Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

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

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 ("SJC) and erythrocyte sedimentation rate ("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 "SJC and the RA score at the CD40 locus (p=0.0004) and an inverse association between "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

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

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe

An updated matrix to predict rapid radiographic progression of early rheumatoid arthritis patients: pooled analyses from several databases

OBJECTIVE: In early RA, some patients exhibit rapid radiographic progression (RRP) after one year, associated with poor functional prognosis. Matrices predicting this risk have been proposed, lacking precision or inadequately calibrated. We developed a matrix to predict RRP with high precision and adequate calibration. METHODS: Post-hoc analysis by pooling individual data from cohorts (ESPOIR and Leuven cohorts) and clinical trials (ASPIRE, BeSt and SWEFOT trials). Adult DMARD-naïve patients with active early RA for which the first therapeutic strategy after inclusion was to prescribe methotrexate or leflunomide were included. A logistic regression model to predict RRP was built. The best model was selected by 10-fold stratified cross-validation by maximizing the Area Under the Curve. Calibration and discriminatory power of the model were checked. The probabilities of RRP for each combination of levels of baseline characteristics were estimated. RESULTS: 1306 patients were pooled. 20.6% exhibited RRP. Four predictors were retained: rheumatoid factor positivity, presence of at least one RA erosion on X-rays, CRP > 30mg/l, number of swollen joints. The matrix estimates RRP probability for 36 combinations of level of baseline characteristics with a greatly enhanced precision compared with previously published matrices (95% CI: from ± 0.02 minimum to ± 0.08 maximum) and model calibration is excellent (P = 0.79). CONCLUSION: A matrix proposing RRP probability with high precision and excellent calibration in early RA was built. Although the matrix has moderate sensitivity and specificity, it is easily usable and may help physicians and patients to make treatment decisions in daily clinical practice.status: publishe

Low serum mannose-binding lectin level increases the risk of death due to pneumococcal infection

BACKGROUND: Previous studies have shown associations between low mannose-binding lectin (MBL) level or variant MBL2 genotype and sepsis susceptibility. However, MBL deficiency has not been rigorously defined, and associations with sepsis outcomes have not been subjected to multivariable analysis. METHODS: We reanalyzed MBL results in a large cohort with use of individual data from 4 studies involving a total of 1642 healthy control subjects and systematically defined a reliable deficiency cutoff. Subsequently, data were reassessed to extend previous MBL and sepsis associations, with adjustment for known outcome predictors. We reanalyzed individual data from 675 patients from 5 adult studies and 1 pediatric study of MBL and severe bacterial infection. RESULTS: XA/O and O/O MBL2 genotypes had the lowest median MBL concentrations. Receiver operating characteristic analysis revealed that an MBL cutoff value of 0.5 microg/mL was a reliable predictor of low-producing MBL2 genotypes (sensitivity, 82%; specificity, 82%; negative predictive value, 98%). MBL deficiency was associated with increased likelihood of death among patients with severe bacterial infection (odds ratio, 2.11; 95% confidence interval, 1.30-3.43). In intensive care unit-based studies, there was a trend toward increased risk of death among MBL-deficient patients (odds ratio, 1.58; 95% confidence interval, 0.90-2.77) after adjustment for Acute Physiology and Chronic Health Enquiry II score. The risk of death was increased among MBL-deficient patients with Streptococcus pneumoniae infection (odds ratio, 5.62; 95% confidence interval, 1.27-24.92) after adjustment for bacteremia, comorbidities, and age. CONCLUSIONS: We defined a serum level for MBL deficiency that can be used with confidence in future studies of MBL disease associations. The risk of death was increased among MBL-deficient patients with severe pneumococcal infection, highlighting the pathogenic significance of this innate immune defence protei

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Low serum mannose-binding lectin level increases the risk of death due to pneumococcal infection

BACKGROUND Previous studies have shown associations between low mannose-binding lectin (MBL) level or variant MBL2 genotype and sepsis susceptibility. However, MBL deficiency has not been rigorously defined, and associations with sepsis outcomes have not been subjected to multivariable analysis. METHODS We reanalyzed MBL results in a large cohort with use of individual data from 4 studies involving a total of 1642 healthy control subjects and systematically defined a reliable deficiency cutoff. Subsequently, data were reassessed to extend previous MBL and sepsis associations, with adjustment for known outcome predictors. We reanalyzed individual data from 675 patients from 5 adult studies and 1 pediatric study of MBL and severe bacterial infection. RESULTS XA/O and O/O MBL2 genotypes had the lowest median MBL concentrations. Receiver operating characteristic analysis revealed that an MBL cutoff value of 0.5 microg/mL was a reliable predictor of low-producing MBL2 genotypes (sensitivity, 82%; specificity, 82%; negative predictive value, 98%). MBL deficiency was associated with increased likelihood of death among patients with severe bacterial infection (odds ratio, 2.11; 95% confidence interval, 1.30-3.43). In intensive care unit-based studies, there was a trend toward increased risk of death among MBL-deficient patients (odds ratio, 1.58; 95% confidence interval, 0.90-2.77) after adjustment for Acute Physiology and Chronic Health Enquiry II score. The risk of death was increased among MBL-deficient patients with Streptococcus pneumoniae infection (odds ratio, 5.62; 95% confidence interval, 1.27-24.92) after adjustment for bacteremia, comorbidities, and age. CONCLUSIONS We defined a serum level for MBL deficiency that can be used with confidence in future studies of MBL disease associations. The risk of death was increased among MBL-deficient patients with severe pneumococcal infection, highlighting the pathogenic significance of this innate immune defence protein