higher CD4:CD8 T cell ratios in MTX responders compared to nonresponders (P < 0.05). The proportion of inducible costimulator-expressing Treg cells was significantly greater among MTX nonresponders. Interleukin-13 (IL-13)-producing, but not interferon-γ- or IL-17-producing, CD4+ effector memory T (Tem) cells were significantly more frequent in MTX nonresponders (P < 0.05). The ratio of IL-13+:IL-17+ Tem cells among CD4+ Tem cells was 1.9-fold higher in MTX nonresponders compared to responders (P < 0.05). Both the CD4:CD8 T cell ratio and the frequency of IL-13+CD4+ Tem cells correlated with changes in the DAS28 score following MTX treatment, whereas T cell expression of immune checkpoint inhibitor markers (CTLA-4, programmed death 1, and T cell immunoglobulin and mucin domain-containing protein 3) did not differ between MTX responders and nonresponders.

CONCLUSION

We observed a bias toward type 2-polarized T cell inflammatory responses in the peripheral blood of MTX-nonresponsive RA patients. Targeting the IL-13+CD4+ T cell pathway could be a new therapeutic strategy in RA patients whose disease remains resistant to MTX.

Mortality is increased in patients with rheumatoid arthritis or diabetes compared to the general population - the Nord-Trøndelag Health Study

Persons with rheumatoid arthritis (RA) or diabetes have increased risk of cardiovascular disease (CVD) and higher death rates compared to the general population. This study used data from the population-based Nord-Trøndelag Health Study (HUNT) and the Norwegian Cause of Death registry to compare all-cause mortality rates for RA or diabetes patients to the general population. We used Cox regression with age as time variable, adjusting for sex, smoking, body mass index, hypertension, total cholesterol, creatinine and previous CVD. To achieve proportional hazards, an interaction term with an age group variable (≤75 years or >75 years) was included for diabetes, smoking and previous CVD. Median follow-up was 18.1 years. Mortality occurred for 123 (32%) of the RA patients, 1,280 (44%) of the diabetes patients, 17 (52%) of the patients with both diseases and 11,641 (18%) of the controls. Both diseases were associated with statistically significantly increased mortality rates. The hazard ratio (HR) for RA was 1.24 (95% CI: 1.03-1.44). The HR of diabetes was 1.82 (1.60-2.04) for individuals ≤75 years old and 1.49 (1.39-1.59) for individuals >75 years. Diabetes had a significantly higher HR for death than RA for participants ≤75 years, but not significantly different for participants >75 years.

Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis

Objective

Approximately 30–40% of rheumatoid arthritis (RA) patients who are initially started on low‐dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response.

Methods

RA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed.

Results

Based on the ratio of transcript values (i.e., the difference in log₂‐transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2‐regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10⁻²⁵) and at 4 weeks after treatment initiation (P = 4.9 × 10⁻²⁸).

Conclusion

Testing for changes in gene expression between pretreatment and 4 weeks post–treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX.

Maximin Projection Learning for Optimal Treatment Decision with Heterogeneous Individualized Treatment Effects

A saline feature of data from clinical trials and medical studies is inhomogeneity. Patients not only differ in baseline characteristics, but also the way they respond to treatment. Optimal individualized treatment regimes are developed to select effective treatments based on patient's heterogeneity. However, the optimal treatment regime might also vary for patients across different subgroups. In this paper, we mainly consider patient's heterogeneity caused by groupwise individualized treatment effects assuming the same marginal treatment effects for all groups. We propose a new maximin-projection learning for estimating a single treatment decision rule that works reliably for a group of future patients from a possibly new subpopulation. Based on estimated optimal treatment regimes for all subgroups, the proposed maximin treatment regime is obtained by solving a quadratically constrained linear programming (QCLP) problem, which can be efficiently computed by interior-point methods. Consistency and asymptotic normality of the estimator is established. Numerical examples show the reliability of the proposed methodology.

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.

Have the 10-year outcomes of patients with early inflammatory arthritis improved in the new millennium compared with the decade before? Results from the Norfolk Arthritis Register

Objective

To compare the 10-year outcome (disease activity, disability, mortality) of two cohorts of patients with inflammatory polyarthritis (IP) recruited 10 years apart.

Methods

Patients with IP were recruited to the Norfolk Arthritis Register from 1990 to 1994 (cohort 1 (C1)) and from 2000 to 2004 (cohort 2 (C2)). Demographic and clinical data were collected at baseline and at years 1, 2, 3, 5, 7 and 10. Longitudinal disease activity (swollen/tender 51 joint counts (SJC51/TJC51)) and disability (Health Assessment Questionnaire (HAQ)) were compared between the cohorts using population-average negative binomial regression and generalised estimating equation analysis, respectively. Risk of 10-year mortality was compared between cohorts using Cox models. Risk of cardiovascular disease (CVD) mortality was compared between cohorts using competing risks analysis. Mortality rate ratios (MRR), adjusted for changes in mortality risk of the general population, were calculated using Poisson regression.

Results

In total 1653 patients were recruited (C1=1022, C2=631). Patients in C2 had 17% lower SJC51 than C1 over 10 years (95% CI −23% to −10%), whereas TJC51 and HAQ were comparable. C2 patients had reduced risk of all-cause and CVD mortality compared with C1 (all-cause: HR 0.72, 95% CI 0.56 to 0.95; CVD: subhazard ratio 0.58, 95% CI 0.37 to 0.93). After accounting for changes in mortality risk in the general population, the difference in mortality was non-significant (all-cause: MRR 0.78, 95% CI 0.56 to 1.10; CVD: MRR 0.77, 95% CI 0.48 to 1.24).

Conclusion

Disease activity significantly improved in the new millennium, whereas disability and mortality were unchanged.

Chromosome conformation signatures define predictive markers of inadequate response to methotrexate in early rheumatoid arthritis

Background

There is a pressing need in rheumatoid arthritis (RA) to identify patients who will not respond to first-line disease-modifying anti-rheumatic drugs (DMARD). We explored whether differences in genomic architecture represented by a chromosome conformation signature (CCS) in blood taken from early RA patients before methotrexate (MTX) treatment could assist in identifying non-response to DMARD and, whether there is an association between such a signature and RA specific expression quantitative trait loci (eQTL).

Methods

We looked for the presence of a CCS in blood from early RA patients commencing MTX using chromosome conformation capture by EpiSwitch™. Using blood samples from MTX responders, non-responders and healthy controls, a custom designed biomarker discovery array was refined to a 5-marker CCS that could discriminate between responders and non-responders to MTX. We cross-validated the predictive power of the CCS by generating 150 randomized groups of 59 early RA patients (30 responders and 29 non-responders) before MTX treatment. The CCS was validated using a blinded, independent cohort of 19 early RA patients (9 responders and 10 non-responders). Last, the loci of the CCS markers were mapped to RA-specific eQTL.

Results

We identified a 5-marker CCS that could identify, at baseline, responders and non-responders to MTX. The CCS consisted of binary chromosome conformations in the genomic regions of IFNAR1, IL-21R, IL-23, CXCL13 and IL-17A. When tested on a cohort of 59 RA patients, the CCS provided a negative predictive value of 90.0% for MTX response. When tested on a blinded independent validation cohort of 19 early RA patients, the signature demonstrated a true negative response rate of 86 and a 90% sensitivity for detection of non-responders to MTX. Only conformations in responders mapped to RA-specific eQTL.

Conclusions

Here we demonstrate that detection of a CCS in blood in early RA is able to predict inadequate response to MTX with a high degree of accuracy. Our results provide a proof of principle that a priori stratification of response to MTX is possible, offering a mechanism to provide alternative treatments for non-responders to MTX earlier in the course of the disease.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1387-9) contains supplementary material, which is available to authorized users.

Capillary electrophoresis-laser-induced fluorescence (CE-LIF)-based immunoassay for quantifying antibodies against cyclic citrullinated peptides

CE-LIF based immunoassay to quantify antibodies against cyclic citrullinated peptides in rheumatoid arthritis patients.

Twenty-Year Outcome and Association Between Early Treatment and Mortality and Disability in an Inception Cohort of Patients With Rheumatoid Arthritis: Results From the Norfolk Arthritis Register

Objective

To describe the outcome in patients with rheumatoid arthritis (RA) over 20 years from symptom onset, and to assess the association between early treatment (with disease‐modifying antirheumatic drugs/steroids) and mortality and disability during follow‐up.

Methods

Patients recruited to the Norfolk Arthritis Register (NOAR) between 1990 and 1994 who met the 2010 American College of Rheumatology/European League Against Rheumatism RA criteria at baseline were included in this analysis. Demographic and clinical variables were collected at baseline and at years 1–3, 5, 7, 10, 15, and 20. Disease activity (swollen joint count [SJC]/tender joint count [TJC]), disability (Health Assessment Questionnaire disability index [HAQ DI]), and mortality over 20 years were determined. Associations between treatment group (early treatment [ET], treatment ≤6 months after symptom onset; late treatment [LT], treatment >6 months after symptom onset; never treatment [NT], no treatment) and mortality and disability were assessed using weighted pooled logistic regression and weighted multilevel mixed‐effects linear regression, respectively. Inverse weights were used to account for confounding by indication and censoring.

Results

This study included 602 patients with RA (median age 56 years [interquartile range 44–68 years]; 65.9% women). The median SJCs and TJCs were low during the follow‐up period (1–3 swollen joints and 3–6 tender joints). The median HAQ DI score increased after year 1 but remained at low/moderate levels (median 1.25 after year 10). The risk of mortality was reduced in the ET and LT groups compared with that in the NT group. The ET group and the NT group had comparable HAQ DI scores during the follow‐up period (β = 0.03, 95% confidence interval [95% CI] −0.06, 0.12), while the HAQ DI score was increased in the LT group (for LT versus NT, β = 0.10 [95% CI 0.02, 0.17]).

Conclusion

The results of this study indicate the importance of early treatment with regard to the long‐term outcomes in patients with RA.

The predictive value of serum S100A9 and response to etanercept is not confirmed in a large UK rheumatoid arthritis cohort

Objective

The aim was to correlate protein concentrations of S100A9 in pretreatment serum samples with response to the tumour-necrosis factor (TNF) inhibitor drugs etanercept in a large UK replication cohort.

Methods

Pretreatment serum samples from patients with RA (n = 236) about to commence treatment with etanercept had S100A9 serum concentration measured using an ELISA. Following the experimental procedure, S100A9 concentrations were analysed with respect to EULAR response.

Results

No evidence of association between S100A9 concentration and EULAR response to the TNF-inhibitor biologic drug etanercept was observed following multinomial logistic regression analysis (non-responder vs moderate responder, P = 0.957; and non-responder vs good responder, P = 0.316). Furthermore, no significant associations were observed when correlating pretreatment S100A9 concentrations with clinical parameters of disease activity (P > 0.05).

Conclusion

In the largest replication cohort conducted to date, no evidence for association was observed to support the use of S100A9 as a clinical biomarker predictive of response to the TNF-inhibitor biologic drug etanercept.

DNA methylation at diagnosis is associated with response to disease-modifying drugs in early rheumatoid arthritis

AIM

A proof-of-concept study to explore whether DNA methylation at first diagnosis is associated with response to disease-modifying antirheumatic drugs (DMARDs) in patients with early rheumatoid arthritis (RA).

PATIENTS & METHODS

DNA methylation was quantified in T-lymphocytes from 46 treatment-naive patients using HumanMethylation450 BeadChips. Treatment response was determined in 6 months using the European League Against Rheumatism (EULAR) response criteria.

RESULTS

Initial filtering identified 21 cytosine-phosphate-guanines (CpGs) that were differentially methylated between responders and nonresponders. After conservative adjustment for multiple testing, six sites remained statistically significant, of which four showed high sensitivity and/or specificity (≥75%) for response to treatment. Moreover, methylation at two sites in combination was the strongest factor associated with response (80.0% sensitivity, 90.9% specificity, AUC 0.85).

CONCLUSION

DNA methylation at diagnosis is associated with disease-modifying antirheumatic drug treatment response in early RA.

Genetic and genomic markers of anti-TNF treatment response in rheumatoid arthritis

Despite the success of anti-TNF drugs in the treatment of rheumatoid arthritis, a significant rate of nonresponse remains. Current clinical factors confer little power for predicting response and, in current practice, an unsatisfactory ‘trial and error’ approach governs therapeutic decisions. Candidate gene and unbiased genome-wide investigations have sought to identify genetic biomarkers that predict who will respond to anti-TNF drugs before the drug is administered. To date, few studies have yielded robust associations; herein, we discuss currently identified associations and the issues that need to be addressed in future investigations including insufficient power and an inadequate measure of disease activity. The potential for alternative predictors of anti-TNF therapy response from transcriptomic and epigenetic data will also be explored.

Third Annual Open Meeting of the UK Pharmacogenomics and Stratified Medicine Network Conference

Third Annual Open Meeting of the UK Pharmacogenetics and Stratified Medicine Network

14 January 2015, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK

The third Annual Open Meeting of the UK Pharmacogenetics and Stratified Medicine Network was held on 14 January 2015 in association with the Wellcome Trust on the Wellcome Trust Genome Campus at Hinxton, Cambridge, UK. In the morning, speakers from Cancer Research UK, the Medical Research Council, Genomics England, Innovate UK (formerly TSB) and the Department of Health described the current major projects they are funding. In the afternoon, speakers from various universities around the United Kingdom presented data on pharmacogenetics and stratified medicine research covering diverse disease areas including cancers, warfarin dosing, Gaucher disease and rheumatoid arthritis.

Health Assessment Questionnaire disability progression in early rheumatoid arthritis: systematic review and analysis of two inception cohorts

Objective

The Health Assessment Questionnaire is widely used for patients with inflammatory polyarthritis (IP) and its subset, rheumatoid arthritis (RA). In this study, we evaluated the progression of HAQ scores in RA (i) by systematically reviewing the published literature on the methods used to assess changes in functional disability over time and (ii) to study in detail HAQ progression in two large prospective observational studies from the UK.

Methods

Data from two large inception cohorts, ERAS and NOAR, were studied to determine trajectories of HAQ progression over time by applying latent class growth models (LCGMs) to each dataset separately. Age, sex, baseline DAS28, symptom duration, rheumatoid factor, fulfilment of the 1987 ACR criteria and socio-economic status (SES) were included as potential predictors of HAQ trajectory subgroup membership.

Results

The literature search identified 49 studies showing that HAQ progression has mainly been based on average changes in the total study population. In the HAQ progression study, a LCGM with four HAQ trajectory subgroups was selected as providing the best fit in both cohorts. In both the cohorts, older age, female sex, longer symptom duration, fulfilment of the 1987 ACR criteria, higher DAS28 and lower SES were associated with increased likelihood of membership of subgroups with worse HAQ progression.

Conclusion

Four distinct HAQ trajectory subgroups were derived from the ERAS and NOAR cohorts. The fact that the subgroups identified were nearly identical supports their validity. Identifying distinct groups of patients who are at risk of poor functional outcome may help to target therapy to those who are most likely to benefit.

Detecting the violation of variance homogeneity in mixed models

Mixed-effects models are increasingly used in many areas of applied science. Despite their popularity, there is virtually no systematic approach for examining the homogeneity of the random-effects covariance structure commonly assumed for such models. We propose two tests for evaluating the homogeneity of the covariance structure assumption across subjects: one is based on the covariance matrices computed from the fitted model and the other is based on the empirical variation computed from the estimated random effects. We used simulation studies to compare performances of the two tests for detecting violations of the homogeneity assumption in the mixed-effects models and showed that they were able to identify abnormal clusters of subjects with dissimilar random-effects covariance structures; in particular, their removal from the fitted model might change the signs and the magnitudes of important predictors in the analysis. In a case study, we applied our proposed tests to a longitudinal cohort study of rheumatoid arthritis patients and compared their abilities to ascertain whether the assumption of covariance homogeneity for subject-specific random effects holds.

Genetic and epigenetic predictors of responsiveness to treatment in RA

Methotrexate and TNF-blocking agents are the DMARDs most commonly prescribed for the treatment of rheumatoid arthritis (RA). However, not all patients treated with these nonbiologic and biologic DMARDs respond satisfactorily and few predictors of treatment efficacy have been identified, despite the fact that these therapies have now been available for many years. Many studies have investigated genetic factors that might predict patient responsiveness to therapies used to treat RA, and epigenetic studies regarding response to treatment are expected to accumulate in the literature in the near future. Herein, we review the advances in identifying genetic and epigenetic predictors of therapeutic responses to methotrexate and/or TNF inhibitors in RA that have been made to date, and highlight important considerations for future studies, such as the need for an improved, preferably biological, outcome measure reflecting response to treatment.

Effectiveness of a clinical practice intervention in early rheumatoid arthritis

OBJECTIVE

To compare the outcome of early rheumatoid arthritis (RA) patients in a country where early clinics were established versus the outcome of patients in nonprotocolized clinics.

METHODS

We compared 2 multicenter cohorts: an RA cohort derived from an early arthritis registry set in 36 reference hospitals in which a specific intervention was established (Evaluation of a Model for Arthritis Care in Spain [SERAP]), and a historical control cohort of patients with early RA attending 34 rheumatology departments (Prognosis in Rheumatoid Arthritis [PROAR] cohort). Effectiveness was tested by comparing the change in the Disease Activity Score in 28 joints (DAS28), the change in the Health Assessment Questionnaire (HAQ), and the change in the Sharp/van der Heijde radiologic score using marginal structural models.

RESULTS

A total of 161 early RA patients were recruited in the PROAR cohort and 447 in the SERAP cohort. Being a SERAP patient was inversely correlated with activity, resulting in a decrease of -0.24 (95% confidence interval [95% CI] -0.39, -0.08) units in the population average of the DAS28 after adjustment was made. Moreover, intervention may be seen as a protective factor of radiologic damage, with a decrease of -0.05 (95% CI -0.09, -0.01) units in the logarithm of the total Sharp/van der Heijde score. On the other hand, a decrease in functional impairment was detected, but intervention was not statistically associated with HAQ changes.

CONCLUSION

Preventing major radiographic progression in a 2-year term inside structured and organized special programs for the management of disease, such as early arthritis clinics, are effective compared to nonprotocolized referrals, treatment, and followup.

Reduction of long-term disability in inflammatory polyarthritis by early and persistent suppression of joint inflammation: results from the Norfolk Arthritis Register

Objective

To test the predictive ability of remission in terms of long-term disability in patients with recent-onset inflammatory polyarthritis (IP).

Methods

Consecutive patients with early IP, recruited between 1990 and 1994 (first cohort) and 2000 and 2004 (second cohort), were included in this study. Remission was defined as the absence of clinically detectable joint inflammation on a 51–joint count. In additional analyses, less stringent definitions of remission were used based on the 40– and 28–joint counts. Remission was assessed at 1, 2, and 3 years after inclusion. A 5-year Health Assessment Questionnaire score ≥1 (moderate disability) was chosen as the primary outcome measure.

Results

A total of 841 and 498 patients from the first and second cohorts, respectively, completed 5 years of followup. In the first cohort, patients with at least 1 episode of remission had lower odds of 5-year disability (odds ratio [OR] 0.26, 95% confidence interval [95% CI] 0.17–0.41). The number of times in remission correlated with the odds of disability, with a mean decrease in the probability of disability of ∼64% for each additional time point in remission (OR 0.38, 95% CI 0.28–0.52). The time until first remission was not associated with functional disability. Remission according to less stringent criteria showed a weaker protection against future disability. Similar results were found in the second cohort.

Conclusion

Patients with IP achieving a state of sustained remission early are less likely to show long-term deterioration of function compared with patients who do not achieve remission. The most persistent remission under the most stringent definition of remission has the lowest probability of long-term disability.

Imaging of polymyalgia rheumatica: indications on its pathogenesis, diagnosis and prognosis

OBJECTIVES

Imaging is one of the most appealing techniques to explore PMR, a disease whose causes, development mechanisms and anatomical targets of inflammatory damage are still scarcely known. This review is concerned with an appraisal of PMR with different imaging modalities with a view to highlighting possible clues to its pathogenesis, diagnosis and prognosis.

METHODS

A systematic literature research was performed searching PubMed until July 2010. The Cochrane Library was searched for the relevant reviews, and the abstracts of the ACR and European League Against Rheumatism congresses of the period 2005-10 were reviewed.

RESULTS

A total of 1059 papers were retrieved, 46 of which were selected at the end of the review process; 6 of them were concerned with two different imaging techniques. Of these papers, 6 (11.5%) were concerned with conventional radiology; 8 (15.4%) with scintigraphy; 17 (32.7%) with ultrasonography (US); 15 (28.8%) with MRI; and 6 (11.5%) with PET. MRI, US and PET appeared to be the most promising imaging techniques. Bilateral subacromial bursitis, biceps long head tenosynovitis and trochanteric bursitis were particularly consistent findings. In addition, MRI and PET showed interspinous bursitis and PET frequently showed large-vessel vasculitis. Few papers have addressed the role of imaging for diagnosis, differential diagnosis and prognosis of PMR.

CONCLUSIONS

Imaging plays an important role in the comprehensive evaluation of PMR, including its pathogenesis, diagnosis and prognosis. Most of its potential is still unexplored, which fact should stimulate further research.

In patients with early inflammatory polyarthritis, ACPA positivity, younger age and inefficacy of the first non-biological DMARD are predictors for receiving biological therapy: results from the Norfolk Arthritis Register

Objectives

To identify baseline disease-related predictors in patients with early inflammatory polyarthritis (IP) for starting subsequent biological therapy and to determine if patients who failed their first non-biological disease-modifying antirheumatic drug (DMARD) within 6 months were more likely to need biological therapy.

Methods

Patients with early IP recruited between 1990 and 1994 (cohort 1) and between 2000 and 2004 (cohort 2) in the Norfolk Arthritis Register were included in this study. The association between possible predictors with the start of biological therapy was assessed using Cox proportional hazards regression models.

Results

32/407 (7.9%) patients in cohort 1 and 45/416 (10.8%) patients in cohort 2 received biological therapy during follow-up. In both cohorts, anti-citrullinated protein antibody (ACPA) positivity (cohort 1, HR 7.62, 95% CI 2.46 to 23.58; cohort 2, HR 4.68, 95% CI 2.23 to 9.78) was the strongest predictor for starting biological therapy. In cohort 2, younger patients (HR 0.97, 95% CI 0.95 to 0.99) and patients who failed their first non-biological DMARD within 6 months due to inefficacy were also more likely to receive biological therapy (HR 2.35, 95% CI 1.05 to 5.27).

Conclusion

Patients with early IP who are ACPA positive, are younger or who fail their first non-biological DMARD due to inefficacy within 6 months are more likely to need biological therapy.