Clonal associations of lymphocyte subsets and functional states revealed by single cell antigen receptor profiling of T and B cells in rheumatoid arthritis synovium

Shared lung and joint T cell repertoire in early rheumatoid arthritis driven by cigarette smoking

OBJECTIVES

Smoking has been associated with an increased risk of developing rheumatoid arthritis (RA) in individuals carrying shared epitope (SE) HLA-DRB1 alleles. Yet, little is known about the regional and systemic T cell dynamics of smoking and a potential link to T cell infiltration in inflamed synovia. In this study, we, therefore, sought to study T cell features in lung and inflamed joints in smoking versus non-smoking patients.

METHODS

We set up a framework to monitor T cells in paired bronchoalveolar lavage fluid, blood and inflamed synovium tissue samples from 17 new-onset treatment naïve anticitrullinated protein antibody+RA patients. T cell receptor (TCR) repertoire of index-sorted tissue residing in T cells was determined by single-cell TCR sequencing coupled with deep immunophenotyping.

RESULTS

A significant enrichment of CD4+ and CD8+ T cells was seen in synovial samples from smoking versus non-smoking patients, along with an increase in expanded T cell clonotypes. This was particularly pronounced among SE+smokers, suggestive of a synergic gene-smoke effect. Strikingly, identical TCR clonalities were present in matched lung and joint samples of RA smokers, the majority being also detectable in circulation. This was mirrored by an increased clustering of lung and synovium TCRs across patients, suggesting a shared specificity by conserved motifs. The lung-joint shared T cell clonotypes showed a restricted TCR gene usage and exhibited a particular 4-1BB+CD57 hi effector profile within the inflamed synovium.

CONCLUSION

The data indicate a profound interplay between a strong MHC predisposition, smoking and induction of autoimmunity by shaping the TCR repertoire.

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.

B-Cell Receptor Repertoire: Recent Advances in Autoimmune Diseases

In the field of contemporary medicine, autoimmune diseases (AIDs) are a prevalent and debilitating group of illnesses. However, they present extensive and profound challenges in terms of etiology, pathogenesis, and treatment. A major reason for this is the elusive pathophysiological mechanisms driving disease onset. Increasing evidence suggests the indispensable role of B cells in the pathogenesis of autoimmune diseases. Interestingly, B-cell receptor (BCR) repertoires in autoimmune diseases display a distinct skewing that can provide insights into disease pathogenesis. Over the past few years, advances in high-throughput sequencing have provided powerful tools for analyzing B-cell repertoire to understand the mechanisms during the period of B-cell immune response. In this paper, we have provided an overview of the mechanisms and analytical methods for generating BCR repertoire diversity and summarize the latest research progress on BCR repertoire in autoimmune diseases, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), primary Sjögren's syndrome (pSS), multiple sclerosis (MS), and type 1 diabetes (T1D). Overall, B-cell repertoire analysis is a potent tool to understand the involvement of B cells in autoimmune diseases, facilitating the creation of innovative therapeutic strategies targeting specific B-cell clones or subsets.

B cell receptor repertoire abnormalities in autoimmune disease

B cells play a crucial role in the immune response and contribute to various autoimmune diseases. Recent studies have revealed abnormalities in the B cell receptor (BCR) repertoire of patients with autoimmune diseases, with distinct features observed among different diseases and B cell subsets. Classically, BCR repertoire was used as an identifier of distinct antigen-specific clonotypes, but the recent advancement of analyzing large-scale repertoire has enabled us to use it as a tool for characterizing cellular biology. In this review, we provide an overview of the BCR repertoire in autoimmune diseases incorporating insights from our latest research findings. In systemic lupus erythematosus (SLE), we observed a significant skew in the usage of VDJ genes, particularly in CD27+IgD+ unswitched memory B cells and plasmablasts. Notably, autoreactive clones within unswitched memory B cells were found to be increased and strongly associated with disease activity, underscoring the clinical significance of this subset. Similarly, various abnormalities in the BCR repertoire have been reported in other autoimmune diseases such as rheumatoid arthritis. Thus, BCR repertoire analysis holds potential for enhancing our understanding of the underlying mechanisms involved in autoimmune diseases. Moreover, it has the potential to predict treatment effects and identify therapeutic targets in autoimmune diseases.

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.

Application of single-cell RNA sequencing methods to develop B cell targeted treatments for autoimmunity

The COVID-19 pandemic coincided with several transformative advances in single-cell analysis. These new methods along with decades of research and trials with antibody therapeutics and RNA based technologies allowed for highly effective vaccines and treatments to be produced at astonishing speeds. While these tools were initially focused on models of infection, they also show promise in an autoimmune setting. Self-reactive B cells play important roles as antigen-presenting cells and cytokine and autoantibody producers for many autoimmune diseases. Yet, current therapies to target autoreactive B cells deplete all B cells irrespective of their pathogenicity. Development of self-reactive B cell targeting therapies that would spare non-pathogenic B cells are needed to treat disease while allowing effective immune responses to other ailments. Single-cell RNA sequencing (scRNA-seq) approaches will aid in identification of the pathogenic self-reactive B cells operative in autoimmunity and help with development of more favorable precision targeted therapies.

Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease with currently no universally highly effective prevention strategies. Identifying pathogenic immune phenotypes in 'At-Risk' populations prior to clinical disease onset is crucial to establishing effective prevention strategies. Here, we applied mass cytometry to deeply characterize the immunophenotypes in blood from At-Risk individuals identified through the presence of serum antibodies to citrullinated protein antigens (ACPA) and/or first-degree relative (FDR) status (n=52), as compared to established RA (n=67), and healthy controls (n=48). We identified significant cell expansions in At-Risk individuals compared with controls, including CCR2+CD4+ T cells, T peripheral helper (Tph) cells, type 1 T helper cells, and CXCR5+CD8+ T cells. We also found that CD15+ classical monocytes were specifically expanded in ACPA-negative FDRs, and an activated PAX5 low naïve B cell population was expanded in ACPA-positive FDRs. Further, we developed an "RA immunophenotype score" classification method based on the degree of enrichment of cell states relevant to established RA patients. This score significantly distinguished At-Risk individuals from controls. In all, we systematically identified activated lymphocyte phenotypes in At-Risk individuals, along with immunophenotypic differences among both ACPA+ and ACPA-FDR At-Risk subpopulations. Our classification model provides a promising approach for understanding RA pathogenesis with the goal to further improve prevention strategies and identify novel therapeutic targets.