Drivers of heterogeneity in synovial fibroblasts in rheumatoid arthritis.

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand activated states of the resident cells. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored drivers of fibroblast-like synoviocyte (FLS) heterogeneity in inflamed joints of patients with rheumatoid arthritis using paired single-cell RNA and ATAC sequencing, multiplexed imaging and spatial transcriptomics along with in vitro modeling of cell-extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell-derived cytokines, TNF, IFN-γ, IL-1ß or lack thereof, drive four distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium.

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)+HLA-DRAhi sublining fibroblasts, IL1B+ pro-inflammatory monocytes, ITGAX+TBX21+ autoimmune-associated B cells and PDCD1+ peripheral helper T (TPH) cells and follicular helper T (TFH) cells. We defined distinct subsets of CD8+ T cells characterized by GZMK+, GZMB+, and GNLY+ phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1+HLA-DRAhi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

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

Notch signalling drives synovial fibroblast identity and arthritis pathology.

The synovium is a mesenchymal tissue composed mainly of fibroblasts, with a lining and sublining that surround the joints. In rheumatoid arthritis the synovial tissue undergoes marked hyperplasia, becomes inflamed and invasive, and destroys the joint1,2. It has recently been shown that a subset of fibroblasts in the sublining undergoes a major expansion in rheumatoid arthritis that is linked to disease activity3-5; however, the molecular mechanism by which these fibroblasts differentiate and expand is unknown. Here we identify a critical role for NOTCH3 signalling in the differentiation of perivascular and sublining fibroblasts that express CD90 (encoded by THY1). Using single-cell RNA sequencing and synovial tissue organoids, we found that NOTCH3 signalling drives both transcriptional and spatial gradients-emanating from vascular endothelial cells outwards-in fibroblasts. In active rheumatoid arthritis, NOTCH3 and Notch target genes are markedly upregulated in synovial fibroblasts. In mice, the genetic deletion of Notch3 or the blockade of NOTCH3 signalling attenuates inflammation and prevents joint damage in inflammatory arthritis. Our results indicate that synovial fibroblasts exhibit a positional identity that is regulated by endothelium-derived Notch signalling, and that this stromal crosstalk pathway underlies inflammation and pathology in inflammatory arthritis.

Emerging synovial cell states in rheumatoid arthritis as potential therapeutic targets.

PURPOSE OF REVIEW: To summarize recently discovered novel cell states in rheumatoid arthritis (RA) synovium that could have important implications for disease treatment. RECENT FINDINGS: The use of multiomic technologies, including single-cell and spatial transcriptomics and mass cytometry, has led to the discovery of several novel cell states, which could have important implications for the treatment of RA. These cells can be found in patient blood, synovial fluid, or synovial tissue and span several immune cell subsets as well as stromal cell types. These diverse cell states may represent the targets of current or future therapeutics, while their fluctuations may inform the ideal timing for therapy. Future efforts are needed to implicate how each cell state functions in the pathophysiologic network within affected joints and how medications perturb each cell state and ultimately the tissue. SUMMARY: Multiomic molecular technologies have afforded the discovery of numerous novel cellular states in RA synovium; the next challenge will be to link these states to pathophysiology and treatment response.

Pathologically expanded peripheral T helper cell subset drives B cells in rheumatoid arthritis.

CD4+ T cells are central mediators of autoimmune pathology; however, defining their key effector functions in specific autoimmune diseases remains challenging. Pathogenic CD4+ T cells within affected tissues may be identified by expression of markers of recent activation. Here we use mass cytometry to analyse activated T cells in joint tissue from patients with rheumatoid arthritis, a chronic immune-mediated arthritis that affects up to 1% of the population. This approach revealed a markedly expanded population of PD-1hiCXCR5-CD4+ T cells in synovium of patients with rheumatoid arthritis. However, these cells are not exhausted, despite high PD-1 expression. Rather, using multidimensional cytometry, transcriptomics, and functional assays, we define a population of PD-1hiCXCR5- 'peripheral helper' T (TPH) cells that express factors enabling B-cell help, including IL-21, CXCL13, ICOS, and MAF. Like PD-1hiCXCR5+ T follicular helper cells, TPH cells induce plasma cell differentiation in vitro through IL-21 secretion and SLAMF5 interaction (refs 3, 4). However, global transcriptomics highlight differences between TPH cells and T follicular helper cells, including altered expression of BCL6 and BLIMP1 and unique expression of chemokine receptors that direct migration to inflamed sites, such as CCR2, CX3CR1, and CCR5, in TPH cells. TPH cells appear to be uniquely poised to promote B-cell responses and antibody production within pathologically inflamed non-lymphoid tissues.

Rheumatology in the era of precision medicine: synovial tissue molecular patterns and treatment response in rheumatoid arthritis.

PURPOSE OF REVIEW: A critical unmet need in rheumatoid arthritis (RA) is the identification of biomarkers that predict which of the available medications will be most effective for an individual in order to lower disease activity sooner than is afforded by the current treat-to-target approach. Here we will discuss recent reports examining the potential for synovial tissue molecular, cellular, and spatial profiling in defining objective measures of treatment response and therein developing personalized medicine for RA. RECENT FINDINGS: Recent high-dimensional molecular profiling of RA synovium has provided unprecedented resolution of the cell types and pathways in tissues affected by rheumatic diseases. Heightened attention to tissue architecture is also emerging as a means to classify individual disease variation that may allow patients to be further stratified by therapeutic response. Although this wealth of data may have already pinpointed promising biomarkers, additional studies, likely including tissue-based functional drug response assays, will be required to demonstrate how the complex tissue environment responds. SUMMARY: Molecular, cellular, and more recently spatial profiling of the RA synovium are uncovering fundamental features of the disease. Current investigations are examining whether this information will provide meaningful biomarkers for individualized medicine in RA.

Smyd2 controls cytoplasmic lysine methylation of Hsp90 and myofilament organization.

Protein lysine methylation is one of the most widespread post-translational modifications in the nuclei of eukaryotic cells. Methylated lysines on histones and nonhistone proteins promote the formation of protein complexes that control gene expression and DNA replication and repair. In the cytoplasm, however, the role of lysine methylation in protein complex formation is not well established. Here we report that the cytoplasmic protein chaperone Hsp90 is methylated by the lysine methyltransferase Smyd2 in various cell types. In muscle, Hsp90 methylation contributes to the formation of a protein complex containing Smyd2, Hsp90, and the sarcomeric protein titin. Deficiency in Smyd2 results in the loss of Hsp90 methylation, impaired titin stability, and altered muscle function. Collectively, our data reveal a cytoplasmic protein network that employs lysine methylation for the maintenance and function of skeletal muscle.

Synovial Tissue: Cellular and Molecular Phenotyping.

PURPOSE OF REVIEW: This review provides a summary of recent molecular findings that have refined our understanding of the cell types that constitute human synovial tissue, particularly in patients with rheumatoid arthritis (RA). RECENT FINDINGS: Recent advances in high-dimensional and single-cell assays have elucidated upwards of 20 cell subsets in the RA synovium. This includes novel fibroblast populations and lymphocyte phenotypes, which in many cases exhibit features that have not been found in other tissues thus far. Molecular profiling studies over the past several years have rapidly generated a comprehensive and detailed outline of the cellular phenotypes in synovial tissue affected by RA. Molecular features of these newly identified cell subsets immediately represent reasonable therapeutic targets and provide the opportunity to design the most clinically relevant mechanistic experiments. Broadly speaking, the ~ 20 cell types thus far identified in RA synovium seem to be fairly well conserved across patients, despite extensive heterogeneity in patient clinical features, stage of disease, and treatment responses. Thus, a next phase in molecular profiling may benefit from quantifying patient samples in terms of the ratios of cell types, with the rationale that certain cellular interactions will predominate in an individual and medications targeting these interactions may be more efficacious for that individual. Such cellular profiling in tissues combined with studies examining how the compendium of these cells interact in their three-dimensional tissue ultrastructures will be important in understanding how collectively these cells drive the disease process and ultimately how best to treat patients.

Increased Staphylococcus aureus Nasal Carriage Rates in Rheumatoid Arthritis Patients on Biologic Therapy.

BACKGROUND: Rheumatoid arthritis patients are at increased risk for periprosthetic joint infection after arthroplasty. The reason is multifactorial. Nasal colonization with Staphylococcus aureus is a modifiable risk factor; carriage rates in RA patients are unknown. The goal of this study is to determine the S aureus nasal carriage rates of RA patients on biologics, RA patients on traditional disease-modifying anti-rheumatic drugs (DMARDs), and osteoarthritis. METHODS: Consecutive patients with RA on biologics (±DMARDs), RA on non-biologic DMARDs, or OA were prospectively enrolled from April 2017 to May 2018. One hundred twenty-three patients were determined necessary per group to show a difference in carriage rates. Patients underwent a nasal swab and answered questions to identify additional risk factors. S aureus positive swabs were further categorized using spa typing. Logistic regression evaluated the association with S aureus colonization between the groups after controlling for known risk factors. RESULTS: RA patients on biologics, 70% of whom were on DMARDs, had statistically significant increase in S aureus colonization (37%) compared to RA on DMARDs alone (24%), or OA (20%) (P = .01 overall). After controlling for glucocorticoids, antibiotic use, recent hospitalization, and diabetes, RA on biologics had a significant increased risk of S aureus nasal colonization (Odds ratio 1.80, 95% confidence interval 1.00-3.22, P = .047). CONCLUSION: S aureus colonization risk was increased for RA on biologics compared to RA not on biologics and OA. Nasal S aureus carriage increases the risk of surgical site infection; this modifiable risk factor should be addressed prior to total joint arthroplasty for this higher risk patient group.

Modulation of TNF-induced macrophage polarization by synovial fibroblasts.

Mesenchymal stromal cells have emerged as powerful modulators of the immune system. In this study, we explored how the human macrophage response to TNF is regulated by human synovial fibroblasts, the representative stromal cell type in the synovial lining of joints that become activated during inflammatory arthritis. We found that synovial fibroblasts strongly suppressed TNF-mediated induction of an IFN-ß autocrine loop and downstream expression of IFN-stimulated genes (ISGs), including chemokines CXCL9 and CXCL10 that are characteristic of classical macrophage activation. TNF induced the production of soluble synovial fibroblast factors that suppressed the macrophage production of IFN-ß, and cooperated with TNF to limit the responsiveness of macrophages to IFN-ß by suppressing activation of Jak-STAT signaling. Genome-wide transcriptome analysis showed that cocultured synovial fibroblasts modulate the expression of approximately one third of TNF-regulated genes in macrophages, including genes in pathways important for macrophage survival and polarization toward an alternatively activated phenotype. Pathway analysis revealed that gene expression programs regulated by synovial fibroblasts in our coculture system were also regulated in rheumatoid arthritis synovial macrophages, suggesting that these fibroblast-mediated changes may contribute to rheumatoid arthritis pathogenesis. This work furthers our understanding of the interplay between innate immune and stromal cells during an inflammatory response, one that is particularly relevant to inflammatory arthritis. Our findings also identify modulation of macrophage phenotype as a new function for synovial fibroblasts that may prove to be a contributing factor in arthritis pathogenesis.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles.

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.

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.

Associations Between Rheumatoid Arthritis Clinical Factors and Synovial Cell Types and States.

OBJECTIVE: Recent studies have uncovered diverse cell types and states in the rheumatoid arthritis (RA) synovium; however, limited data exist correlating these findings with patient-level clinical information. Using the largest cohort to date with clinical and multicell data, we determined associations between RA clinical factors with cell types and states in the RA synovium. METHODS: The Accelerated Medicines Partnership Rheumatoid Arthritis study recruited patients with active RA who were not receiving disease-modifying antirheumatic drugs (DMARDs) or who had an inadequate response to methotrexate (MTX) or tumor necrosis factor inhibitors. RA clinical factors were systematically collected. Biopsies were performed on an inflamed joint, and tissue were disaggregated and processed with a cellular indexing of transcriptomes and epitopes sequencing pipeline from which the following cell type percentages and cell type abundance phenotypes (CTAPs) were derived: endothelial, fibroblast, and myeloid (EFM); fibroblasts; myeloid; T and B cells; T cells and fibroblasts (TF); and T and myeloid cells. Correlations were measured between RA clinical factors, cell type percentage, and CTAPs. RESULTS: We studied 72 patients (mean age 57 years, 75% women, 83% seropositive, mean RA duration 6.6 years, mean Disease Activity Score-28 C-reactive Protein 3 [DAS28-CRP3] score 4.8). Higher DAS28-CRP3 correlated with a higher T cell percentage (P < 0.01). Those receiving MTX and not a biologic DMARD (bDMARD) had a higher percentage of B cells versus those receiving no DMARDs (P < 0.01). Most of those receiving bDMARDs were categorized as EFM (57%), whereas none were TF. No significant difference was observed across CTAPs for age, sex, RA disease duration, or DAS28-CRP3. CONCLUSION: In this comprehensive screen of clinical factors, we observed differential associations between DMARDs and cell phenotypes, suggesting that RA therapies, more than other clinical factors, may impact cell type/state in the synovium and ultimately influence response to subsequent therapies.

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.

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.

Computer Vision Analysis of Rheumatoid Arthritis Synovium Reveals Lymphocytic Inflammation Is Associated With Immunoglobulin Skewing in Blood.

OBJECTIVE: We sought to develop computer vision methods to quantify aggregates of cells in synovial tissue and compare these with clinical and gene expression parameters. METHODS: We assembled a computer vision pipeline to quantify five features encompassing synovial cell density and aggregates and compared these with pathologist scores, disease classification, autoantibody status, and RNA expression in a cohort of 156 patients with rheumatoid arthritis (RA) and 149 patients with osteoarthritis (OA). RESULTS: All five features were associated with pathologist scores of synovial lymphocytic inflammation (P < 0.0001). Three features that related to the cells per unit of tissue were significantly increased in patients with both seronegative and seropositive RA compared with those with OA; on the other hand, aggregate features (number and diameter) were significantly increased in seropositive, but not seronegative, RA compared with OA. Aggregate diameter was associated with the gene expression of immunoglobulin heavy-chain genes in the synovial tissue. Compared with blood, synovial immunoglobulin isotypes were skewed from IGHM and IGHD to IGHG3 and IGHG1. Further, patients with RA with high levels of lymphocytic infiltrates in the synovium demonstrated parallel skewing in their blood with a relative decrease in IGHGM (P < 0.002) and IGHD (P < 0.03) and an increase in class-switched immunoglobulin genes IGHG3 (P < 0.03) and IGHG1 (P < 0.002). CONCLUSION: High-resolution automated identification and quantification of synovial immune cell aggregates uncovered skewing in the synovium from naïve IGHD and IGHM to memory IGHG3 and IGHG1 and revealed that this process is reflected in the blood of patients with high inflammatory synovium.

Clinical and Histological Features of Prosthetic Joint Infections May Differ in Patients With Inflammatory Arthritis and Osteoarthritis.

Background: Patients with inflammatory arthritis are at increased risk of prosthetic joint infections (PJIs), but diagnosis in these patients can be challenging because active inflammatory arthritis produces elevated inflammatory markers that may mimic those seen in PJI. Purpose: In this pilot study, we sought to identify the clinical, microbiologic, and histopathologic features of culture-positive and culture-negative PJI in patients with inflammatory arthritis who underwent total hip arthroplasty (THA) or total knee arthroplasty (TKA). We also sought to obtain preliminary data to support a definitive study of optimal methods for PJI diagnosis in patients with inflammatory arthritis. Methods: We performed a retrospective analysis of TKA and THA patients treated for PJI from 2009 to 2018 at a single tertiary care orthopedic institution. Data were extracted from a longitudinally maintained hospital infection database. We reviewed hematoxylin and eosin slides of osteoarthritis and inflammatory arthritis PJI cases matched 3:1, respectively, by age, sex, and culture status. Clinical characteristics were evaluated using the Fisher exact test, χ2 test, Student t test, and Mann-Whitney U test where appropriate. Results: A total of 807 PJI cases were identified (36 inflammatory arthritis and 771 osteoarthritis cases). Patients with inflammatory arthritis presented younger, had a higher Charlson Comorbidity Index, more frequently used glucocorticoids, were more likely women, and had a higher proportion of culture-negative PJI compared with osteoarthritis patients. Of the 88 inflammatory arthritis cases reviewed for histopathology, a higher proportion of culture-positive than culture-negative PJI cases had >10 polymorphonuclear leucocytes per high-power field and met Musculoskeletal Infection Society criteria but presented with less chronic inflammation. Conclusions: This retrospective prognostic study suggests that culture-negative PJI may be more frequent in patients with inflammatory arthritis than in those with osteoarthritis. Chronic infections, antibiotic use, or misdiagnosis may be contributing factors to unclear PJI diagnoses among culture-negative cases. This preliminary work supports the need for further studies to assess the differences in clinical features between culture-negative and culture-positive PJI in patients with inflammatory arthritis and the ability of biological diagnostic markers to discriminate between them in this population.

The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis.

Synovial tissue inflammation is the 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. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a CD8+ GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated 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.

Machine learning identification of thresholds to discriminate osteoarthritis and rheumatoid arthritis synovial inflammation.

BACKGROUND: We sought to identify features that distinguish osteoarthritis (OA) and rheumatoid arthritis (RA) hematoxylin and eosin (H&E)-stained synovial tissue samples. METHODS: We compared fourteen pathologist-scored histology features and computer vision-quantified cell density (147 OA and 60 RA patients) in H&E-stained synovial tissue samples from total knee replacement (TKR) explants. A random forest model was trained using disease state (OA vs RA) as a classifier and histology features and/or computer vision-quantified cell density as inputs. RESULTS: Synovium from OA patients had increased mast cells and fibrosis (p < 0.001), while synovium from RA patients exhibited increased lymphocytic inflammation, lining hyperplasia, neutrophils, detritus, plasma cells, binucleate plasma cells, sub-lining giant cells, fibrin (all p < 0.001), Russell bodies (p = 0.019), and synovial lining giant cells (p = 0.003). Fourteen pathologist-scored features allowed for discrimination between OA and RA, producing a micro-averaged area under the receiver operating curve (micro-AUC) of 0.85±0.06. This discriminatory ability was comparable to that of computer vision cell density alone (micro-AUC = 0.87±0.04). Combining the pathologist scores with the cell density metric improved the discriminatory power of the model (micro-AUC = 0.92±0.06). The optimal cell density threshold to distinguish OA from RA synovium was 3400 cells/mm2, which yielded a sensitivity of 0.82 and specificity of 0.82. CONCLUSIONS: H&E-stained images of TKR explant synovium can be correctly classified as OA or RA in 82% of samples. Cell density greater than 3400 cells/mm2 and the presence of mast cells and fibrosis are the most important features for making this distinction.