Activation of naïve CD4+ T cells re-tunes STAT1 signaling to deliver unique cytokine responses in memory CD4+ T cells.

The cytokine IL-6 controls the survival, proliferation and effector characteristics of lymphocytes through activation of the transcription factors STAT1 and STAT3. While STAT3 activity is an ever-present feature of IL-6 signaling in CD4+ T cells, prior activation via the T cell antigen receptor limits IL-6's control of STAT1 in effector and memory populations. Here we found that phosphorylation of STAT1 in response to IL-6 was regulated by the tyrosine phosphatases PTPN2 and PTPN22 expressed in response to the activation of naïve CD4+ T cells. Transcriptomics and chromatin immunoprecipitation-sequencing (ChIP-seq) of IL-6 responses in naïve and effector memory CD4+ T cells showed how the suppression of STAT1 activation shaped the functional identity and effector characteristics of memory CD4+ T cells. Thus, tyrosine phosphatases induced by the activation of naïve T cells determine the way activated or memory CD4+ T cells sense and interpret cytokine signals.

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

Senescent endothelial cells promote pathogenic neutrophil trafficking in inflamed tissues.

Cellular senescence is a hallmark of advanced age and a major instigator of numerous inflammatory pathologies. While endothelial cell (EC) senescence is aligned with defective vascular functionality, its impact on fundamental inflammatory responses in vivo at single-cell level remain unclear. To directly investigate the role of EC senescence on dynamics of neutrophil-venular wall interactions, we applied high resolution confocal intravital microscopy to inflamed tissues of an EC-specific progeroid mouse model, characterized by profound indicators of EC senescence. Progerin-expressing ECs supported prolonged neutrophil adhesion and crawling in a cell autonomous manner that additionally mediated neutrophil-dependent microvascular leakage. Transcriptomic and immunofluorescence analysis of inflamed tissues identified elevated levels of EC CXCL1 on progerin-expressing ECs and functional blockade of CXCL1 suppressed the dysregulated neutrophil responses elicited by senescent ECs. Similarly, cultured progerin-expressing human ECs exhibited a senescent phenotype, were pro-inflammatory and prompted increased neutrophil attachment and activation. Collectively, our findings support the concept that senescent ECs drive excessive inflammation and provide new insights into the mode, dynamics, and mechanisms of this response at single-cell level.

Diversity of NF-κB signalling and inflammatory heterogeneity in Rheumatic Autoimmune Disease.

Systemic Autoimmune Rheumatic Diseases, including Rheumatoid Arthritis, Systemic Lupus Erythematosus and Sjogren's syndrome, are characterised by a loss of immune tolerance and chronic inflammation. There is marked heterogeneity in clinical and molecular phenotypes in each condition, and the aetiology of these is unclear. NF-κB is an inducible transcription factor that is critical in the physiological inflammatory response, and which has been implicated in chronic inflammation. Genome-wide association studies have linked risk alleles related to the NF-κB pathway to the pathogenesis of multiple Systemic Autoimmune Rheumatic Diseases. This review describes how cell- and pathway-specific NF-κB activation contribute to the spectrum of clinical phenotypes and molecular pathotypes in rheumatic disease. Potential clinical applications are explored, including therapeutic interventions and utilisation of NF-κB as a biomarker of disease subtypes and treatment response.

Notch ligands are biomarkers of anti-TNF response in RA patients.

Notch and its ligands play a critical role in rheumatoid arthritis (RA) pathogenesis. Hence, studies were conducted to delineate the functional significance of the Notch pathway in RA synovial tissue (ST) cells and the influence of RA therapies on their expression. Morphological studies reveal that JAG1, DLL4, and Notch1 are highly enriched in RA ST lining and sublining CD68+CD14+ MΦs. JAG1 and DLL4 transcription is jointly upregulated in RA MΦs reprogrammed by TLR4/5 ligation and TNF, whereas Syntenin-1 exposure expands JAG1, DLL4, and Notch1 expression levels in these cells. Single-cell RNA-seq data exhibit that JAG1 and Notch3 are overexpressed on all fibroblast-like synoviocyte (FLS) subpopulations, in parallel, JAG2, DLL1, and Notch1 expression levels are modest on RA FLS and are predominately potentiated by TLR4 ligation. Intriguingly, JAG1, DLL1/4, and Notch1/3 are presented on RA endothelial cells, and their expression is mutually reconfigured by TLR4/5 ligation in the endothelium. Synovial JAG1/JAG2/DLL1 or Notch1/3 transcriptomes were unchanged in patients who received disease-modifying anti-rheumatic drugs (DMARDs) or IL-6R Ab therapy regardless of disease activity score. Uniquely, RA MΦs and endothelial cells rewired by IL-6 displayed DLL4 transcriptional upregulation, and IL-6R antibody treatment disrupted RA ST DLL4 transcription in good responders compared to non-responders or moderate responders. Nevertheless, the JAG1/JAG2/DLL1/DLL4 transcriptome was diminished in anti-TNF good responders with myeloid pathotype and was unaltered in the fibroid pathotype except for DLL4. Taken together, our findings suggest that RA myeloid Notch ligands can serve as markers for anti-TNF responsiveness and trans-activate Notch receptors expressed on RA FLS and/or endothelial cells.

BBmix: a Bayesian beta-binomial mixture model for accurate genotyping from RNA-sequencing.

MOTIVATION: While many pipelines have been developed for calling genotypes using RNA-sequencing (RNA-Seq) data, they all have adapted DNA genotype callers that do not model biases specific to RNA-Seq such as allele-specific expression (ASE). RESULTS: Here, we present Bayesian beta-binomial mixture model (BBmix), a Bayesian beta-binomial mixture model that first learns the expected distribution of read counts for each genotype, and then deploys those learned parameters to call genotypes probabilistically. We benchmarked our model on a wide variety of datasets and showed that our method generally performed better than competitors, mainly due to an increase of up to 1.4% in the accuracy of heterozygous calls, which may have a big impact in reducing false positive rate in applications sensitive to genotyping error such as ASE. Moreover, BBmix can be easily incorporated into standard pipelines for calling genotypes. We further show that parameters are generally transferable within datasets, such that a single learning run of less than 1 h is sufficient to call genotypes in a large number of samples. AVAILABILITY AND IMPLEMENTATION: We implemented BBmix as an R package that is available for free under a GPL-2 licence at https://gitlab.com/evigorito/bbmix and https://cran.r-project.org/package=bbmix with accompanying pipeline at https://gitlab.com/evigorito/bbmix_pipeline.

DEGGs: an R package with shiny app for the identification of differentially expressed gene-gene interactions in high-throughput sequencing data.

SUMMARY: The discovery of differential gene-gene correlations across phenotypical groups can help identify the activation/deactivation of critical biological processes underlying specific conditions. The presented R package, provided with a count and design matrix, extract networks of group-specific interactions that can be interactively explored through a shiny user-friendly interface. For each gene-gene link, differential statistical significance is provided through robust linear regression with an interaction term. AVAILABILITY AND IMPLEMENTATION: DEGGs is implemented in R and available on GitHub at https://github.com/elisabettasciacca/DEGGs. The package is also under submission on Bioconductor.

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.

Analysis of Complement Gene Expression, Clinical Associations, and Biodistribution of Complement Proteins in the Synovium of Early Rheumatoid Arthritis Patients Reveals Unique Pathophysiologic Features.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by synovial hyperplasia and inflammation. The finding of autoantibodies in seropositive RA suggests that complement system activation might play a pathophysiologic role due to the local presence of immune complexes in the joints. Our first objective was to explore the Pathobiology of Early Arthritis Cohort (PEAC) mRNA sequencing data for correlations between clinical disease severity as measured by DAS28-ESR (disease activity score in 28 joints for erythrocyte sedimentation rate) and complement system gene expression, both in the synovium and in blood. Our second objective was to determine the biodistribution using multiplex immunohistochemical staining of specific complement activation proteins and inhibitors from subjects in the Accelerating Medicines Partnership (AMP) RA/SLE study. In the PEAC study, there were significant positive correlations between specific complement gene mRNA expression levels in the synovium and DAS28-ESR for the following complement genes: C2, FCN1, FCN3, CFB, CFP, C3AR1, C5AR1, and CR1 Additionally, there were significant negative correlations between DAS28-ESR and Colec12, C5, C6, MASP-1, CFH, and MCP In the synovium there were also significant positive correlations between DAS28-ESR and FcγR1A, FcγR1B, FcγR2A, and FcγR3A Notably, CFHR4 synovial expression was positively correlated following treatment with the DAS28-ESR at 6 mo, suggesting a role in worse therapeutic responses. The inverse correlation of C5 RNA expression in the synovium may underlie the failure of significant benefit from C5/C5aR inhibitors in clinical trials performed in patients with RA. Multiplex immunohistochemical analyses of early RA synovium reveal significant evidence of regional alterations of activation and inhibitory factors that likely promote local complement activation.

Cytokine-directed cellular cross-talk imprints synovial pathotypes in rheumatoid arthritis.

INTRODUCTION: Structural reorganisation of the synovium with expansion of fibroblast-like synoviocytes (FLS) and influx of immune cells is a hallmark of rheumatoid arthritis (RA). Activated FLS are increasingly recognised as a critical component driving synovial tissue remodelling by interacting with immune cells resulting in distinct synovial pathotypes of RA. METHODS: Automated high-content fluorescence microscopy of co-cultured cytokine-activated FLS and autologous peripheral CD4+ T cells from patients with RA was established to quantify cell-cell interactions. Phenotypic profiling of cytokine-treated FLS and co-cultured T cells was done by flow cytometry and RNA-Seq, which were integrated with publicly available transcriptomic data from patients with different histological synovial pathotypes. Computational prediction and knock-down experiments were performed in FLS to identify adhesion molecules for cell-cell interaction. RESULTS: Cytokine stimulation, especially with TNF-α, led to enhanced FLS-T cell interaction resulting in cell-cell contact-dependent activation, proliferation and differentiation of T cells. Signatures of cytokine-activated FLS were significantly enriched in RA synovial tissues defined as lymphoid-rich or leucocyte-rich pathotypes, with the most prominent effects for TNF-α. FLS cytokine signatures correlated with the number of infiltrating CD4+ T cells in synovial tissue of patients with RA. Ligand-receptor pair interaction analysis identified ICAM1 on FLS as an important mediator in TNF-mediated FLS-T cell interaction. Both, ICAM1 and its receptors were overexpressed in TNF-treated FLS and co-cultured T cells. Knock-down of ICAM1 in FLS resulted in reduced TNF-mediated FLS-T cell interaction. CONCLUSION: Our study highlights the role of cytokine-activated FLS in orchestrating inflammation-associated synovial pathotypes providing novel insights into disease mechanisms of RA.

UBE2L3 regulates TLR7-induced B cell autoreactivity in Systemic Lupus Erythematosus.

Both TLR7 and NF-κB hyperactivity are known to contribute to pathogenesis in Systemic Lupus Erythematosus (SLE), driving a pro-interferon response, autoreactive B cell expansion and autoantibody production. UBE2L3 is an SLE susceptibility gene which drives plasmablast/plasma cell expansion in SLE, but its role in TLR7 signalling has not been elucidated. We aimed to investigate the role of UBE2L3 in TLR7-mediated NF-κB activation, and the effect of UBE2L3 inhibition by Dimethyl Fumarate (DMF) on SLE B cell differentiation in vitro. Our data demonstrate that UBE2L3 is critical for activation of NF-κB downstream of TLR7 stimulation, via interaction with LUBAC. DMF, which directly inhibits UBE2L3, significantly inhibited TLR7-induced NF-κB activation, differentiation of memory B cells and plasmablasts, and autoantibody secretion in SLE. DMF also downregulated interferon signature genes and plasma cell transcriptional programmes. These results demonstrate that UBE2L3 inhibition could potentially be used as a therapy in SLE through repurposing of DMF, thus preventing TLR7-driven autoreactive B cell maturation.

Rituximab versus tocilizumab in anti-TNF inadequate responder patients with rheumatoid arthritis (R4RA): 16-week outcomes of a stratified, biopsy-driven, multicentre, open-label, phase 4 randomised controlled trial.

BACKGROUND: Although targeted biological treatments have transformed the outlook for patients with rheumatoid arthritis, 40% of patients show poor clinical response, which is mechanistically still unexplained. Because more than 50% of patients with rheumatoid arthritis have low or absent CD20 B cells-the target for rituximab-in the main disease tissue (joint synovium), we hypothesised that, in these patients, the IL-6 receptor inhibitor tocilizumab would be more effective. The aim of this trial was to compare the effect of tocilizumab with rituximab in patients with rheumatoid arthritis who had an inadequate response to anti-tumour necrosis factor (TNF) stratified for synovial B-cell status. METHODS: This study was a 48-week, biopsy-driven, multicentre, open-label, phase 4 randomised controlled trial (rituximab vs tocilizumab in anti-TNF inadequate responder patients with rheumatoid arthritis; R4RA) done in 19 centres across five European countries (the UK, Belgium, Italy, Portugal, and Spain). Patients aged 18 years or older who fulfilled the 2010 American College of Rheumatology and European League Against Rheumatism classification criteria for rheumatoid arthritis and were eligible for treatment with rituximab therapy according to UK National Institute for Health and Care Excellence guidelines were eligible for inclusion in the trial. To inform balanced stratification, following a baseline synovial biopsy, patients were classified histologically as B-cell poor or rich. Patients were then randomly assigned (1:1) centrally in block sizes of six and four to receive two 1000 mg rituximab infusions at an interval of 2 weeks (rituximab group) or 8 mg/kg tocilizumab infusions at 4-week intervals (tocilizumab group). To enhance the accuracy of the stratification of B-cell poor and B-cell rich patients, baseline synovial biopsies from all participants were subjected to RNA sequencing and reclassified by B-cell molecular signature. The study was powered to test the superiority of tocilizumab over rituximab in the B-cell poor population at 16 weeks. The primary endpoint was defined as a 50% improvement in Clinical Disease Activity Index (CDAI50%) from baseline. The trial is registered on the ISRCTN database, ISRCTN97443826, and EudraCT, 2012-002535-28. FINDINGS: Between Feb 28, 2013, and Jan 17, 2019, 164 patients were classified histologically and were randomly assigned to the rituximab group (83 [51%]) or the tocilizumab group (81 [49%]). In patients histologically classified as B-cell poor, there was no statistically significant difference in CDAI50% between the rituximab group (17 [45%] of 38 patients) and the tocilizumab group (23 [56%] of 41 patients; difference 11% [95% CI -11 to 33], p=0·31). However, in the synovial biopsies classified as B-cell poor with RNA sequencing the tocilizumab group had a significantly higher response rate compared with the rituximab group for CDAI50% (rituximab group 12 [36%] of 33 patients vs tocilizumab group 20 [63%] of 32 patients; difference 26% [2 to 50], p=0·035). Occurrence of adverse events (rituximab group 76 [70%] of 108 patients vs tocilizumab group 94 [80%] of 117 patients; difference 10% [-1 to 21) and serious adverse events (rituximab group 8 [7%] of 108 vs tocilizumab group 12 [10%] of 117; difference 3% [-5 to 10]) were not significantly different between treatment groups. INTERPRETATION: The results suggest that RNA sequencing-based stratification of rheumatoid arthritis synovial tissue showed stronger associations with clinical responses compared with histopathological classification. Additionally, for patients with low or absent B-cell lineage expression signature in synovial tissue tocilizumab is more effective than rituximab. Replication of the results and validation of the RNA sequencing-based classification in independent cohorts is required before making treatment recommendations for clinical practice. FUNDING: Efficacy and Mechanism Evaluation programme from the UK National Institute for Health Research.

Spectrum: fast density-aware spectral clustering for single and multi-omic data.

MOTIVATION: Clustering patient omic data is integral to developing precision medicine because it allows the identification of disease subtypes. A current major challenge is the integration multi-omic data to identify a shared structure and reduce noise. Cluster analysis is also increasingly applied on single-omic data, for example, in single cell RNA-seq analysis for clustering the transcriptomes of individual cells. This technology has clinical implications. Our motivation was therefore to develop a flexible and effective spectral clustering tool for both single and multi-omic data. RESULTS: We present Spectrum, a new spectral clustering method for complex omic data. Spectrum uses a self-tuning density-aware kernel we developed that enhances the similarity between points that share common nearest neighbours. It uses a tensor product graph data integration and diffusion procedure to reduce noise and reveal underlying structures. Spectrum contains a new method for finding the optimal number of clusters (K) involving eigenvector distribution analysis. Spectrum can automatically find K for both Gaussian and non-Gaussian structures. We demonstrate across 21 real expression datasets that Spectrum gives improved runtimes and better clustering results relative to other methods. AVAILABILITY AND IMPLEMENTATION: Spectrum is available as an R software package from CRAN https://cran.r-project.org/web/packages/Spectrum/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Autoimmune Susceptibility Gene C5orf30 Regulates Macrophage-Mediated Resolution of Inflammation.

Genetic variants in C5orf30 have been associated with development of the autoimmune conditions primary biliary cirrhosis and rheumatoid arthritis. In rheumatoid arthritis, C5orf30 expression is cell-specific, with highest expression found in macrophages and synovial fibroblasts. C5orf30 is highly expressed in inflamed joints and is a negative regulator of tissue damage in a mouse model of inflammatory arthritis. Transcriptomic analysis from ultrasound-guided synovial biopsy of inflamed joints in a well characterized clinical cohort of newly diagnosed, disease-modifying antirheumatic drugs-naive rheumatoid arthritis patients was used to determine the clinical association of C5orf30 expression with disease activity. A combined molecular and computational biology approach was used to elucidate C5orf30 function in macrophages both in vitro and in vivo. Synovial expression of C5orf30 is inversely correlated with both clinical measures of rheumatoid arthritis disease activity and with synovial TNF mRNA expression. C5orf30 plays a role in regulating macrophage phenotype and is differentially turned over in inflammatory and anti-inflammatory macrophages. Inhibition of C5orf30 reduces wound healing/repair-associated functions of macrophages, reduces signaling required for resolution of inflammation, and decreases secretion of anti-inflammatory mediators. In an animal model of wound healing (zebrafish), C5orf30 inhibition increases the recruitment of macrophages to the wound site. Finally, we demonstrate that C5orf30 skews macrophage immunometabolism, demonstrating a mechanism for C5orf30-mediated immune regulation.

De novo mutations implicate novel genes in systemic lupus erythematosus.

The omnigenic model of complex disease stipulates that the majority of the heritability will be explained by the effects of common variation on genes in the periphery of core disease pathways. Rare variant associations, expected to explain far less of the heritability, may be enriched in core disease genes and thus will be instrumental in the understanding of complex disease pathogenesis and their potential therapeutic targets. Here, using complementary whole-exome sequencing, high-density imputation, and in vitro cellular assays, we identify candidate core genes in the pathogenesis of systemic lupus erythematosus (SLE). Using extreme-phenotype sampling, we sequenced the exomes of 30 SLE parent-affected-offspring trios and identified 14 genes with missense de novo mutations (DNM), none of which are within the >80 SLE susceptibility loci implicated through genome-wide association studies. In a follow-up cohort of 10, 995 individuals of matched European ancestry, we imputed genotype data to the density of the combined UK10K-1000 genomes Phase III reference panel across the 14 candidate genes. Gene-level analyses indicate three functional candidates: DNMT3A, PRKCD, and C1QTNF4. We identify a burden of rare variants across PRKCD associated with SLE risk (P = 0.0028), and across DNMT3A associated with two severe disease prognosis sub-phenotypes (P = 0.0005 and P = 0.0033). We further characterise the TNF-dependent functions of the third candidate gene C1QTNF4 on NF-κB activation and apoptosis, which are inhibited by the p.His198Gln DNM. Our results identify three novel genes in SLE susceptibility and support extreme-phenotype sampling and DNM gene discovery to aid the search for core disease genes implicated through rare variation.

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.

Extracellular traps and PAD4 released by macrophages induce citrullination and auto-antibody production in autoimmune arthritis.

The mechanisms underlying the transition of rheumatoid arthritis (RA) systemic autoimmunity to the joints remain largely unknown. Here, we demonstrate that macrophages in the secondary lymphoid organs (SLOs) and synovial ectopic lymphoid-like structures (ELSs) express peptidylarginine deiminase 4 (PAD4) in murine collagen induced arthritis (CIA) and synovial biopsies from RA patients. Moreover, peptidyl citrulline colocalized with macrophages in SLOs and ELSs, and depletion of macrophages in CIA decreased lymphoid tissue citrullination and serum anti-citrullinated protein/peptide antibody (ACPA) levels. Furthermore, PAD was released from activated murine and RA synovial tissue and fluid (SF) macrophages which functionally deiminated extracellular proteins/peptides in vitro. Additionally, activated murine and SF macrophages displayed macrophage extracellular trap formation (METosis) and release of intracellular citrullinated histones. Moreover, presentation of citrullinated proteins induced ACPA production in vitro. Thus, lymphoid tissue macrophages contribute to self-antigen citrullination and ACPA production, indicating that their selective targeting would potentially ameliorate citrullination-dependent autoimmune disorders.

Validity of a two-component imaging-derived disease activity score for improved assessment of synovitis in early rheumatoid arthritis.

OBJECTIVES: Imaging of joint inflammation provides a standard against which to derive an updated DAS for RA. Our objectives were to develop and validate a DAS based on reweighting the DAS28 components to maximize association with US-assessed synovitis. METHODS: Early RA patients from two observational cohorts (n = 434 and n = 117) and a clinical trial (n = 59) were assessed at intervals up to 104 weeks from baseline; all US scans were within 1 week of clinical exam. There were 899, 163 and 183 visits in each cohort. Associations of combined US grey scale and power Doppler scores (GSPD) with 28 tender joint count and 28 swollen joint count (SJC28), CRP, ESR and general health visual analogue scale were examined in linear mixed model regressions. Cross-validation evaluated model predictive ability. Coefficients learned from training data defined a re-weighted DAS28 that was validated against radiographic progression in independent data (3037 observations; 717 patients). RESULTS: Of the conventional DAS28 components only SJC28 and CRP were associated with GSPD in all three development cohorts. A two-component model including SJC28 and CRP outperformed a four-component model (R2 = 0.235, 0.392, 0.380 vs 0.232, 0.380, 0.375, respectively). The re-weighted two-component DAS28CRP outperformed conventional DAS28 definitions in predicting GSPD (Δtest log-likelihood <-2.6, P < 0.01), Larsen score and presence of erosions. CONCLUSION: A score based on SJC28 and CRP alone demonstrated stronger associations with synovitis and radiographic progression than the original DAS28 and should be considered in research on pathophysiological manifestations of early RA. Implications for clinical management of RA remain to be established.

UBE2L3 polymorphism amplifies NF-κB activation and promotes plasma cell development, linking linear ubiquitination to multiple autoimmune diseases.

UBE2L3 is associated with increased susceptibility to numerous autoimmune diseases, but the underlying mechanism is unexplained. By using data from a genome-wide association study of systemic lupus erythematosus (SLE), we observed a single risk haplotype spanning UBE2L3, consistently aligned across multiple autoimmune diseases, associated with increased UBE2L3 expression in B cells and monocytes. rs140490 in the UBE2L3 promoter region showed the strongest association. UBE2L3 is an E2 ubiquitin-conjugating enzyme, specially adapted to function with HECT and RING-in-between-RING (RBR) E3 ligases, including HOIL-1 and HOIP, components of the linear ubiquitin chain assembly complex (LUBAC). Our data demonstrate that UBE2L3 is the preferred E2 conjugating enzyme for LUBAC in vivo, and UBE2L3 is essential for LUBAC-mediated activation of NF-κB. By accurately quantifying NF-κB translocation in primary human cells from healthy individuals stratified by rs140490 genotype, we observed that the autoimmune disease risk UBE2L3 genotype was correlated with basal NF-κB activation in unstimulated B cells and monocytes and regulated the sensitivity of NF-κB to CD40 stimulation in B cells and TNF stimulation in monocytes. The UBE2L3 risk allele correlated with increased circulating plasmablast and plasma cell numbers in SLE individuals, consistent with substantially elevated UBE2L3 protein levels in plasmablasts and plasma cells. These results identify key immunological consequences of the UBE2L3 autoimmune risk haplotype and highlight an important role for UBE2L3 in plasmablast and plasma cell development.

Autoantibodies targeting TLR and SMAD pathways define new subgroups in systemic lupus erythematosus.

OBJECTIVES: The molecular targets of the vast majority of autoantibodies in systemic lupus erythematosus (SLE) are unknown. We set out to identify novel autoantibodies in SLE to improve diagnosis and identify subgroups of SLE individuals. METHODS: A baculovirus-insect cell expression system was used to create an advanced protein microarray with 1543 full-length human proteins expressed with a biotin carboxyl carrier protein (BCCP) folding tag, to enrich for correctly folded proteins. Sera from a discovery cohort of UK and US SLE individuals (n = 186) and age/ethnicity matched controls (n = 188) were assayed using the microarray to identify novel autoantibodies. Autoantibodies were validated in a second validation cohort (91 SLE, 92 controls) and a confounding rheumatic disease cohort (n = 92). RESULTS: We confirmed 68 novel proteins as autoantigens in SLE and 11 previous autoantigens in both cohorts (FDR<0.05). Using hierarchical clustering and principal component analysis, we observed four subgroups of SLE individuals associated with four corresponding clusters of functionally linked autoantigens. Two clusters of novel autoantigens revealed distinctive networks of interacting proteins: SMAD2, SMAD5 and proteins linked to TGF-ß signalling; and MyD88 and proteins involved in TLR signalling, apoptosis, NF-κB regulation and lymphocyte development. The autoantibody clusters were associated with different patterns of organ involvement (arthritis, pulmonary, renal and neurological). A panel of 26 autoantibodies, which accounted for four SLE clusters, showed improved diagnostic accuracy compared to conventional antinuclear antibody and anti-dsDNA antibody assays. CONCLUSIONS: These data suggest that the novel SLE autoantibody clusters may be of prognostic utility for predicting organ involvement in SLE patients and for stratifying SLE patients for specific therapies.