Dana E. Orange

Osteoarthritis (OA) and systemic sclerosis (SSc) are diseases with distinct etiologies but similar disease phenotypes, most prominently fibrosis, a process governed by the pathological activation of fibroblasts. Mechanisms underpinning fibrosis in these diseases are widely studied, though have yet to be directly compared. We employed single-cell RNA-seq and high-resolution spatial transcriptomics to describe the functional plasticity and the range of fibroblast activation states in both diseases. We identified disease-enriched fibroblast subsets conserved in both diseases, including fibrogenic myofibroblast-like cells, chemokine- and cytokine-expressing inflammatory fibroblasts, and lining-like fibroblasts. These subsets exhibited convergent fibrotic programs also observed in idiopathic pulmonary fibrosis, as well as overlapping osteochondral transcriptional programs. Xenium 5K spatial transcriptomics revealed that conserved, disease-associated fibroblasts reside in highly similar anatomic niches in OA synovium and SSc skin. These consisted of a fibrotic ECM-rich niche harboring myofibroblast-like cells and an inflammatory niche containing inflammatory fibroblasts adjacent to infiltrating immune cells. Disease-associated transcriptional remodeling converged on shared functional pathways and common putative upstream molecular regulators. These findings identify conserved cellular states, spatial niches, and regulatory programs across OA and SSc, suggesting that fibrotic disease is underpinned by shared pathogenic stromal states and candidate targets for therapeutic strategies are applicable across both diseases.

In chronic inflammatory diseases, maladaptive tissue remodeling is driven by a complex interplay of resident cells, immune infiltrates, and the extracellular matrix. In the autoimmune disorder rheumatoid arthritis (RA), synovial tissue undergoes massive expansion to form an invasive pannus that drives the erosion of cartilage and bone. The mechanisms mediating this aggressive growth are incompletely defined. Using spatial transcriptomic profiling of patient tissue, we detected an abundance of proliferating fibroblasts near the synovial tissue lining surface and adjacent to macrophages expressing high levels of secreted phosophoprotein-1 (encoding osteopontin; SPP1 ^hi macrophages). These synovial lining regions were also distinctly marked by deposits of the clot-forming protein fibrin. Although the SPP1 ^hi macrophages phenotypically resembled the profibrotic macrophages that drive lung and liver fibrosis, these niches were devoid of the dense highly ordered collagen that marks fibrosis. Functionally, we found that SPP1 ^hi macrophages degraded and phagocytosed fibrin matrices and promoted fibroblast proliferation. Given that fibrin provides transient matrices for de novo tissue generation in the context of wound healing, these data support a model of hyperplastic tissue outgrowth involving SPP1 ^hi macrophages, fibroblasts, and fibrin matrices adhered to the exterior synovial tissue surface. Whereas current RA therapies primarily aim to dampen proinflammatory responses, our findings provide the rationale for targeting progenerative pathways and SPP1 ^hi macrophages.

Objective: Pain in osteoarthritis (OA) is often discordant with structural joint damage, particularly in obesity-associated OA, where adipose-derived signals may drive nociception independently of cartilage pathology. Leptin has been demonstrated to be necessary, but not sufficient, to drive obesity-associated OA. Here, we tested the hypothesis that leptin mediates OA-associated pain through sensory neuron reprogramming rather than chondrocyte-intrinsic signaling, suggesting a fat-sensory nerve axis. Design: Male and female constitutive leptin-deficient (Ob/Ob), heterozygous (Ob/+), and wild-type (WT) mice, as well as chondrocyte-specific leptin receptor knockout mice (Aggrecan-CreERT2;LepRfl/fl), were challenged with destabilization of the medial meniscus (DMM) surgery to induce OA. Pain-related behaviors, joint pathology, serum cytokines, and lumbar dorsal root ganglia (DRG) transcriptomes were assessed. Human DRG cultures treated with leptin underwent transcriptomic profiling. Secondary analyses of human infrapatellar fat pad and synovium single-cell datasets evaluated leptin and leptin receptor expression patterns. Results: Chondrocyte-specific deletion of the leptin receptor did not mitigate OA pathology or pain. Global leptin-deficient (Ob/Ob) mice exhibited worse structural joint outcomes than WT and Ob/+ animals following DMM yet were robustly protected from OA-associated hyperalgesia – directly dissociating pain from structural pathology and demonstrating that leptin is involved in nociceptive sensitization. Serum cytokine profiles were sex-dependent and did not align with pain outcomes, separating systemic inflammation from nociceptive differences. Transcriptomic analysis of DRGs revealed that leptin drives enrichment of lipid metabolism, eicosanoid, and inflammatory programs, whereas leptin deficiency shifts sensory neurons toward a cytoskeletal remodeling state that does not sustain pain signaling. In human DRG cultures, leptin treatment produced a transcriptomic shift to enrich for neuronal excitability while vehicle treated cells were enriched for inflammatory signaling. Human infrapatellar fat pad and synovium transcriptomic data demonstrated adipocyte-enriched leptin expression and broad distribution of the leptin receptor across stromal, vascular, immune, and adipocyte populations. Conclusions: Leptin contributes to OA pain through neuro-immune crosstalk between adipose tissue and sensory neurons rather than through direct cartilage signaling. These findings identify leptin-associated neuronal programs linked to nociceptor sensitization and support targeting leptin-modulated neuro-immune pathways as a strategy to alleviate OA pain independently of structural disease progression.

Objectives: To identify synovial transcriptional clusters in human knee osteoarthritis (OA) and determine how these relate to synovial histologic features, cell-type-associated gene expression, and cartilage degeneration severity. Methods: Bulk RNA sequencing (RNA-seq) of synovial tissue from n = 135 patients with knee OA was analyzed using consensus clustering. Clusters were compared by clinical and histologic features, including cartilage degeneration severity (OARSI score). Single-cell RNA-seq (n = 18) and spatial transcriptomics were used to relate cartilage degeneration-associated gene expression patterns to synovial cell populations. Results: Four synovial transcriptional clusters that differed in synovial histologic features and cartilage degeneration severity were identified. Greater cartilage degeneration was associated with enrichment of lining fibroblast- and inflammatory myeloid-associated gene expression, whereas lesser cartilage degeneration was associated with enrichment of sublining fibroblast, endothelial, mural cell, and adipocyte-associated gene expression. Conclusions: Human knee OA synovium segregates into transcriptional clusters associated with cartilage degeneration severity. Synovial transcriptional heterogeneity corresponds to cell-type-associated gene expression.

Objective: The synovial tissue pathotype may determine the treatment response in rheumatoid arthritis (RA); however, biopsies are not widely available. Synovial fluid is a promising tissue surrogate. Our purpose was to compare RA synovial fluid cell counts with histopathology and use synovial fluid to predict tissue inflammation. Methods: Synovial fluid and tissue were collected during knee arthroplasty. Patients were stratified based on their medication treatment history. Synovial lymphocytic inflammation (SLI) was graded from low to high. Synovial fluid white blood cell (WBC) count and differentials were performed in the clinical laboratory. Descriptive statistics, correlations, receiver operating characteristic curve analysis, and multivariable regression were performed to determine the associations with tissue SLI. Results: Sixty‐four patients with RA had paired synovial tissue and synovial fluid data available. The mean Clinical Disease Activity Index (CDAI) score was 17.9. High tissue SLI was observed in 29 patients, and low SLI was observed in 35 patients, with roughly equal distribution among treatment groups. The mean synovial fluid WBC count was 5,661 cells/μL and was not correlated with CDAI but correlated positively with SLI and percentage polymorphonuclear cells (PMN%). Synovial fluid WBC count ≥1,400 cells/μL was sensitive (0.86) and specific (0.91) for high SLI (area under the curve 0.91). In a multivariable regression, PMN% was associated with high SLI (odds ratio [OR] 1.46 [95% confidence interval (CI) 1.14–1.85]). Synovial fluid monocyte percentage was negatively associated with high SLI (OR 0.44 [95% CI 0.27–0.73]). Conclusion: Synovial fluid WBC count is sensitive and specific for differentiating high and low lymphocytic synovial inflammation. Further analysis of the synovial fluid as it relates to the adjacent tissue in different cohorts is needed. image

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by antinuclear antibodies (ANAs). Epstein-Barr virus (EBV) infection has been epidemiologically associated with SLE, yet its role in pathogenesis remains incompletely defined. Here, we developed an EBV-specific single-cell RNA-sequencing platform and used it to demonstrate that EBV infection reprograms autoreactive antinuclear antigen B cells to drive autoimmunity in SLE. We demonstrated that, in SLE, EBV ⁺ B cells are predominantly CD27 ⁺ CD21 ^low memory B cells that are present at increased frequencies and express ZEB2 , TBX21 (T-bet), and antigen-presenting cell transcriptional pathways. Integrative analysis of chromatin immunoprecipitation sequencing (ChIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and RNA polymerase II occupancy data revealed EBV nuclear antigen 2 (EBNA2) binding at the transcriptional start sites and regulatory regions of CD27 , ZEB2 , and TBX21 , as well as the antigen-presenting cell genes demonstrated to be up-regulated in SLE EBV ⁺ B cells. We expressed recombinant antibodies from SLE EBV ⁺ B cells and demonstrated that they bind prototypical SLE nuclear autoantigens, whereas those from healthy individuals do not. We further found that SLE EBV ⁺ B cells can serve as antigen-presenting cells to drive activation of T peripheral helper cells with concomitant activation of related EBV ⁻ antinuclear double-negative 2 B cells and plasmablasts. Our results provide a mechanistic basis for EBV being a driver of SLE through infecting and reprogramming nuclear antigen-reactive B cells to become activated antigen-presenting cells with the potential to promote systemic disease–driving autoimmune responses.

The extracellular matrix (ECM) is the common denominator of more than 50 chronic diseases. Some of these chronic pathologies lead to enhanced tissue formation and deposition, whereas others are associated with increased tissue degradation, and some exhibit a combination of both, leading to severe tissue alterations. To develop effective therapies for diseases affecting the lung, liver, kidney, skin, intestine, musculoskeletal system, heart, and solid tumors, we need to modulate the ECM’s composition to restore its organization and function. Across diverse organ diseases, there are common denominators and distinguishing factors in this fibroinflammatory axis, which may be used to foster new insights into drug development across disease indications. The 2nd Extracellular Matrix Pharmacology Congress took place in Copenhagen, Denmark, from 17 to 19 June 2024 and was hosted by the International Society of Extracellular Matrix Pharmacology. The event was attended by 450 participants from 35 countries, among whom were prominent scientists who brought together state-of-the-art research on organ diseases and asked important questions to facilitate drug development. We highlight key aspects of the ECM in the liver, kidney, skin, intestine, musculoskeletal system, lungs, and solid tumors to advance our understanding of the ECM and its central targets in drug development. We also highlight key advances in the tools and technology that enable this drug development, thereby supporting the ECM.

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.

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. image