shinyExprPortal: a configurable 'shiny' portal for sharing analysis of molecular expression data.

MOTIVATION: The scale of omics research presents many obstacles to full sharing and access to analysis results. Current publication models impose limits on the number of pages and figures, requiring careful preparation and selection of content. At the same time, depositing data in open repositories significantly shifts the burden of access and reproduction to readers, who may include people who are not programmers or analysts. RESULTS: We introduce shinyExprPortal, an R package that implements omics web portals with minimal coding effort. The portals allow exploration of transcriptomic or proteomic expression data and phenotypes, showcasing results of various types of analysis including differential expression, co-expression and pathways analysis. The integration with bioinformatics workflows enables researchers to focus on their results and share findings using interactive and publication-quality plots. AVAILABILITY AND IMPLEMENTATION: The shinyExprPortal package is available to download and install from CRAN and https://github.com/C4TB/shinyExprPortal.

Axl and MerTK regulate synovial inflammation and are modulated by IL-6 inhibition in rheumatoid arthritis.

The TAM tyrosine kinases, Axl and MerTK, play an important role in rheumatoid arthritis (RA). Here, using a unique synovial tissue bioresource of patients with RA matched for disease stage and treatment exposure, we assessed how Axl and MerTK relate to synovial histopathology and disease activity, and their topographical expression and longitudinal modulation by targeted treatments. We show that in treatment-naive patients, high AXL levels are associated with pauci-immune histology and low disease activity and inversely correlate with the expression levels of pro-inflammatory genes. We define the location of Axl/MerTK in rheumatoid synovium using immunohistochemistry/fluorescence and digital spatial profiling and show that Axl is preferentially expressed in the lining layer. Moreover, its ectodomain, released in the synovial fluid, is associated with synovial histopathology. We also show that Toll-like-receptor 4-stimulated synovial fibroblasts from patients with RA modulate MerTK shedding by macrophages. Lastly, Axl/MerTK synovial expression is influenced by disease stage and therapeutic intervention, notably by IL-6 inhibition. These findings suggest that Axl/MerTK are a dynamic axis modulated by synovial cellular features, disease stage and treatment.

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.

nestedcv: an R package for fast implementation of nested cross-validation with embedded feature selection designed for transcriptomics and high-dimensional data.

Motivation: Although machine learning models are commonly used in medical research, many analyses implement a simple partition into training data and hold-out test data, with cross-validation (CV) for tuning of model hyperparameters. Nested CV with embedded feature selection is especially suited to biomedical data where the sample size is frequently limited, but the number of predictors may be significantly larger (P ≫ n). Results: The nestedcv R package implements fully nested k × l-fold CV for lasso and elastic-net regularized linear models via the glmnet package and supports a large array of other machine learning models via the caret framework. Inner CV is used to tune models and outer CV is used to determine model performance without bias. Fast filter functions for feature selection are provided and the package ensures that filters are nested within the outer CV loop to avoid information leakage from performance test sets. Measurement of performance by outer CV is also used to implement Bayesian linear and logistic regression models using the horseshoe prior over parameters to encourage a sparse model and determine unbiased model accuracy. Availability and implementation: The R package nestedcv is available from CRAN: https://CRAN.R-project.org/package=nestedcv.

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.

Network analysis of synovial RNA sequencing identifies gene-gene interactions predictive of response in rheumatoid arthritis.

BACKGROUND: To determine whether gene-gene interaction network analysis of RNA sequencing (RNA-Seq) of synovial biopsies in early rheumatoid arthritis (RA) can inform our understanding of RA pathogenesis and yield improved treatment response prediction models. METHODS: We utilized four well curated pathway repositories obtaining 10,537 experimentally evaluated gene-gene interactions. We extracted specific gene-gene interaction networks in synovial RNA-Seq to characterize histologically defined pathotypes in early RA and leverage these synovial specific gene-gene networks to predict response to methotrexate-based disease-modifying anti-rheumatic drug (DMARD) therapy in the Pathobiology of Early Arthritis Cohort (PEAC). Differential interactions identified within each network were statistically evaluated through robust linear regression models. Ability to predict response to DMARD treatment was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: Analysis comparing different histological pathotypes showed a coherent molecular signature matching the histological changes and highlighting novel pathotype-specific gene interactions and mechanisms. Analysis of responders vs non-responders revealed higher expression of apoptosis regulating gene-gene interactions in patients with good response to conventional synthetic DMARD. Detailed analysis of interactions between pairs of network-linked genes identified the SOCS2/STAT2 ratio as predictive of treatment success, improving ROC area under curve (AUC) from 0.62 to 0.78. We identified a key role for angiogenesis, observing significant statistical interactions between NOS3 (eNOS) and both CAMK1 and eNOS activator AKT3 when comparing responders and non-responders. The ratio of CAMKD2/NOS3 enhanced a prediction model of response improving ROC AUC from 0.63 to 0.73. CONCLUSIONS: We demonstrate a novel, powerful method which harnesses gene interaction networks for leveraging biologically relevant gene-gene interactions leading to improved models for predicting treatment response.

Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial.

Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5-20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established. Here, in-depth histological/molecular analyses of R4RA synovial biopsies identify humoral immune response gene signatures associated with response to rituximab and tocilizumab, and a stromal/fibroblast signature in patients refractory to all medications. Post-treatment changes in synovial gene expression and cell infiltration highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms. Using ten-by-tenfold nested cross-validation, we developed machine learning algorithms predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68) and, notably, multidrug resistance (AUC = 0.69). This study supports the notion that disease endotypes, driven by diverse molecular pathology pathways in the diseased tissue, determine diverse clinical and treatment-response phenotypes. It also highlights the importance of integration of molecular pathology signatures into clinical algorithms to optimize the future use of existing medications and inform the development of new drugs for refractory patients.

Pilot Project for a Web-Based Dynamic Nomogram to Predict Survival 1 Year After Hip Fracture Surgery: Retrospective Observational Study.

BACKGROUND: Hip fracture is associated with high mortality. Identification of individual risk informs anesthetic and surgical decision-making and can reduce the risk of death. However, interpreting mathematical models and applying them in clinical practice can be difficult. There is a need to simplify risk indices for clinicians and laypeople alike. OBJECTIVE: Our primary objective was to develop a web-based nomogram for prediction of survival up to 365 days after hip fracture surgery. METHODS: We collected data from 329 patients. Our variables included sex; age; BMI; white cell count; levels of lactate, creatinine, hemoglobin, and C-reactive protein; physical status according to the American Society of Anesthesiologists Physical Status Classification System; socioeconomic status; duration of surgery; total time in the operating room; side of surgery; and procedure urgency. Thereafter, we internally calibrated and validated a Cox proportional hazards model of survival 365 days after hip fracture surgery; logistic regression models of survival 30, 120, and 365 days after surgery; and a binomial model. To present the models on a laptop, tablet, or mobile phone in a user-friendly way, we built an app using Shiny (RStudio). The app showed a drop-down box for model selection and horizontal sliders for data entry, model summaries, and prediction and survival plots. A slider represented patient follow-up over 365 days. RESULTS: Of the 329 patients, 24 (7.3%) died within 30 days of surgery, 65 (19.8%) within 120 days, and 94 (28.6%) within 365 days. In all models, the independent predictors of mortality were age, BMI, creatinine level, and lactate level. The logistic model also incorporated white cell count as a predictor. The Cox proportional hazards model showed that mortality differed as follows: age 80 vs 60 years had a hazard ratio (HR) of 0.6 (95% CI 0.3-1.1), a plasma lactate level of 2 vs 1 mmol/L had an HR of 2.4 (95% CI 1.5-3.9), and a plasma creatinine level of 60 vs 90 mol/L had an HR of 2.3 (95% CI 1.3-3.9). CONCLUSIONS: In conclusion, we provide an easy-to-read web-based nomogram that predicts survival up to 365 days after hip fracture. The Cox proportional hazards model and logistic models showed good discrimination, with concordance index values of 0.732 and 0.781, respectively.

Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis.

OBJECTIVES: To integrate published single-cell RNA sequencing (scRNA-seq) data and assess the contribution of synovial fibroblast (SF) subsets to synovial pathotypes and respective clinical characteristics in treatment-naïve early arthritis. METHODS: In this in silico study, we integrated scRNA-seq data from published studies with additional unpublished in-house data. Standard Seurat, Harmony and Liger workflow was performed for integration and differential gene expression analysis. We estimated single cell type proportions in bulk RNA-seq data (deconvolution) from synovial tissue from 87 treatment-naïve early arthritis patients in the Pathobiology of Early Arthritis Cohort using MuSiC. SF proportions across synovial pathotypes (fibroid, lymphoid and myeloid) and relationship of disease activity measurements across different synovial pathotypes were assessed. RESULTS: We identified four SF clusters with respective marker genes: PRG4+ SF (CD55, MMP3, PRG4, THY1neg ); CXCL12+ SF (CXCL12, CCL2, ADAMTS1, THY1low ); POSTN+ SF (POSTN, collagen genes, THY1); CXCL14+ SF (CXCL14, C3, CD34, ASPN, THY1) that correspond to lining (PRG4+ SF) and sublining (CXCL12+ SF, POSTN+ + and CXCL14+ SF) SF subsets. CXCL12+ SF and POSTN+ + were most prominent in the fibroid while PRG4+ SF appeared highest in the myeloid pathotype. Corresponding, lining assessed by histology (assessed by Krenn-Score) was thicker in the myeloid, but also in the lymphoid pathotype + the fibroid pathotype. PRG4+ SF correlated positively with disease severity parameters in the fibroid, POSTN+ SF in the lymphoid pathotype whereas CXCL14+ SF showed negative association with disease severity in all pathotypes. CONCLUSION: This study shows a so far unexplored association between distinct synovial pathologies and SF subtypes defined by scRNA-seq. The knowledge of the diverse interplay of SF with immune cells will advance opportunities for tailored targeted treatments.

Circulating and Synovial Pentraxin-3 (PTX3) Expression Levels Correlate With Rheumatoid Arthritis Severity and Tissue Infiltration Independently of Conventional Treatments Response.

Aims: To determine the relationship between PTX3 systemic and synovial levels and the clinical features of rheumatoid arthritis (RA) in a cohort of early, treatment naïve patients and to explore the relevance of PTX3 expression in predicting response to conventional-synthetic (cs) Disease-Modifying-Anti-Rheumatic-Drugs (DMARDs) treatment. Methods: PTX3 expression was analyzed in 119 baseline serum samples from early naïve RA patients, 95 paired samples obtained 6-months following the initiation of cs-DMARDs treatment and 43 healthy donors. RNA-sequencing analysis and immunohistochemistry for PTX3 were performed on a subpopulation of 79 and 58 synovial samples, respectively, to assess PTX3 gene and protein expression. Immunofluorescence staining was performed to characterize PTX3 expressing cells within the synovium. Results: Circulating levels of PTX3 were significantly higher in early RA compared to healthy donors and correlated with disease activity at baseline and with the degree of structural damages at 12-months. Six-months after commencing cs-DMARDs, a high level of PTX3, proportional to the baseline value, was still detectable in the serum of patients, regardless of their response status. RNA-seq analysis confirmed that synovial transcript levels of PTX3 correlated with disease activity and the presence of mediators of inflammation, tissue remodeling and bone destruction at baseline. PTX3 expression in the synovium was strongly linked to the degree of immune cell infiltration, the presence of ectopic lymphoid structures and seropositivity for autoantibodies. Accordingly, PTX3 was found to be expressed by numerous synovial cell types such as plasma cells, fibroblasts, vascular and lymphatic endothelial cells, macrophages, and neutrophils. The percentage of PTX3-positive synovial cells, although significantly reduced at 6-months post-treatment as a result of global decreased cellularity, was similar in cs-DMARDs responders and non-responders. Conclusion: This study demonstrates that, early in the disease and prior to treatment modification, the level of circulating PTX3 is a reliable marker of RA activity and predicts a high degree of structural damages at 12-months. In the joint, PTX3 associates with immune cell infiltration and the presence of ectopic lymphoid structures. High synovial and peripheral blood levels of PTX3 are associated with chronic inflammation characteristic of RA. Additional studies to determine the mechanistic link are required.

Effects of targeting the transcription factors Ikaros and Aiolos on B cell activation and differentiation in systemic lupus erythematosus.

OBJECTIVE: To evaluate the effects of targeting Ikaros and Aiolos by cereblon modulator iberdomide on the activation and differentiation of B-cells from patients with systemic lupus erythematosus (SLE). METHODS: CD19+ B-cells isolated from the peripheral blood of patients with SLE (n=41) were cultured with TLR7 ligand resiquimod ±IFNα together with iberdomide or control from day 0 (n=16). Additionally, in vitro B-cell differentiation was induced by stimulation with IL-2/IL-10/IL-15/CD40L/resiquimod with iberdomide or control, given at day 0 or at day 4. At day 5, immunoglobulins were measured by ELISA and cells analysed by flow cytometry. RNA-Seq was performed on fluorescence-activated cell-sorted CD27-IgD+ naïve-B-cells and CD20lowCD27+CD38+ plasmablasts to investigate the transcriptional consequences of iberdomide. RESULTS: Iberdomide significantly inhibited the TLR7 and IFNα-mediated production of immunoglobulins from SLE B-cells and the production of antinuclear antibodies as well as significantly reducing the number of CD27+CD38+ plasmablasts (0.3±0.18, vehicle 1.01±0.56, p=0.011) and CD138+ plasma cells (0.12±0.06, vehicle 0.28±0.02, p=0.03). Additionally, treatment with iberdomide from day 0 significantly inhibited the differentiation of SLE B-cells into plasmablasts (6.4±13.5 vs vehicle 34.9±20.1, p=0.013) and antibody production. When given at later stages of differentiation, iberdomide did not affect the numbers of plasmablasts or the production of antibodies; however, it induced a significant modulation of gene expression involving IKZF1 and IKZF3 transcriptional programmes in both naïve B-cells and plasmablasts (400 and 461 differentially modulated genes, respectively, false discovery rate<0.05). CONCLUSION: These results demonstrate the relevance of Ikaros and Aiolos as therapeutic targets in SLE due to their ability to modulate B cell activation and differentiation downstream of TLR7.

IL-23 skin and joint profiling in psoriatic arthritis: novel perspectives in understanding clinical responses to IL-23 inhibitors.

OBJECTIVES: To determine the relationship between synovial versus skin transcriptional/histological profiles in patients with active psoriatic arthritis (PsA) and explore mechanistic links between diseased tissue pathology and clinical outcomes. METHODS: Twenty-seven active PsA patients were enrolled in an observational/open-label study and underwent biopsies of synovium and paired lesional/non-lesional skin before starting anti-tumour necrosis factor (TNF) (if biologic-naïve) or ustekinumab (if anti-TNF inadequate responders). Molecular analysis of 80-inflammation-related genes and protein levels for interleukin (IL)-23p40/IL-23p19/IL-23R were assessed by real-time-PCR and immunohistochemistry, respectively. RESULTS: At baseline, all patients had persistent active disease as per inclusion criteria. At primary end-point (16-weeks post-treatment), skin responses favoured ustekinumab, while joint responses favoured anti-TNF therapies. Principal component analysis revealed distinct clustering of synovial tissue gene expression away from the matched skin. While IL12B, IL23A and IL23R were homogeneously expressed in lesional skin, their expression was extremely heterogeneous in paired synovial tissues. Here, IL-23 transcriptomic/protein expression was strongly linked to patients with high-grade synovitis who, however, were not distinguishable by conventional clinimetric measures. CONCLUSIONS: PsA synovial tissue shows a heterogeneous IL-23 axis profile when compared with matched skin. Synovial molecular pathology may help to identify among clinically indistinguishable patients those with a greater probability of responding to IL-23 inhibitors.

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.

M3C: Monte Carlo reference-based consensus clustering.

Genome-wide data is used to stratify patients into classes for precision medicine using clustering algorithms. A common problem in this area is selection of the number of clusters (K). The Monti consensus clustering algorithm is a widely used method which uses stability selection to estimate K. However, the method has bias towards higher values of K and yields high numbers of false positives. As a solution, we developed Monte Carlo reference-based consensus clustering (M3C), which is based on this algorithm. M3C simulates null distributions of stability scores for a range of K values thus enabling a comparison with real data to remove bias and statistically test for the presence of structure. M3C corrects the inherent bias of consensus clustering as demonstrated on simulated and real expression data from The Cancer Genome Atlas (TCGA). For testing M3C, we developed clusterlab, a new method for simulating multivariate Gaussian clusters.

Interleukin-36 family dysregulation drives joint inflammation and therapy response in psoriatic arthritis.

OBJECTIVES: IL-36 agonists are pro-inflammatory cytokines involved in the pathogenesis of psoriasis. However, their role in the pathogenesis of arthritis and treatment response to DMARDs in PsA remains uncertain. Therefore, we investigated the IL-36 axis in the synovium of early, treatment-naïve PsA, and for comparison RA patients, pre- and post-DMARDs therapy. METHODS: Synovial tissues were collected by US-guided biopsy from patients with early, treatment-naïve PsA and RA at baseline and 6 months after DMARDs therapy. IL-36 family members were investigated in synovium by RNA sequencing and immunohistochemistry, and expression levels correlated with DMARDs treatment response ex vivo. Additionally, DMARDs effects on IL-36 were investigated in vitro in fibroblast-like synoviocytes. RESULTS: PsA synovium displayed a reduced expression of IL-36 antagonists, while IL-36 agonists were comparable between PsA and RA. Additionally, neutrophil-related molecules, which drive a higher activation of the IL-36 pathway, were upregulated in PsA compared with RA. At baseline, the synovial expression of IL-36α was significantly higher in PsA non-responders to DMARDs treatment, with the differential expression being sustained at 6 months post-treatment. In vitro, primary PsA-derived fibroblasts were more responsive to IL-36 stimulation compared with RA and, importantly, DMARDs treatment increased IL-36 expression in PsA fibroblasts. CONCLUSION: The impaired balance between IL-36 agonists-antagonists described herein for the first time in PsA synovium and the decreased sensitivity to DMARDs in vitro may explain the apparent lower efficacy of DMARDs in PsA compared with RA. Exogenous replacement of IL-36 antagonists may be a novel promising therapeutic target for PsA patients.

Lactate Buildup at the Site of Chronic Inflammation Promotes Disease by Inducing CD4+ T Cell Metabolic Rewiring.

Accumulation of lactate in the tissue microenvironment is a feature of both inflammatory disease and cancer. Here, we assess the response of immune cells to lactate in the context of chronic inflammation. We report that lactate accumulation in the inflamed tissue contributes to the upregulation of the lactate transporter SLC5A12 by human CD4+ T cells. SLC5A12-mediated lactate uptake into CD4+ T cells induces a reshaping of their effector phenotype, resulting in increased IL17 production via nuclear PKM2/STAT3 and enhanced fatty acid synthesis. It also leads to CD4+ T cell retention in the inflamed tissue as a consequence of reduced glycolysis and enhanced fatty acid synthesis. Furthermore, antibody-mediated blockade of SLC5A12 ameliorates the disease severity in a murine model of arthritis. Finally, we propose that lactate/SLC5A12-induced metabolic reprogramming is a distinctive feature of lymphoid synovitis in rheumatoid arthritis patients and a potential therapeutic target in chronic inflammatory disorders.

Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes.

There is a current imperative to unravel the hierarchy of molecular pathways that drive the transition of early to established disease in rheumatoid arthritis (RA). Herein, we report a comprehensive RNA sequencing analysis of the molecular pathways that drive early RA progression in the disease tissue (synovium), comparing matched peripheral blood RNA-seq in a large cohort of early treatment-naive patients, namely, the Pathobiology of Early Arthritis Cohort (PEAC). We developed a data exploration website (https://peac.hpc.qmul.ac.uk/) to dissect gene signatures across synovial and blood compartments, integrated with deep phenotypic profiling. We identified transcriptional subgroups in synovium linked to three distinct pathotypes: fibroblastic pauci-immune pathotype, macrophage-rich diffuse-myeloid pathotype, and a lympho-myeloid pathotype characterized by infiltration of lymphocytes and myeloid cells. This is suggestive of divergent pathogenic pathways or activation disease states. Pro-myeloid inflammatory synovial gene signatures correlated with clinical response to initial drug therapy, whereas plasma cell genes identified a poor prognosis subgroup with progressive structural damage.

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.