Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes

The immunomodulatory of interleukin-33 in rheumatoid arthritis: A systematic review

Rheumatoid arthritis (RA) is a systemic chronic autoimmune disease that primarily affects the joints and surrounding soft tissues, characterized by chronic inflammation and proliferation of the synovium. Various immune cells are involved in the pathophysiology of RA. The complex interplay of factors such as chronic inflammation, genetic susceptibility, dysregulation of serum antibody levels, among others, contribute to the complexity of the disease mechanism, disease activity, and treatment of RA. Recently, the cytokine storm leading to increased disease activity in RA has gained significant attention. Interleukin-33 (IL-33), a member of the IL-1 family, plays a crucial role in inflammation and immune regulation. ST2 (suppression of tumorigenicity 2 receptor), the receptor for IL-33, is widely expressed on the surface of various immune cells. When IL-33 binds to its receptor ST2, it activates downstream signaling pathways to exert immunoregulatory effects. In RA, IL-33 regulates the progression of the disease by modulating immune cells such as circulating monocytes, tissue-resident macrophages, synovial fibroblasts, mast cells, dendritic cells, neutrophils, T cells, B cells, endothelial cells, and others. We have summarized and analyzed these findings to elucidate the pathways through which IL-33 regulates RA. Furthermore, IL-33 has been detected in the synovium, serum, and synovial fluid of RA patients. Due to inconsistent research results, we conducted a meta-analysis on the association between serum IL-33, synovial fluid IL-33, and the risk of developing RA in patients. The pooled SMD was 1.29 (95% CI: 1.15-1.44), indicating that IL-33 promotes the onset and pathophysiological progression of RA. Therefore, IL-33 may serve as a biomarker for predicting the risk of developing RA and treatment outcomes. As existing drugs for RA still cannot address drug resistance in some patients, new therapeutic approaches are needed to alleviate the significant burden on RA patients and healthcare systems. In light of this, we analyzed the potential of targeting the IL-33/ST2-related signaling pathway to modulate immune cells associated with RA and alleviate inflammation. We also reviewed IL-33 and RA susceptibility-related single nucleotide polymorphisms, suggesting potential involvement of IL-33 and macrophage-related drug-resistant genes in RA resistance therapy. Our review elucidates the role of IL-33 in the pathophysiology of RA, offering new insights for the treatment of RA.

Contextual AI models for single-cell protein biology

Understanding protein function and developing molecular therapies require deciphering the cell types in which proteins act as well as the interactions between proteins. However, modeling protein interactions across biological contexts remains challenging for existing algorithms. Here we introduce PINNACLE, a geometric deep learning approach that generates context-aware protein representations. Leveraging a multiorgan single-cell atlas, PINNACLE learns on contextualized protein interaction networks to produce 394,760 protein representations from 156 cell type contexts across 24 tissues. PINNACLE's embedding space reflects cellular and tissue organization, enabling zero-shot retrieval of the tissue hierarchy. Pretrained protein representations can be adapted for downstream tasks: enhancing 3D structure-based representations for resolving immuno-oncological protein interactions, and investigating drugs' effects across cell types. PINNACLE outperforms state-of-the-art models in nominating therapeutic targets for rheumatoid arthritis and inflammatory bowel diseases and pinpoints cell type contexts with higher predictive capability than context-free models. PINNACLE's ability to adjust its outputs on the basis of the context in which it operates paves the way for large-scale context-specific predictions in biology.

Interferon subverts an AHR-JUN axis to promote CXCL13+ T cells in lupus

Systemic lupus erythematosus (SLE) is prototypical autoimmune disease driven by pathological T cell-B cell interactions1,2. Expansion of T follicular helper (TFH) and T peripheral helper (TPH) cells, two T cell populations that provide help to B cells, is a prominent feature of SLE3,4. Human TFH and TPH cells characteristically produce high levels of the B cell chemoattractant CXCL13 (refs. 5,6), yet regulation of T cell CXCL13 production and the relationship between CXCL13+ T cells and other T cell states remains unclear. Here, we identify an imbalance in CD4+ T cell phenotypes in patients with SLE, with expansion of PD-1+/ICOS+ CXCL13+ T cells and reduction of CD96hi IL-22+ T cells. Using CRISPR screens, we identify the aryl hydrocarbon receptor (AHR) as a potent negative regulator of CXCL13 production by human CD4+ T cells. Transcriptomic, epigenetic and functional studies demonstrate that AHR coordinates with AP-1 family member JUN to prevent CXCL13+ TPH/TFH cell differentiation and promote an IL-22+ phenotype. Type I interferon, a pathogenic driver of SLE7, opposes AHR and JUN to promote T cell production of CXCL13. These results place CXCL13+ TPH/TFH cells on a polarization axis opposite from T helper 22 (TH22) cells and reveal AHR, JUN and interferon as key regulators of these divergent T cell states.

Biologics or Janus Kinase Inhibitors in Rheumatoid Arthritis Patients Who are Insufficient Responders to Conventional Anti-Rheumatic Drugs

Rheumatoid arthritis (RA) is a chronic immune-mediated inflammatory disease which can induce progressive disability if not properly treated early. Over the last 20 years, the improvement of knowledge on the pathogenesis of the disease has made available several drugs targeting key elements of the pathogenetic process, which now represent the preferred treatment option after the failure of first-line therapy with conventional drugs such as methotrexate (MTX). To this category of targeted drugs belong anti-cytokine or cell-targeted biological agents and more recently also Janus kinase inhibitors (JAKis). In the absence to date of specific biomarkers to guide the therapeutic choice in the context of true precision medicine, the choice of the first targeted drug after MTX failure is guided by treatment cost (especially after the marketing of biosimilar products) and by the clinical characteristics of the patient (age, sex, comorbidities and compliance) and the disease (presence or absence of autoantibodies and systemic or extra-articular manifestations), which may influence the efficacy and safety profile of the available products. This viewpoint focuses on the decision-making process underlying the personalized approach to RA therapy and will analyse the evidence in the literature supporting the choice of individual products and in particular the differential choice between biological drugs and JAKis.

The peculiar features, diversity and impact of citrulline-reactive autoantibodies

Since entering the stage 25 years ago as a highly specific serological biomarker for rheumatoid arthritis, anti-citrullinated protein antibodies (ACPAs) have been a topic of extensive research. This hallmark B cell response arises years before disease onset, displays interpatient autoantigen variability, and is associated with poor clinical outcomes. Technological and scientific advances have revealed broad clonal diversity and intriguing features including high levels of somatic hypermutation, variable-domain N-linked glycosylation, hapten-like peptide interactions, and clone-specific multireactivity to citrullinated, carbamylated and acetylated epitopes. ACPAs have been found in different isotypes and subclasses, in both circulation and tissue, and are secreted by both plasmablasts and long-lived plasma cells. Notably, although some disease-promoting features have been reported, results now demonstrate that certain monoclonal ACPAs therapeutically block arthritis and inflammation in mouse models. A wealth of functional studies using patient-derived polyclonal and monoclonal antibodies have provided evidence for pathogenic and protective effects of ACPAs in the context of arthritis. To understand the roles of ACPAs, one needs to consider their immunological properties by incorporating different facets such as rheumatoid arthritis B cell biology, environmental triggers and chronic antigen exposure. The emerging picture points to a complex role of citrulline-reactive autoantibodies, in which the diversity and dynamics of antibody clones could determine clinical progression and manifestations.

Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice

Since the advent of single-cell RNA sequencing (scRNA-seq) methodology, single-cell analysis has become a powerful tool for exploration of cellular networks and dysregulated immune responses in disease pathogenesis. Advanced bioinformatics tools have enabled the combined analysis of scRNA-seq data and information on various cell properties, such as cell surface molecular profiles, chromatin accessibility and spatial information, leading to a deeper understanding of pathology. This Review provides an overview of the achievements in single-cell analysis applied to clinical samples of rheumatic and allergic diseases, including rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, allergic airway diseases and atopic dermatitis, with an expanded scope beyond peripheral blood cells to include local diseased tissues. Despite the valuable insights that single-cell analysis has provided into disease pathogenesis, challenges remain in translating single-cell findings into clinical practice and developing personalized treatment strategies. Beyond understanding the atlas of cellular diversity, we discuss the application of data obtained in each study to clinical practice, with a focus on identifying biomarkers and therapeutic targets.

Molecular maps of synovial cells in inflammatory arthritis using an optimized synovial tissue dissociation protocol

In this study, we optimized the dissociation of synovial tissue biopsies for single-cell omics studies and created a single-cell atlas of human synovium in inflammatory arthritis. The optimized protocol allowed consistent isolation of highly viable cells from tiny fresh synovial biopsies, minimizing the synovial biopsy drop-out rate. The synovium scRNA-seq atlas contained over 100,000 unsorted synovial cells from 25 synovial tissues affected by inflammatory arthritis, including 16 structural, 11 lymphoid, and 15 myeloid cell clusters. This synovial cell map expanded the diversity of synovial cell types/states, detected synovial neutrophils, and broadened synovial endothelial cell classification. We revealed tissue-resident macrophage subsets with proposed matrix-sensing (FOLR2+COLEC12high) and iron-recycling (LYVE1+SLC40A1+) activities and identified fibroblast subsets with proposed functions in cartilage breakdown (SOD2highSAA1+SAA2+SDC4+) and extracellular matrix remodeling (SERPINE1+COL5A3+LOXL2+). Our study offers an efficient synovium dissociation method and a reference scRNA-seq resource, that advances the current understanding of synovial cell heterogeneity in inflammatory arthritis.

Integrated analysis of single-cell RNA-seq, bulk RNA-seq, Mendelian randomization, and eQTL reveals T cell-related nomogram model and subtype classification in rheumatoid arthritis

Objective

Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy.

Methods

scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features.

Results

By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients.

Conclusion

Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

Gut microbiota as a sensor of autoimmune response and treatment for rheumatoid arthritis

Rheumatoid arthritis (RA) is considered a multifactorial condition where interaction between the genetic and environmental factors lead to immune dysregulation causing autoreactivity. While among the various genetic factors, HLA-DR4 and DQ8, have been reported to be the strongest risk factors, the role of various environmental factors has been unclear. Though events initiating autoreactivity remain unknown, a mucosal origin of RA has gained attention based on the recent observations with the gut dysbiosis in patients. However, causality of gut dysbiosis has been difficult to prove in humans. Mouse models, especially mice expressing RA-susceptible and -resistant HLA class II genes have helped unravel the complex interactions between genetic factors and gut microbiome. This review describes the interactions between HLA genes and gut dysbiosis in sex-biased preclinical autoreactivity and discusses the potential use of endogenous commensals as indicators of treatment efficacy as well as therapeutic tool to suppress pro-inflammatory response in rheumatoid arthritis.

Phosphoproteomic profiling of early rheumatoid arthritis synovium reveals active signalling pathways and differentiates inflammatory pathotypes

BACKGROUND

Kinases are intracellular signalling mediators and key to sustaining the inflammatory process in rheumatoid arthritis (RA). Oral inhibitors of Janus Kinase family (JAKs) are widely used in RA, while inhibitors of other kinase families e.g. phosphoinositide 3-kinase (PI3K) are under development. Most current biomarker platforms quantify mRNA/protein levels, but give no direct information on whether proteins are active/inactive. Phosphoproteome analysis has the potential to measure specific enzyme activation status at tissue level.

METHODS

We validated the feasibility of phosphoproteome and total proteome analysis on 8 pre-treatment synovial biopsies from treatment-naive RA patients using label-free mass spectrometry, to identify active cell signalling pathways in synovial tissue which might explain failure to respond to RA therapeutics.

RESULTS

Differential expression analysis and functional enrichment revealed clear separation of phosphoproteome and proteome profiles between lymphoid and myeloid RA pathotypes. Abundance of specific phosphosites was associated with the degree of inflammatory state. The lymphoid pathotype was enriched with lymphoproliferative signalling phosphosites, including Mammalian Target Of Rapamycin (MTOR) signalling, whereas the myeloid pathotype was associated with Mitogen-Activated Protein Kinase (MAPK) and CDK mediated signalling. This analysis also highlighted novel kinases not previously linked to RA, such as Protein Kinase, DNA-Activated, Catalytic Subunit (PRKDC) in the myeloid pathotype. Several phosphosites correlated with clinical features, such as Disease-Activity-Score (DAS)-28, suggesting that phosphosite analysis has potential for identifying novel biomarkers at tissue-level of disease severity and prognosis.

CONCLUSIONS

Specific phosphoproteome/proteome signatures delineate RA pathotypes and may have clinical utility for stratifying patients for personalised medicine in RA.

Leveraging Multi-Tissue, Single-Cell Atlases as Tools to Elucidate Shared Mechanisms of Immune-Mediated Inflammatory Diseases

The observation that certain therapeutic strategies for targeting inflammation benefit patients with distinct immune-mediated inflammatory diseases (IMIDs) is exemplified by the success of TNF blockade in conditions including rheumatoid arthritis, ulcerative colitis, and skin psoriasis, albeit only for subsets of individuals with each condition. This suggests intersecting "nodes" in inflammatory networks at a molecular and cellular level may drive and/or maintain IMIDs, being "shared" between traditionally distinct diagnoses without mapping neatly to a single clinical phenotype. In line with this proposition, integrative tumour tissue analyses in oncology have highlighted novel cell states acting across diverse cancers, with important implications for precision medicine. Drawing upon advances in the oncology field, this narrative review will first summarise learnings from the Human Cell Atlas in health as a platform for interrogating IMID tissues. It will then review cross-disease studies to date that inform this endeavour before considering future directions in the field.

Clonal associations between lymphocyte subsets and functional states in rheumatoid arthritis synovium

Rheumatoid arthritis (RA) is an autoimmune disease involving antigen-specific T and B cells. Here, we perform single-cell RNA and repertoire sequencing on paired synovial tissue and blood samples from 12 seropositive RA patients. We identify clonally expanded CD4 + T cells, including CCL5+ cells and T peripheral helper (Tph) cells, which show a prominent transcriptomic signature of recent activation and effector function. CD8 + T cells show higher oligoclonality than CD4 + T cells, with the largest synovial clones enriched in GZMK+ cells. CD8 + T cells with possibly virus-reactive TCRs are distributed across transcriptomic clusters. In the B cell compartment, NR4A1+ activated B cells, and plasma cells are enriched in the synovium and demonstrate substantial clonal expansion. We identify synovial plasma cells that share BCRs with synovial ABC, memory, and activated B cells. Receptor-ligand analysis predicted IFNG and TNFRSF members as mediators of synovial Tph-B cell interactions. Together, these results reveal clonal relationships between functionally distinct lymphocyte populations that infiltrate the synovium of patients with RA.

Endothelial cell sphingosine 1-phosphate receptor 1 restrains VE-cadherin cleavage and attenuates experimental inflammatory arthritis

In rheumatoid arthritis, inflammatory mediators extravasate from blood into joints via gaps between endothelial cells (ECs), but the contribution of ECs is not known. Sphingosine 1-phosphate receptor 1 (S1PR1), widely expressed on ECs, maintains the vascular barrier. Here, we assessed the contribution of vascular integrity and EC S1PR1 signaling to joint damage in mice exposed to serum-induced arthritis (SIA). EC-specific deletion of S1PR1 or pharmacological blockade of S1PR1 promoted vascular leak and amplified SIA, whereas overexpression of EC S1PR1 or treatment with an S1PR1 agonist delayed SIA. Blockade of EC S1PR1 induced membrane metalloproteinase-dependent cleavage of vascular endothelial cadherin (VE-cadherin), a principal adhesion molecule that maintains EC junctional integrity. We identified a disintegrin and a metalloproteinase domain 10 (ADAM10) as the principal VE-cadherin "sheddase." Mice expressing a stabilized VE-cadherin construct had decreased extravascular VE-cadherin and vascular leakage in response to S1PR1 blockade, and they were protected from SIA. Importantly, patients with active rheumatoid arthritis had decreased circulating S1P and microvascular expression of S1PR1, suggesting a dysregulated S1P/S1PR1 axis favoring vascular permeability and vulnerability. We present a model in which EC S1PR1 signaling maintains homeostatic vascular barrier function by limiting VE-cadherin shedding mediated by ADAM10 and suggest this signaling axis as a therapeutic target in inflammatory arthritis.

The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis

Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8 + GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.

Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes

Our limited understanding of the pathophysiological mechanisms that operate during sepsis is an obstacle to rational treatment and clinical trial design. There is a critical lack of data from low- and middle-income countries where the sepsis burden is increased which inhibits generalized strategies for therapeutic intervention. Here we perform RNA sequencing of whole blood to investigate longitudinal host response to sepsis in a Ghanaian cohort. Data dimensional reduction reveals dynamic gene expression patterns that describe cell type-specific molecular phenotypes including a dysregulated myeloid compartment shared between sepsis and COVID-19. The gene expression signatures reported here define a landscape of host response to sepsis that supports interventions via targeting immunophenotypes to improve outcomes.

Uncover spatially informed variations for single-cell spatial transcriptomics with STew

Motivation

The recent spatial transcriptomics (ST) technologies have enabled characterization of gene expression patterns and spatial information, advancing our understanding of cell lineages within diseased tissues. Several analytical approaches have been proposed for ST data, but effectively utilizing spatial information to unveil the shared variation with gene expression remains a challenge.

Results

We introduce STew, a Spatial Transcriptomic multi-viEW representation learning method, to jointly analyze spatial information and gene expression in a scalable manner, followed by a data-driven statistical framework to measure the goodness of model fit. Through benchmarking using human dorsolateral prefrontal cortex and mouse main olfactory bulb data with true manual annotations, STew achieved superior performance in both clustering accuracy and continuity of identified spatial domains compared with other methods. STew is also robust to generate consistent results insensitive to model parameters, including sparsity constraints. We next applied STew to various ST data acquired from 10× Visium, Slide-seqV2, and 10× Xenium, encompassing single-cell and multi-cellular resolution ST technologies, which revealed spatially informed cell type clusters and biologically meaningful axes. In particular, we identified a proinflammatory fibroblast spatial niche using ST data from psoriatic skins. Moreover, STew scales almost linearly with the number of spatial locations, guaranteeing its applicability to datasets with thousands of spatial locations to capture disease-relevant niches in complex tissues.

Availability and implementation

Source code and the R software tool STew are available from github.com/fanzhanglab/STew.

Granzyme K drives a newly-intentified pathway of complement activation

Granzymes are a family of serine proteases mainly expressed by CD8+ T cells, natural killer cells, and innate-like lymphocytes1,2. Although their major role is thought to be the induction of cell death in virally infected and tumor cells, accumulating evidence suggests some granzymes can regulate inflammation by acting on extracellular substrates2. Recently, we found that the majority of tissue CD8+ T cells in rheumatoid arthritis (RA) synovium, inflammatory bowel disease and other inflamed organs express granzyme K (GZMK)3, a tryptase-like protease with poorly defined function. Here, we show that GZMK can activate the complement cascade by cleaving C2 and C4. The nascent C4b and C2a fragments form a C3 convertase that cleaves C3, allowing further assembly of a C5 convertase that cleaves C5. The resulting convertases trigger every major event in the complement cascade, generating the anaphylatoxins C3a and C5a, the opsonins C4b and C3b, and the membrane attack complex. In RA synovium, GZMK is enriched in areas with abundant complement activation, and fibroblasts are the major producers of complement C2, C3, and C4 that serve as targets for GZMK-mediated complement activation. Our findings describe a previously unidentified pathway of complement activation that is entirely driven by lymphocyte-derived GZMK and proceeds independently of the classical, lectin, or alternative pathways. Given the widespread abundance of GZMK-expressing T cells in tissues in chronic inflammatory diseases and infection, GZMK-mediated complement activation is likely to be an important contributor to tissue inflammation in multiple disease contexts.

Two Broad Categories Overlapping With Rheumatoid Arthritis Observed in Synovial Biopsies from Patients With Juvenile Idiopathic Arthritis

OBJECTIVE

The objective is to characterize transcriptomic profiles and immune cell composition and distribution in juvenile idiopathic arthritis (JIA) synovial biopsies, assess for associations of these features with clinical parameters, and compare JIA and rheumatoid arthritis (RA) synovial features.

METHODS

RNA sequencing (RNASeq) was performed on 24 samples, with pathway analysis and inference of relative abundance of immune cell subsets based on gene expression data. Two multiplex fluorescence immunohistochemistry (IHC) panels were performed on 28 samples (including 13 on which RNASeq was performed), staining for CD206- classical and CD206+ nonclassical macrophages, and CD8+ and CD4+ T and B lymphocytes. Data were compared to a published series of early RA synovial biopsies.

RESULTS

Pathway analysis of the most variably expressed genes (n = 339) identified a B and plasma cell signature as the main driver of heterogeneity in JIA synovia, with strong overlap between JIA and RA synovitis. Multiplex IHC confirmed heterogeneity of immune cell infiltration. M1-like macrophage-rich synovial lining was associated with greater lining hypertrophy and higher (CD45+) pan-immune cell and CD8+ T cell infiltration.

CONCLUSION

Our study indicates significant similarities between JIA and RA synovitis. Similar to RA, JIA synovia may be broadly categorized into two groups: (1) those with an inflammatory/adaptive immune transcriptomic signature, M1-like macrophage and CD8+ T cell infiltration, and thicker, M1-like macrophage-rich synovial lining, and (2) those with an M2-like macrophage transcriptomic signature, greater M2/M1-like macrophage ratios, and thinner, M2-like macrophage-rich synovial lining. Synovial features were not significantly associated with clinical parameters, likely because of group size and heterogeneity.

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks. Here, we advance the characterization of T-cells with T-CellAnnoTator (TCAT), a pipeline that simultaneously quantifies pre-defined GEPs capturing activation states and cellular subsets. From 1,700,000 T-cells from 700 individuals across 38 tissues and five diverse disease contexts, we discover 46 reproducible GEPs reflecting the known core functions of T-cells including proliferation, cytotoxicity, exhaustion, and T helper effector states. We experimentally characterize several novel activation programs and apply TCAT to describe T-cell activation and exhaustion in Covid-19 and cancer, providing insight into T-cell function in these diseases.

Inflammatory tissue priming: novel insights and therapeutic opportunities for inflammatory rheumatic diseases

Due to optimised treatment strategies and the availability of new therapies during the last decades, formerly devastating chronic inflammatory diseases such as rheumatoid arthritis or systemic sclerosis (SSc) have become less menacing. However, in many patients, even state-of-the-art treatment cannot induce remission. Moreover, the risk for flares strongly increases once anti-inflammatory therapy is tapered or withdrawn, suggesting that underlying pathological processes remain active even in the absence of overt inflammation. It has become evident that tissues have the ability to remember past encounters with pathogens, wounds and other irritants, and to react more strongly and/or persistently to the next occurrence. This priming of the tissue bears a paramount role in defence from microbes, but on the other hand drives inflammatory pathologies (the Dr Jekyll and Mr Hyde aspect of tissue adaptation). Emerging evidence suggests that long-lived tissue-resident cells, such as fibroblasts, macrophages, long-lived plasma cells and tissue-resident memory T cells, determine inflammatory tissue priming in an interplay with infiltrating immune cells of lymphoid and myeloid origin, and with systemically acting factors such as cytokines, extracellular vesicles and antibodies. Here, we review the current state of science on inflammatory tissue priming, focusing on tissue-resident and tissue-occupying cells in arthritis and SSc, and reflect on the most promising treatment options targeting the maladapted tissue response during these diseases.

Interferons and epigenetic mechanisms in training, priming and tolerance of monocytes and hematopoietic progenitors

Training and priming of innate immune cells involve preconditioning by PAMPs, DAMPs, and/or cytokines that elicits stronger induction of inflammatory genes upon secondary challenge. Previous models distinguish training and priming based upon whether immune activation returns to baseline prior to secondary challenge. Tolerance is a protective mechanism whereby potent stimuli induce refractoriness to secondary challenge. Training and priming are important for innate memory responses that protect against infection, efficacy of vaccines, and maintaining innate immune cells in a state of readiness; tolerance prevents toxicity from excessive immune activation. Dysregulation of these processes can contribute to pathogenesis of autoimmune/inflammatory conditions, post-COVID-19 hyperinflammatory states, or sepsis-associated immunoparalysis. Training, priming, and tolerance regulate similar "signature" inflammatory genes such as TNF, IL6, and IL1B and utilize overlapping epigenetic mechanisms. We review how interferons (IFNs), best known for activating JAK-STAT signaling and interferon-stimulated genes, also play a key role in regulating training, priming, and tolerance via chromatin-mediated mechanisms. We present new data on how monocyte-to-macrophage differentiation modulates IFN-γ-mediated priming, affects regulation of AP-1 and CEBP activity, and attenuates superinduction of inflammatory genes. We present a "training-priming continuum" model that integrates IFN-mediated priming into current concepts about training and tolerance and proposes a central role for STAT1 and IRF1.

Molecular portrait of chronic joint diseases: Defining endotypes toward personalized medicine

Joint diseases affect hundreds of millions of people worldwide, and their prevalence is constantly increasing. To date, despite recent advances in the development of therapeutic options for most rheumatic conditions, a significant proportion of patients still lack efficient disease management, considerably impacting their quality of life. Through the spectrum of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and osteoarthritis (OA) as quintessential and common rheumatic diseases, this review first provides an overview of their epidemiological and clinical features before exploring how the better definition of clinical phenotypes has helped their clinical management. It then discusses the recent progress in understanding the diversity of endotypes underlying disease phenotypes. Finally, this review highlights the current challenges of implementing molecular endotypes towards the personalized management of RA, PsA and OA patients in the future.

Synovial fibroblast gene expression is associated with sensory nerve growth and pain in rheumatoid arthritis

It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in the synovium; however, recent studies reveal that pain scores in patients do not correlate with synovial inflammation. We developed a machine-learning approach (graph-based gene expression module identification or GbGMI) to identify an 815-gene expression module associated with pain in synovial biopsy samples from patients with established RA who had limited synovial inflammation at arthroplasty. We then validated this finding in an independent cohort of synovial biopsy samples from patients who had early untreated RA with little inflammation. Single-cell RNA sequencing analyses indicated that most of these 815 genes were most robustly expressed by lining layer synovial fibroblasts. Receptor-ligand interaction analysis predicted cross-talk between human lining layer fibroblasts and human dorsal root ganglion neurons expressing calcitonin gene-related peptide (CGRP+). Both RA synovial fibroblast culture supernatant and netrin-4, which is abundantly expressed by lining fibroblasts and was within the GbGMI-identified pain-associated gene module, increased the branching of pain-sensitive murine CGRP+ dorsal root ganglion neurons in vitro. Imaging of solvent-cleared synovial tissue with little inflammation from humans with RA revealed CGRP+ pain-sensing neurons encasing blood vessels growing into synovial hypertrophic papilla. Together, these findings support a model whereby synovial lining fibroblasts express genes associated with pain that enhance the growth of pain-sensing neurons into regions of synovial hypertrophy in RA.

Understanding Spondyloarthritis Pathogenesis: The Promise of Single-Cell Profiling

PURPOSE OF REVIEW

Single-cell profiling, either in suspension or within the tissue context, is a rapidly evolving field. The purpose of this review is to outline recent advancements and emerging trends with a specific focus on studies in spondyloarthritis.

RECENT FINDINGS

The introduction of sequencing-based approaches for the quantification of RNA, protein, or epigenetic modifications at single-cell resolution has provided a major boost to discovery-driven research. Fluorescent flow cytometry, mass cytometry, and image-based cytometry continue to evolve. Spatial transcriptomics and imaging mass cytometry have extended high-dimensional analysis to cells in tissues. Applications in spondyloarthritis include the indexing and functional characterization of cells, discovery of disease-associated cell states, and identification of signatures associated with therapeutic responses. Single-cell TCR-seq has provided evidence for clonal expansion of CD8+ T cells in spondyloarthritis. The use of single-cell profiling approaches in spondyloarthritis research is still in its early stages. Challenges include high cost and limited availability of diseased tissue samples. To harness the full potential of the rapidly expanding technical capabilities, large-scale collaborative efforts are imperative.

Synovial Tissue Insights into Heterogeneity of Rheumatoid Arthritis

PURPOSE OF REVIEW

Rheumatoid arthritis is one of the most common rheumatic and autoimmune diseases. While it can affect many different organ systems, RA primarily involves inflammation in the synovium, the tissue that lines joints. Patients with RA exhibit significant clinical heterogeneity in terms of presence or absence of autoantibodies, degree of permanent deformities, and most importantly, treatment response. These clinical characteristics point to heterogeneity in the cellular and molecular pathogenesis of RA, an area that several recent studies have begun to address.

RECENT FINDINGS

Single-cell RNA-sequencing initiatives and deeper focused studies have revealed several RA-associated cell populations in synovial tissues, including peripheral helper T cells, autoimmunity-associated B cells (ABCs), and NOTCH3+ sublining fibroblasts. Recent large transcriptional studies and translational clinical trials present frameworks to capture cellular and molecular heterogeneity in RA synovium. Technological developments, such as spatial transcriptomics and machine learning, promise to further elucidate the different types of RA synovitis and the biological mechanisms that characterize them, key elements of precision medicine to optimize patient care and outcomes in RA. This review recaps the findings of those recent studies and puts our current knowledge and future challenges into scientific and clinical perspective.

The therapeutic potential of immunoengineering for systemic autoimmunity

Disease-modifying drugs have transformed the treatment options for many systemic autoimmune diseases. However, an evolving understanding of disease mechanisms, which might vary between individuals, is paving the way for the development of novel agents that operate in a patient-tailored manner through immunophenotypic regulation of disease-relevant cells and the microenvironment of affected tissue domains. Immunoengineering is a field that is focused on the application of engineering principles to the modulation of the immune system, and it could enable future personalized and immunoregulatory therapies for rheumatic diseases. An important aspect of immunoengineering is the harnessing of material chemistries to design technologies that span immunologically relevant length scales, to enhance or suppress immune responses by re-balancing effector and regulatory mechanisms in innate or adaptive immunity and rescue abnormalities underlying pathogenic inflammation. These materials are endowed with physicochemical properties that enable features such as localization in immune cells and organs, sustained delivery of immunoregulatory agents, and mimicry of key functions of lymphoid tissue. Immunoengineering applications already exist for disease management, and there is potential for this new discipline to improve disease modification in rheumatology.

Intensive training programme for ultrasound-guided minimally invasive synovial tissue biopsy on knees and wrists in different phases of inflammation

OBJECTIVES

To develop an intensive training programme for ultrasound (US)-guided synovial tissue (ST) biopsy on knees and wrists in inflammatory arthritis and to assess the learning curve, patient tolerability, sample quality and trainees' expectations.

METHODS

Active or remission rheumatoid arthritis patients were enrolled. Nine trainees joined the 4-month programme in a centre experienced in performing US-guided ST biopsies consisting of four sequential phases: (1) observation, (2) performance of guided step-by-step phases, (3) execution of the whole procedure on paired joints (knees or wrists) of the same patient in parallel with the trainer and (4) performance of the procedure autonomously. Sample representativity was assessed by histology, and procedure-related adverse events were recorded. Before and after the programme, trainees' expectations and perceptions were collected.

RESULTS

328 ST biopsy procedures were included. The rate of trainees' informative samples was: (1) comparable to the trainers in active and remission knees, but lower in active wrists (70% for trainees vs 100% for trainers, p=0.06) in phase 3; (2) excellent on active knees and wrists (91.9% and 90.9% respectively) but lower (77.6%, p=0.0089) on remission knees in phase 4. Procedures performed by trainees did not affect patient tolerability. Trainees' expectations about procedure-related invasiveness and pain infliction decreased while the difficulty of procedure execution on active wrists and remission knees remained perceived as moderately difficult.

CONCLUSIONS

This intensive training programme develops advanced skills in the performance of US-guided ST biopsy on knees and wrists, yielding high-quality specimens available for basic and translational studies on inflammatory joint diseases.

Profiling joint tissues at single-cell resolution: advances and insights

Advances in the profiling of human joint tissues at single-cell resolution have provided unique insights into the organization and function of these tissues in health and disease. Data generated by various single-cell technologies, including single-cell RNA sequencing and cytometry by time-of-flight, have identified the distinct subpopulations that constitute these tissues. These timely studies have provided the building blocks for the construction of single-cell atlases of joint tissues including cartilage, bone and synovium, leading to the identification of developmental trajectories, deciphering of crosstalk between cells and discovery of rare populations such as stem and progenitor cells. In addition, these studies have revealed unique pathogenetic populations that are potential therapeutic targets. The use of these approaches in synovial tissues has helped to identify how distinct cell subpopulations can orchestrate disease initiation and progression and be responsible for distinct pathological outcomes. Additionally, repair of tissues such as cartilage and meniscus remains an unmet medical need, and single-cell methodologies can be invaluable in providing a blueprint for both effective tissue-engineering strategies and therapeutic interventions for chronic joint diseases such as osteoarthritis and rheumatoid arthritis.

Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability

In autoimmune diseases such as rheumatoid arthritis, the immune system attacks the body's own cells. Developing a precise understanding of the cell states where noncoding autoimmune risk variants impart causal mechanisms is critical to developing curative therapies. Here, to identify noncoding regions with accessible chromatin that associate with cell-state-defining gene expression patterns, we leveraged multimodal single-nucleus RNA and assay for transposase-accessible chromatin (ATAC) sequencing data across 28,674 cells from the inflamed synovial tissue of 12 donors. Specifically, we used a multivariate Poisson model to predict peak accessibility from single-nucleus RNA sequencing principal components. For 14 autoimmune diseases, we discovered that cell-state-dependent ('dynamic') chromatin accessibility peaks in immune cell types were enriched for heritability, compared with cell-state-invariant ('cs-invariant') peaks. These dynamic peaks marked regulatory elements associated with T peripheral helper, regulatory T, dendritic and STAT1+CXCL10+ myeloid cell states. We argue that dynamic regulatory elements can help identify precise cell states enriched for disease-critical genetic variation.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.