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

Multi-lineage transcriptional and cell communication signatures define pathways in individuals at-risk for developing rheumatoid arthritis that initiate and perpetuate disease

Elevated anti-citrullinated protein antibodies (ACPA) levels in the peripheral blood are associated with an increased risk for developing rheumatoid arthritis (RA). Currently, no treatments are available that prevent progression to RA in these at-risk individuals. In addition, diverse pathogenic mechanisms underlying a common clinical phenotype in RA complicate therapy as no single agent is universally effective. We propose that a unifying set of transcription factor and their downstream pathways regulate a pro-inflammatory cell communication network, and that this network allows multiple cell types to serve as pathogenic drivers in at-risk individuals and in early RA. To test this hypothesis, we identified ACPA-positive at-risk individuals, patients with early ACPA-positive RA and matched controls. We measured single cell chromatin accessibility and transcriptomic profiles from their peripheral blood mononuclear cells. The datasets were then integrated to define key TF, as well as TF-regulated targets and pathways. A distinctive TF signature was enriched in early RA and at-risk individuals that involved key pathogenic mechanisms in RA, including SUMOylation, RUNX2, YAP1, NOTCH3, and β-Catenin Pathways. Interestingly, this signature was identified in multiple cell types, including T cells, B cells, and monocytes, and the pattern of cell type involvement varied among the at-risk and early RA participants, supporting our hypothesis. Similar patterns of individualized gene expression patterns and cell types were confirmed in single cell studies of RA synovium. Cell communication analysis provided biological validation that diverse lineages can deliver the same core set of pro-inflammatory mediators to receiver cells in vivo that subsequently orchestrate rheumatoid inflammation. These cell-type-specific signature pathways could explain the personalized pathogenesis of RA and contribute to the diversity of clinical responses to targeted therapies. Furthermore, these data could provide opportunities for stratifying individuals at-risk for RA, and selecting therapies tailored for prevention or treatment of RA. Overall, this study supports a new paradigm to understand how a common clinical phenotype could arise from diverse pathogenic mechanisms and demonstrates the relevance of peripheral blood cells to synovial disease.

Multi-lineage transcriptional and cell communication signatures define pathways in individuals at-risk for developing rheumatoid arthritis that initiate and perpetuate disease

Elevated anti-citrullinated protein antibodies (ACPA) levels in the peripheral blood are associated with an increased risk for developing rheumatoid arthritis (RA). Currently, no treatments are available that prevent progression to RA in these at-risk individuals. In addition, diverse pathogenic mechanisms underlying a common clinical phenotype in RA complicate therapy as no single agent is universally effective. We propose that a unifying set of transcription factor and their downstream pathways regulate a pro-inflammatory cell communication network, and that this network allows multiple cell types to serve as pathogenic drivers in at-risk individuals and in early RA. To test this hypothesis, we identified ACPA-positive at-risk individuals, patients with early ACPA-positive RA and matched controls. We measured single cell chromatin accessibility and transcriptomic profiles from their peripheral blood mononuclear cells. The datasets were then integrated to define key TF, as well as TF-regulated targets and pathways. A distinctive TF signature was enriched in early RA and at-risk individuals that involved key pathogenic mechanisms in RA, including SUMOylation, RUNX2, YAP1, NOTCH3, and β-Catenin Pathways. Interestingly, this signature was identified in multiple cell types, including T cells, B cells, and monocytes, and the pattern of cell type involvement varied among the at-risk and early RA participants, supporting our hypothesis. Similar patterns of individualized gene expression patterns and cell types were confirmed in single cell studies of RA synovium. Cell communication analysis revealed that the lineages displaying this RA TF signature deliver a common set of pro-inflammatory mediators to receiver cells that subsequently orchestrate rheumatoid inflammation. These cell-type-specific signature pathways could explain the personalized pathogenesis of RA and contribute to the diversity of clinical responses to targeted therapies. Furthermore, these data could provide opportunities for stratifying individuals at-risk for RA, and selecting therapies tailored for prevention or treatment of RA. Overall, this study supports a new paradigm to understand how a common clinical phenotype could arise from diverse pathogenic mechanisms and demonstrates the relevance of peripheral blood cells to synovial disease.

CellPhenoX: An eXplainable Cell-specific machine learning method to predict clinical Phenotypes using single-cell multi-omics

Single-cell technologies have enhanced our knowledge of molecular and cellular heterogeneity underlying disease. As the scale of single-cell datasets expands, linking cell-level phenotypic alterations with clinical outcomes becomes increasingly challenging. To address this, we introduce CellPhenoX, an eXplainable machine learning method to identify cell-specific phenotypes that influence clinical outcomes. CellPhenoX integrates classification models, explainable AI techniques, and a statistical framework to generate interpretable, cell-specific scores that uncover cell populations associated with relevant clinical phenotypes and interaction effects. We demonstrated the performance of CellPhenoX across diverse single-cell designs, including simulations, binary disease-control comparisons, and multi-class studies. Notably, CellPhenoX identified an activated monocyte phenotype in COVID-19, with expansion correlated with disease severity after adjusting for covariates and interactive effects. It also uncovered an inflammation-associated gradient in fibroblasts from ulcerative colitis. We anticipate that CellPhenoX holds the potential to detect clinically relevant phenotypic changes in single-cell data with multiple sources of variation, paving the way for translating single-cell findings into clinical impact.

T Cell Dysregulation in Rheumatoid Arthritis: from Genetic Susceptibility to Established Disease

PURPOSE OF REVIEW

Rheumatoid arthritis (RA) is a complex autoimmune disease characterized by chronic inflammation of the synovial tissue, where T cells play a central role in pathogenesis. Recent research has identified T peripheral helper (Tph) cells as critical mediators of local B cell activation in inflamed tissues. This review synthesizes the latest advancements in our understanding the of the role of T cells in RA, from initiation to established disease.

RECENT FINDINGS

We explore recent advances regarding the genetic and epigenetic factors that predispose individuals to RA, the mechanisms of T cell activation and differentiation, and the interactions between T cells and other immune and stromal cells within the synovial microenvironment. The emergence of Tph cells as key drivers of RA pathobiology is highlighted, along with their potential as therapeutic targets. We also discuss the heterogeneity of T cell responses and their interplay with synovial cells, while addressing critical research gaps such as the drivers of T cell recruitment and the plasticity of synovial phenotypes. A deeper understanding of T cell dynamics in RA will provide valuable insights for developing targeted therapies to modulate T cell-mediated inflammation and improve patient outcomes.

Systemic inflammation and lymphocyte activation precede rheumatoid arthritis

Some autoimmune diseases, including rheumatoid arthritis (RA), are preceded by a critical subclinical phase of disease activity. Proactive clinical management is hampered by a lack of biological understanding of this subclinical 'at-risk' state and the changes underlying disease development. In a cross-sectional and longitudinal multi-omics study of peripheral immunity in the autoantibody-positive at-risk for RA period, we identified systemic inflammation, proinflammatory-skewed B cells, expanded Tfh17-like cells, epigenetic bias in naive T cells, TNF+IL1B+ monocytes resembling a synovial macrophage population, and CD4 T cell transcriptional features resembling those suppressed by abatacept (CTLA4-Ig) in RA patients. Our findings characterize pathogenesis prior to clinical diagnosis and suggest the at-risk state exhibits substantial immune alterations that could potentially be targeted for early intervention to delay or prevent autoimmunity. We provide a suite of tools at https://apps.allenimmunology.org/aifi/insights/ra-progression/ to facilitate exploration and enhance accessibility of this extensive dataset.

An interdisciplinary perspective on peripheral drivers of pain in rheumatoid arthritis

Pain is one of the most debilitating symptoms of rheumatoid arthritis (RA), and yet remains poorly understood, especially when pain occurs in the absence of synovitis. Without active inflammation, experts most often attribute joint pain to central nervous system dysfunction. However, advances in the past 5 years in both immunology and neuroscience research suggest that chronic pain in RA is also driven by a variety of abnormal interactions between peripheral neurons and mediators produced by resident cells in the local joint environment. In this Review, we discuss these novel insights from an interdisciplinary neuro-immune perspective. We outline a potential working model for the peripheral drivers of pain in RA, which includes autoantibodies, resident immune and mesenchymal cells and their interactions with different subtypes of peripheral sensory neurons. We also offer suggestions for how future collaborative research could be designed to accelerate analgesic drug development.

Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying non-invasive, blood-based pathologic immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation in patients with LN and to identify correlates of renal parameters and treatment response. Unbiased analysis identified 3 immunologically distinct groups of patients with LN that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at one year. Patients with enriched circulating granzyme B+ T cells at baseline showed more severe disease and increased numbers of activated CD8 T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized primarily by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive by immunophenotyping at enrollment but with chronic renal injuries. Main immune profiles could be distilled down to 5 simple cytometric parameters that recapitulate several of the associations, highlighting the potential for blood immune profiling to translate to clinically useful non-invasive metrics to assess immune-mediated disease in LN.