Expression quantitative trait loci analysis in rheumatoid arthritis identifies tissue specific variants associated with severity and outcome.

OBJECTIVE: Genome-wide association studies have successfully identified more than 100 loci associated with susceptibility to rheumatoid arthritis (RA). However, our understanding of the functional effects of genetic variants in causing RA and their effects on disease severity and response to treatment remains limited. METHODS: In this study, we conducted expression quantitative trait locus (eQTL) analysis to dissect the link between genetic variants and gene expression comparing the disease tissue against blood using RNA-Sequencing of synovial biopsies (n=85) and blood samples (n=51) from treatment-naïve patients with RA from the Pathobiology of Early Arthritis Cohort. RESULTS: This identified 898 eQTL genes in synovium and genes loci in blood, with 232 genes in common to both synovium and blood, although notably many eQTL were tissue specific. Examining the HLA region, we uncovered a specific eQTL at HLA-DPB2 with the critical triad of single-nucleotide polymorphisms (SNPs) rs3128921 driving synovial HLA-DPB2 expression, and both rs3128921 and HLA-DPB2 gene expression correlating with clinical severity and increasing probability of the lympho-myeloid pathotype. CONCLUSIONS: This analysis highlights the need to explore functional consequences of genetic associations in disease tissue. HLA-DPB2 SNP rs3128921 could potentially be used to stratify patients to more aggressive treatment immediately at diagnosis.

Blood RNA-sequencing across the continuum of ANA-positive autoimmunity reveals insights into initiating immunopathology.

OBJECTIVE: Mechanisms underpinning clinical evolution to systemic lupus erythematosus (SLE) from preceding antinuclear antibodies (ANA) positivity are poorly understood. This study aimed to understand blood immune cell transcriptional signatures associated with subclinical ANA positivity, and progression or non-progression to SLE. METHODS: Bulk RNA-sequencing of peripheral blood mononuclear cells isolated at baseline from 35 ANA positive (ANA+) subjects with non-diagnostic symptoms was analysed using differential gene expression, weighted gene co-expression network analysis, deconvolution of cell subsets and functional enrichment analyses. ANA+ subjects, including those progressing to classifiable SLE at 12 months (n=15) and those with stable subclinical ANA positivity (n=20), were compared with 15 healthy subjects and 18 patients with SLE. RESULTS: ANA+ subjects demonstrated extensive transcriptomic dysregulation compared with healthy controls with reduced CD4+naïve T-cells and resting NK cells, but higher activated dendritic cells. B-cell lymphopenia was evident in SLE but not ANA+ subjects. Two-thirds of dysregulated genes were common to ANA+ progressors and non-progressors. ANA+ progressors showed elevated modular interferon signature in which constituent genes were inducible by both type I interferon (IFN-I) and type II interferon (IFN-II) in vitro. Baseline downregulation of mitochondrial oxidative phosphorylation complex I components significantly associated with progression to SLE but did not directly correlate with IFN modular activity. Non-progressors demonstrated more diverse cytokine profiles. CONCLUSIONS: ANA positivity, irrespective of clinical trajectory, is profoundly dysregulated and transcriptomically closer to SLE than to healthy immune function. Metabolic derangements and IFN-I activation occur early in the ANA+ preclinical phase and associated with diverging transcriptomic profiles which distinguish subsequent clinical evolution.

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

OBJECTIVES: Biologic DMARDs (bDMARDs) are widely used in patients with RA, but response to bDMARDs is heterogeneous. The objective of this work was to identify pretreatment proteomic biomarkers associated with RA clinical outcome measures in patients starting bDMARDs. METHODS: Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to generate spectral maps of sera from patients with RA before and after 3 months of treatment with the bDMARD etanercept. Protein levels were regressed against RA clinical outcome measures, i.e. 28-joint DAS (DAS28) and its subcomponents and DAS28 <2.6 (i.e. remission). The proteins with the strongest evidence for association were analysed in an independent, replication dataset. Finally, subnetwork analysis was carried out using the Disease Module Detection algorithm and biological plausibility of identified proteins was assessed by enrichment analysis. RESULTS: A total of 180 patients with RA were included in the discovery dataset and 58 in the validation dataset from a UK-based prospective multicentre study. Ten individual proteins were found to be significantly associated with RA clinical outcome measures. The association of T-complex protein 1 subunit η with DAS28 remission was replicated in an independent cohort. Subnetwork analysis of the 10 proteins from the regression analysis identified the ontological theme, with the strongest associations being with acute phase and acute inflammatory responses. CONCLUSION: This longitudinal study of 180 patients with RA commencing etanercept has identified several putative protein biomarkers of treatment response to this drug, one of which was replicated in an independent cohort.

Socioeconomic deprivation is associated with reduced response and lower treatment persistence with TNF inhibitors in rheumatoid arthritis.

OBJECTIVE: To investigate the association between socioeconomic deprivation and outcomes following TNF inhibitor (TNFi) treatment. METHODS: Individuals commencing their first TNFi in the British Society for Rheumatology Biologics Register for RA (BSRBR-RA) and Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS) cohort were included. Socioeconomic deprivation was proxied using the Index of Multiple Deprivation and categorized as 20% most deprived, middle 40% or 40% least deprived. DAS28-derived outcomes at 6 months (BSRBR-RA) and 3 months (BRAGGSS) were compared using regression models with the least deprived as referent. Risks of all-cause and cause-specific drug discontinuation were compared using Cox models in the BSRBR-RA. Additional analyses adjusted for lifestyle factors (e.g. smoking, BMI) as potential mediators. RESULTS: 16 085 individuals in the BSRBR-RA were included (mean age 56 years, 76% female), of whom 18%, 41% and 41% were in the most, middle and least deprived groups, respectively. Of 3459 included in BRAGGSS (mean age 57, 77% female), proportions were 22%, 36% and 41%, respectively. The most deprived group had 0.3-unit higher 6-month DAS28 (95% CI 0.22, 0.37) and were less likely to achieve low disease activity (odds ratio [OR] 0.76; 95% CI 0.68, 0.84) in unadjusted models. Results were similar for 3-month DAS28 (ß = 0.23; 95% CI 0.11, 0.36) and low disease activity (OR 0.77; 95% CI 0.63, 0.94). The most deprived were more likely to discontinue treatment (hazard ratio 1.18; 95% CI 1.12, 1.25), driven by ineffectiveness rather than adverse events. Adjusted estimates were generally attenuated. CONCLUSION: Socioeconomic deprivation is associated with reduced response to TNFi. Improvements in determinants of health other than lifestyle factors are needed to address socioeconomic inequities.

Pre-treatment calprotectin (MRP8/14) provides no added value to testing CRP alone in terms of predicting response to TNF inhibitors in rheumatoid arthritis in a post hoc analysis.

OBJECTIVES: The inflammatory protein calprotectin (MRP8/14) has been identified as a promising biomarker of treatment response in rheumatoid arthritis (RA). Our aim was to test MRP8/14 as a biomarker of response to tumour necrosis factor (TNF)-inhibitors in the largest RA cohort to date and to compare with C-reactive protein (CRP). METHODS: Serum MRP8/14 was measured in 470 patients with RA about to commence treatment with adalimumab (n=196) or etanercept (n=274). Additionally, MRP8/14 was measured in the 3-month sera of 179 adalimumab-treated patients. Response was determined using European League against Rheumatism (EULAR) response criteria calculated using the traditional 4-component (4C) DAS28-CRP and alternate validated versions using 3-component (3C) and 2-component (2C), clinical disease activity index (CDAI) improvement criteria and change in individual outcome measures. Logistic/linear regression models were fitted for response outcome. RESULTS: In the 3C and 2C models, patients with RA were 1.92 (CI: 1.04 to 3.54) and 2.03 (CI: 1.09 to 3.78) times more likely to be classified as EULAR responders if they had high (75th quartile) pre-treatment levels of MRP8/14 compared with low (25th quartile). No significant associations were observed for the 4C model. When only using CRP as a predictor, in the 3C and 2C analyses, patients above the 75th quartile were 3.79 (CI: 1.81 to 7.93) and 3.58 (CI: 1.74 to 7.35) times more likely to be EULAR responders and addition of MRP8/14 did not significantly improve model fit (p values=0.62 and 0.80, respectively). No significant associations were observed in the 4C analysis. Exclusion of CRP from the outcome measure (CDAI) did not result in any significant associations with MRP8/14 (OR 1.00 (CI: 0.99 to 1.01), suggesting that the associations were due to the correlation with CRP and that there is no additional utility of MRP8/14 beyond use of CRP in patients with RA starting TNFi therapy. CONCLUSION: Beyond correlation with CRP, we found no evidence to suggest that MRP8/14 explains additional variability in response to TNFi in patients with RA over and above CRP alone.

Non-trough adalimumab and certolizumab drug levels associated with a therapeutic EULAR response in adherent patients with rheumatoid arthritis.

OBJECTIVES: Interventions aimed at increasing TNF-α inhibitor serum drug levels (SDLs) may improve treatment response; however, previous studies suggesting SDL cut-offs have not accounted for treatment adherence. The aim of this study was to establish the relationship between adalimumab/certolizumab SDLs and EULAR good vs non-/moderate response and to define SDL cut-offs associated with good response in fully adherent patients. METHODS: In a prospective observational study, 475 patients with RA were treated with certolizumab (n = 192) or adalimumab (n = 283). At baseline and 3, 6 and 12 months, patients had 28-joint DAS, self-reported treatment adherence and SDLs measured. Fully adherent patients were analysed as a subgroup. Follow-up data at 3, 6 and 12 months were analysed separately. Median SDLs were compared in good vs non-/moderate response patients and receiver operating characteristics (ROC) curves were used to establish cut-off SDLs. RESULTS: Fully adherent good responders had significantly higher median adalimumab/certolizumab SDLs compared with non-/moderate responders (P = 0.04 and P = 0.0005, respectively). ROC analysis reported 3 month non-trough adalimumab SDLs discriminated good vs non-/moderate response with an area under the curve (AUC) of 0.63 (95% CI 0.52, 0.75), with a cut-off of 7.5 mg/l being 39.1% specific and 80.9% sensitive. Similarly, 3 month non-trough certolizumab SDLs discriminated good vs non-/moderate response with an AUC of 0.65 (95% CI 0.51, 0.78), with a cut-off of 26.0 mg/l being 43.9% specific and 77.8% sensitive. CONCLUSION: In fully adherent patients, higher SDLs are detected in good responders, suggesting that interventions to improve SDLs, such as encouraging adherence, could improve treatment response. The 3 month non-trough SDL cut-offs of 7.5 mg/l for adalimumab and 26.0 mg/l for certolizumab may be useful in clinical practice.

Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy.

BACKGROUND: No reliable biomarkers to predict response to TNF inhibitors (TNFi) in RA patients currently exist. The aims of this study were to replicate changes in gene co-expression modules that were previously reported in response to TNFi therapy in RA; to test if changes in module expression are specific to TNFi therapy; and to determine whether module expression transitions towards a disease-free state in responding patients. METHOD: Published transcriptomic data from the whole blood of disease-free controls (n = 10) and RA patients, treated with the TNFi adalimumab (n = 70) or methotrexate (n = 85), were studied. Treatment response was assessed using the EULAR response criteria following 3 or 6 months of treatment. Change in transcript expression between pre- and post-treatment was recorded for previously defined modules. Linear mixed models tested whether modular expression after treatment transitioned towards a disease-free state. RESULTS: For 25 of the 27 modules, change in expression between pre- and post-treatment in the adalimumab cohort replicated published findings. Of these 25 modules, six transitioned towards a disease-free state by 3 months (P < 0.05), irrespective of clinical response. One module (M3.2), related to inflammation and TNF biology, significantly correlated with response to adalimumab. Similar patterns of modular expression, with reduced magnitude, were observed in the methotrexate cohort. CONCLUSION: This study provides independent validation of changes in module expression in response to therapy in RA. However, these effects are not specific to TNFi. Further studies are required to determine whether specific modules could assist molecular classification of therapeutic response.

The use of missing values in proteomic data-independent acquisition mass spectrometry to enable disease activity discrimination.

MOTIVATION: Data-independent acquisition mass spectrometry allows for comprehensive peptide detection and relative quantification than standard data-dependent approaches. While less prone to missing values, these still exist. Current approaches for handling the so-called missingness have challenges. We hypothesized that non-random missingness is a useful biological measure and demonstrate the importance of analysing missingness for proteomic discovery within a longitudinal study of disease activity. RESULTS: The magnitude of missingness did not correlate with mean peptide concentration. The magnitude of missingness for each protein strongly correlated between collection time points (baseline, 3 months, 6 months; R = 0.95-0.97, confidence interval = 0.94-0.97) indicating little time-dependent effect. This allowed for the identification of proteins with outlier levels of missingness that differentiate between the patient groups characterized by different patterns of disease activity. The association of these proteins with disease activity was confirmed by machine learning techniques. Our novel approach complements analyses on complete observations and other missing value strategies in biomarker prediction of disease activity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Proteomic analysis to define predictors of treatment response to adalimumab or methotrexate in rheumatoid arthritis patients.

Seropositivity for anti-citrullinated peptide antibodies (ACPA) in patients with rheumatoid arthritis (RA), a chronic autoimmune arthritis, is associated with worse long-term disease outcomes. ACPA is ubiquitously tested in RA patients, but other autoantibodies exist (in both citrullinated and non-citrullinated form) which may provide additional information on RA subtypes and/or treatment response. We used a multiplex bead-based assay of 376 autoantibodies to test associations between these autoantibodies and treatment response in RA patients. Clusters of patients with similar autoantibody expression were defined and cluster membership was associated with treatment response. Thirty-four autoantibodies were differentially expressed in RA patients compared with healthy controls; citrullinated vimentin was associated with treatment response. A selection of citrullinated autoantibodies was found to be associated with treatment response in a subanalysis of ACPA-negative RA patients. Finer ACPA specificities in ACPA-negative RA patients may be predictive of treatment response and could represent a rich vein of future study.

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.

Adding value to real-world data: the role of biomarkers.

Adding biomarker information to real world datasets (e.g. biomarker data collected into disease/drug registries) can enhance mechanistic understanding of intra-patient differences in disease trajectories and differences in important clinical outcomes. Biomarkers can detect pathologies present early in disease potentially paving the way for preventative intervention strategies, which may help patients to avoid disability, poor treatment outcome, disease sequelae and premature mortality. However, adding biomarker data to real world datasets comes with a number of important challenges including sample collection and storage, study design and data analysis and interpretation. In this narrative review we will consider the benefits and challenges of adding biomarker data to real world datasets and discuss how biomarker data have added to our understanding of complex diseases, focusing on rheumatoid arthritis.

Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis.

OBJECTIVES: Identifying blood-based biomarkers that predict treatment response in RA is a clinical priority. We investigated differential DNA methylation as a candidate biomarker of response for the first-line drug used in RA, MTX. METHODS: DNA methylation was measured in DNA samples from individuals recruited to the Rheumatoid Arthritis Medication Study. Differentially methylated positions were compared between whole blood samples collected at baseline and at 4 weeks from patients who, by 6 months, had a good (n = 34) or poor response (n = 34) to MTX using linear modelling, adjusting for gender, age, cell composition, baseline 28-joint disease activity score (DAS28) and smoking status. Analyses also compared methylation with changes in DAS28 and changes in swollen joint count and tender joint count, and changes in CRP over the initial 6 months after MTX commencement. Differentially methylated positions showing significant differences with any response parameter were tested using pyrosequencing in an independent group of 100 patients from the Rheumatoid Arthritis Medication Study. RESULTS: In the discovery group, two CpG sites showed methylation changes at 4 weeks associated with clinical EULAR response by 6 months. Significant changes in methylation for three differentially methylated positions associated with change in tender joint counts, three with change in swollen joint count and a further four with change in CRP. Of the 12 CpGs, four showed replicated association in an independent dataset of samples from the Rheumatoid Arthritis Medication Study. CONCLUSION: These data represent an advance on current practice by contributing to a personalized medicine strategy allowing an escalation or change in therapy as early as 4 weeks.

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.

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.

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.

High frequency of antidrug antibodies and association of random drug levels with efficacy in certolizumab pegol-treated patients with rheumatoid arthritis: results from the BRAGGSS cohort.

OBJECTIVES: To evaluate (i) the association between random certolizumab drug levels, antidrug antibodies (ADAbs) and treatment response in patients with rheumatoid arthritis (RA); (ii) longitudinal factors associated with ADAbs and certolizumab drug levels. METHODS: This prospective cohort included 115 patients with RA treated with certolizumab. Serum samples were collected at 3, 6 and 12 months following treatment initiation. Drug levels and ADAbs were measured using ELISA and radioimmunoassay, respectively, at 3, 6 and 12 months. Disease Activity Score in 28 joints (DAS28) were measured at each visit and 12 months European League Against Rheumatism (EULAR) response was calculated. Patient self-reported adherence was collected longitudinally. Ordinal logistic regression and generalised estimating equation were used to test the association: (i) between drug levels, from serum sampled and treatment response; (ii) between ADAbs and drug levels; (iii) patient-centred factors and drug levels. RESULTS: ADAbs were detected in 37% (42/112 patients by 12 months). The presence of ADAbs were significantly associated with lower drug levels over 12 months (ß=-0.037, 95% CI -0.055 to 0.018, p<0.0001) but not independently with 12 months EULAR response (ß=0.0013 (95% CI -0.0032 to 0.00061), p=0.18). Drug level was associated with 12 months EULAR response (ß=0.032 (95% CI 0.0011 to 0.063), p=0.042). In the multivariate model, ADAb level and adherence were significantly associated with drug concentrations. CONCLUSIONS: This is the first study to demonstrate that higher certolizumab drug levels are associated with better 12 months EULAR response. ADAbs in certolizumab-treated patients with RA were detected at higher levels than previous studies and help determine the aetiology of a low drug level.

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.