Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial

Methotrexate promotes the release of granulocyte-macrophage colony-stimulating factor from rheumatoid arthritis fibroblast-like synoviocytes via autocrine interleukin-1 signaling

BACKGROUND

Activated fibroblast-like synoviocytes (FLS) are drivers of synovitis and structural joint damage in rheumatoid arthritis (RA). Despite the use of disease-modifying drugs, only about 50% of RA patients reach remission in real-world settings. We used an unbiased approach to investigate the effects of standard-of-care methotrexate (MTX) and a Janus kinase inhibitor, tofacitinib (TOFA), on gene expression in RA-FLS, in order to identify untargeted disease mediators.

METHODS

Primary RA-FLS were activated by stimulation with interleukin-1β (IL-1β) or platelet-derived growth factor + IL-1β in the presence or absence of MTX or TOFA, with or without additional inhibitors. Co-cultures of synovial cells were performed in direct and indirect systems. Cells were collected for RNA sequencing or qPCR, and supernatants were analyzed for protein concentrations.

RESULTS

Six thousand three hundred fifty genes were differentially expressed, the majority being upregulated, in MTX-treated activated RA-FLS and 970 genes, the majority being downregulated, in TOFA-treated samples. Pathway analysis showed that MTX had largest effects on 'Molecular mechanisms of cancer' and TOFA on 'Interferon signaling'. Targeted analysis of disease-associated genes revealed that MTX increased the expression of cell cycle-regulating genes but also of pro-inflammatory mediators like IL-1α (IL1A) and granulocyte-macrophage colony-stimulating factor, GM-CSF (CSF2). The MTX-promoted expression of CSF2 in activated RA-FLS peaked at 48 h, could be mediated via either NF-κB or AP-1 transcription factors, and was abrogated by IL-1 inhibitors (IRAK4 inhibitor and anakinra). In a co-culture setting, MTX-treatment of activated RA-FLS induced IL1B expression in macrophages.

CONCLUSIONS

MTX treatment induces secretion of IL-1 from activated RA-FLS which by autocrine signaling augments their release of GM-CSF. This unexpected effect of MTX might contribute to the persistence of synovitis.

Peripheral blood immunophenotypic diversity in patients with rheumatoid arthritis and its impact on therapeutic responsiveness

OBJECTIVE

Considering the diverse aetiologies and immunodysregulatory statuses observed in each patient with rheumatoid arthritis (RA), stratification based on peripheral blood immunophenotyping holds the potential to enhance therapeutic responses to molecular targeted therapies, biological/targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs).

METHODS

Immunophenotype analysis was conducted on a cohort of over 500 b/tsDMARDs-naïve patients using flow cytometry. Patients with RA were stratified based on their immunophenotypes, and the treatment response to each targeted therapy was evaluated. Validation was performed using an additional cohort of 183 b/tsDMARDs-naïve patients with RA.

RESULTS

Patients with RA were stratified into five clusters, two of which exhibited distinct RA phenotypes compared with controls, characterised by significant increases in CD4+ effector memory T cells re-expressing CD45RA. Notably, the effectiveness of different b/tsDMARDs varied across clusters. The group using promising b/tsDMARDs was labelled as 'expected' whereas the 'non-expected' group comprised those using others. The expected group outperformed the non-expected group with higher 26-week remission rates (39.9% vs 24.6%, p=0.0004) and low disease activity achievement (80.8% vs 60.2%, p<0.0001). Trajectory analysis showed the non-expected group's 26-week disease activity was influenced by Clinical Disease Activity Index at baseline unlike the expected group. Additionally, different molecular targeted therapies influenced the proportions of each immune cell subset variably. To validate, immunophenotyping was performed on a validation cohort. When 183 cases were grouped based on their b/tsDMARDs usage into expected/non-expected groups, the expected group had a higher remission rate (p=0.0021), further confirming the observed trend.

CONCLUSION

Our findings offer valuable insights into the diversity of RA and potential therapeutic strategies grounded in the molecular underpinnings.

Machine learning in the prediction of treatment response in rheumatoid arthritis: A systematic review

OBJECTIVE

This study aimed to investigate the current status and performance of machine learning (ML) approaches in providing reproducible treatment response predictions.

METHODS

This systematic review was conducted in accordance with the PRISMA statement and the CHARMS checklist. We searched PubMed, Cochrane Library, Web of Science, Scopus, and EBSCO databases for cohort studies that derived and/or validated ML models focused on predicting rheumatoid arthritis (RA) treatment response. We extracted data and critically appraised studies based on the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) and Prediction Model Risk of Bias Assessment Tool (PROBAST) guidelines.

RESULTS

From 210 unduplicated records identified by the literature search, we retained 29 eligible studies. Of these studies, 10 developed a predictive model and reported a mean adherence to the TRIPOD guidelines of 45.6 % (95 % CI: 38.3-52.8 %). The remaining 19 studies not only developed a predictive model but also validated it externally, with a mean adherence of 42.9 % (95 % CI: 39.1-46.6 %). Most of the articles had an unclear risk of bias (41.4 %), followed by a high risk of bias, which was present in 37.9 %.

CONCLUSIONS

In recent years, ML methods have been increasingly used to predict treatment response in RA. Our critical appraisal revealed unclear and high risk of bias in most of the identified models, suggesting that researchers can do more to address the risk of bias and increase transparency, including the use of calibration measures and reporting methods for handling missing data.

FUNDING

None.

Another Notch in the Belt of Rheumatoid Arthritis

Notch ligands and receptors, including JAG1/2, DLL1/4, and Notch1/3, are enriched on macrophages (MΦs), fibroblast-like synoviocytes (FLS), and/or endothelial cells in rheumatoid arthritis (RA) compared with normal synovial tissues (ST). Power Doppler ultrasound-guided ST studies reveal that the Notch family is highly involved in early active RA, especially during neovascularization. In contrast, the Notch family is not implicated during the erosive stage, evidenced by their lack of correlation with radiographic damage in RA ST. Toll-like receptors and tumor necrosis factor (TNF) are the common inducers of Notch expression in RA MΦs, FLS, and endothelial cells. Among Notch ligands, JAG1 and/or DLL4 are most inducible by inflammatory responses in RA MΦs or endothelial cells and transactivate their receptors on RA FLS. TNF plays a central role on Notch ligands, as anti-TNF good responders display JAG1/2 and DLL1/4 transcriptional downregulation in RA ST myeloid cells. In in vitro studies, TNF increases Notch3 expression in MΦs, which is further amplified by RA FLS addition. Specific disease-modifying antirheumatic drugs reduced JAG1 and Notch3 expression in MΦ and RA FLS cocultures. Organoids containing FLS and endothelial cells have increased expression of JAG1 and Notch3. Nonetheless, Methotrexate, interleukin-6 receptor (IL-6R) antibodies, and B cell blockers are mostly ineffective at decreasing Notch family expression. NF-κB, MAPK, and AKT pathways are involved in Notch signaling, whereas JAK/STATs are not. Although Notch blockade has been effective in RA preclinical studies, its small molecule inhibitors have failed in phase I and II studies, suggesting that alternative strategies may be required to intercept their function.

On difficulties to define prognostic factors for clinical practice in rheumatoid arthritis

In rheumatoid arthritis (RA), the identification of prognostic factors (PF) capable of predicting disease outcome, response to treatment or success of dose reduction is an important issue, as these factors are intended to serve as a basis for decision-making. The task is complex from the outset, as the definition of disease prognosis or therapeutic prognosis is not uniquevocal. The heterogeneity of the definitions used partly explains the failure to identify PF that can be applied at an individual level. But other factors also contribute. First, the scope of the disease studied is too broad, including nosologically different entities. Second, potential PF are only measured at a single point of time, whereas changes over a period of time should be taken into account to a greater extent, not forgetting the potential impact of the treatment received during this period. Beyond these limiting factors, one of the main obstacles to the identification of PF is probably the fact that the phase of the disease is not sufficiently taken into account. Predicting the disease outcome when it is well established is a more complex challenge than when it is just beginning, as many factors are likely to interfere. The same applies to therapeutic PF, which should be determined according to disease duration. Difficulties also arise from the approaches used, which are often restricted to a single field of interest whereas they should be much more integrative and call on new large-scale data analysis tools with a view to precision medicine.In RA, prognosis can be defined at two levels: disease outcome, including joint damage and risk of extra-articular manifestations and/or complications, and treatment outcome, including response to therapy, risk of adverse effects and drug-free remission.

Diminished expression of the ubiquitin-proteasome system in early treatment-naïve patients with rheumatoid arthritis and concomitant type 2 diabetes may be linked to IL-1 pathway hyper-activity; results from PEAC cohort

OBJECTIVE

Based on the recent evidence of IL-1 inhibition in patients with rheumatoid arthritis (RA) and concomitant type 2 diabetes (T2D), we evaluated the synovial tissue expression of IL-1 related genes in relationship to the ubiquitin-proteasome system and the effects of insulin on ubiquitinated proteins in fibroblast-like synoviocytes (FLSs).

METHODS

The synovial expression of IL-1 pathway genes was compared in early (< 1 year) treatment-naïve RA patients with T2D (RA/T2D n = 16) and age- and sex-matched RA patients without T2D (n = 16), enrolled in the Pathobiology of Early Arthritis Cohort (PEAC). The synovial expression of ubiquitin in macrophages and synovial lining fibroblasts was also assessed by Immunohistochemistry/immunofluorescence and correlated with synovial pathotypes. Finally, FLSs from RA patients (n = 5) were isolated and treated with human insulin (200 and 500 nM) and ubiquitinated proteins were assessed by western blot.

RESULTS

Synovial tissues of RA/T2D patients were characterised by a consistent reduced expression of ubiquitin-proteasome genes. More specifically, ubiquitin genes (UBB, UBC, and UBA52) and genes codifying proteasome subunits (PSMA2, PSMA6, PSMA7, PSMB1, PSMB3, PSMB4, PSMB6, PSMB8, PSMB9, PSMB10, PSMC1, PSMD9, PSME1, and PSME2) were significantly lower in RA/T2D patients. On the contrary, genes regulating fibroblast functions (FGF7, FGF10, FRS2, FGFR3, and SOS1), and genes linked to IL-1 pathway hyper-activity (APP, IRAK2, and OSMR) were upregulated in RA/T2D. Immunohistochemistry showed a significant reduction of the percentage of ubiquitin-positive cells in synovial tissues of RA/T2D patients. Ubiquitin-positive cells were also increased in patients with a lympho-myeloid pathotype compared to diffuse myeloid or pauci-immune-fibroid. Finally, in vitro experiments showed a reduction of ubiquitinated proteins in RA-FLSs treated with a high concentration of insulin (500 nM).

CONCLUSIONS

A different IL-1 pathway gene expression was observed in the synovial tissues of early treatment-naïve RA/T2D patients, linked to decreased expression of the ubiquitin-proteasome system. These findings may provide a mechanistic explanation of the observed clinical benefits of IL-1 inhibition in patients with RA and concomitant T2D.

Loss of synovial tissue macrophage homeostasis precedes rheumatoid arthritis clinical onset

This study performed an in-depth investigation into the myeloid cellular landscape in the synovium of patients with rheumatoid arthritis (RA), "individuals at risk" of RA, and healthy controls (HC). Flow cytometric analysis demonstrated the presence of a CD40-expressing CD206+CD163+ macrophage population dominating the inflamed RA synovium, associated with disease activity and treatment response. In-depth RNA sequencing and metabolic analysis demonstrated that this macrophage population is transcriptionally distinct, displaying unique inflammatory and tissue-resident gene signatures, has a stable bioenergetic profile, and regulates stromal cell responses. Single-cell RNA sequencing profiling of 67,908 RA and HC synovial tissue cells identified nine transcriptionally distinct macrophage clusters. IL-1B+CCL20+ and SPP1+MT2A+ are the principal macrophage clusters in RA synovium, displaying heightened CD40 gene expression, capable of shaping stromal cell responses, and are importantly enriched before disease onset. Combined, these findings identify the presence of an early pathogenic myeloid signature that shapes the RA joint microenvironment and represents a unique opportunity for early diagnosis and therapeutic intervention.

The Contribution of Macrophage Plasticity to Inflammatory Arthritis and Their Potential as Therapeutic Targets

Inflammatory arthritis are common chronic inflammatory autoimmune diseases characterised by progressive, destructive inflammation of the joints leading to a loss of function and significant comorbidities; importantly, there are no cures and only 20% of patients achieve drug-free remission for over 2 years. Macrophages play a vital role in maintaining homeostasis, however, under the wrong environmental cues, become drivers of chronic synovial inflammation. Based on the current "dogma", M1 macrophages secrete pro-inflammatory cytokines and chemokines, promoting tissue degradation and joint and bone erosion which over time lead to accelerated disease progression. On the other hand, M2 macrophages secrete anti-inflammatory mediators associated with wound healing, tissue remodelling and the resolution of inflammation. Currently, four subtypes of M2 macrophages have been identified, namely M2a, M2b, M2c and M2d. However, more subtypes may exist due to macrophage plasticity and the ability for repolarisation. Macrophages are highly plastic, and polarisation exists as a continuum with diverse intermediate phenotypes. This plasticity is achieved by a highly amenable epigenome in response to environmental stimuli and shifts in metabolism. Initiating treatment during the early stages of disease is important for improved prognosis and patient outcomes. Currently, no treatment targeting macrophages specifically is available. Such therapeutics are being investigated in ongoing clinical trials. The repolarisation of pro-inflammatory macrophages towards the anti-inflammatory phenotype has been proposed as an effective approach in targeting the M1/M2 imbalance, and in turn is a potential therapeutic strategy for IA diseases. Therefore, elucidating the mechanisms that govern macrophage plasticity is fundamental for the success of novel macrophage targeting therapeutics.

Truth unveiled by time and the marbled definition of D2T-RA: retrospective analysis on the persistence of the difficult-to-treat status among refractory RA patients

BACKGROUND

The current EULAR definition of difficult-to-treat rheumatoid arthritis (D2T-RA) identifies patients with active disease refractory to multiple treatments at a single time point, without considering the persistence of this condition over time. The study aimed to assess difficult-to-treat rheumatoid arthritis (D2T-RA) over 12 months, considering persistence over time rather than a single time point, in a real-life cohort.

METHODS

In a single-center real-life cohort, demographic and clinic data were cross-sectionally collected for each patient at baseline and retrospectively over the previous 12 months bimonthly. For each timepoint, the prevalence of D2T-RA patients was calculated, and patients meeting the EULAR definition for at least 6 months were defined as persistent D2T-RA (pD2T-RA). Finally, the clinical characteristics associated with the time-based definition of pD2T-RA were analyzed.

RESULTS

Among 610 adult RA patients, 104 were refractory to ≥ 2 treatments. Initially, 41.3% met D2T-RA criteria, but only 27.9% fulfilled persistent D2T-RA (pD2T-RA) criteria over 6 months. The pD2T-RA group was associated with male gender, higher HAQ and Charlson Comorbidity Index scores, more failed treatments, and use of non-NSAID analgesics. Logistic regression linked pD2T-RA to higher SDAI and CRP values, and the use of glucocorticoids or analgesics. Chronic use of glucocorticoids was strongly associated with pD2T-RA.

CONCLUSIONS

The application of a temporal criterion allowed for the selection of a subgroup of pD2T-RA patients who differ from those who meet the definition of D2T-RA only episodically. Chronic use of glucocorticoids was the factor most strongly associated with pD2T-RA status.

A best practices framework for spatial biology studies in drug discovery and development: enabling successful cohort studies using digital spatial profiling

The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard 'omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell-cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue

Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.

Fcγ-receptor-IIIA bioactivity of circulating and synovial immune complexes in rheumatoid arthritis

OBJECTIVE

Previous technical limitations prevented the proof of Fcγ-receptor (FcγR)-activation by soluble immune complexes (sICs) in patients. FcγRIIIa (CD16) is a risk factor in rheumatoid arthritis (RA). We aimed at determining the presence of CD16-activating sICs in RA and control diseases.

METHODS

Sera from an exploratory cohort (n=50 patients with RA) and a validation cohort (n=106 patients with RA, 20 patients with psoriasis arthritis (PsA), 22 patients with systemic lupus erythematosus (SLE) and 31 healthy controls) were analysed using a new reporter cell assay. Additionally, 26 synovial fluid samples were analysed, including paired serum/synovial samples.

RESULTS

For the first time using a reliable and sensitive functional assay, the presence of sICs in RA sera was confirmed. sICs possess an intrinsic capacity to activate CD16 and can be found in both synovial fluid and in blood. In low experimental dilutions, circulating sICs were also detected in a subset of healthy people and in PsA. However, we report a significantly increased frequency of bioactive circulating sICs in RA. While the bioactivity of circulating sICs was low and did not correlate with clinical parameters, synovial sICs were highly bioactive and correlated with serum autoantibody levels. Receiver operator curves indicated that sICs bioactivity in synovial fluid could be used to discriminate immune complex-associated arthritis from non-associated forms. Finally, circulating sICs were more frequently found in SLE than in RA. The degree of CD16 bioactivity showed strong donor-dependent differences, especially in SLE.

CONCLUSIONS

RA is characterised by the presence of circulating and synovial sICs that can engage and activate CD16.

Unraveling immune cell heterogeneity in autoimmune arthritis: insights from single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of immune-mediated arthritis, which comprises rheumatoid arthritis and spondyloarthritis. This review outlines the key findings and advancements in scRNA-seq studies focused on the pathogenesis of autoimmune arthritis and its clinical application. In rheumatoid arthritis, scRNA-seq has elucidated the heterogeneity among synovial fibroblasts and immune cell subsets in inflammatory sites, offering insights into disease mechanisms and the differences in treatment responses. Various studies have identified distinct synovial fibroblast subpopulations, such as THY1+ inflammatory and THY1- destructive fibroblasts. Furthermore, scRNA-seq has revealed diverse T cell profiles in the synovium, including peripheral helper T cells and clonally expanded CD8+ T cells, shedding light on potential therapeutic targets and predictive markers of treatment response. Similarly, in spondyloarthritis, particularly psoriatic arthritis and ankylosing spondylitis, scRNA-seq studies have identified distinct cellular profiles associated with disease pathology. Challenges such as cost and sample size limitations persist, but collaborative efforts and utilization of public databases hold promise for overcoming these obstacles. Overall, scRNA-seq emerges as a powerful tool for dissecting cellular heterogeneity and driving precision medicine in immune-mediated arthritis.

Molecular and cellular dynamics of the developing human neocortex at single-cell resolution

The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation1. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.

Synovial 5-Lipoxygenase-Derived Oxylipins Define a Lympho-Myeloid-Enriched Synovium

OBJECTIVE

Oxylipins are bioactive lipids derived from polyunsaturated fatty acids (PUFAs) that modulate inflammation and may remain overexpressed in refractory synovitis. In plasma, they could also be biomarkers of synovial pathology. The aim of this study is to determine if synovial oxylipins in inflamed joints correlate with plasma oxylipins and with synovial histologic patterns.

METHODS

Patients with established rheumatoid or psoriatic arthritis with active disease despite treatment were recruited, and paired synovial tissue (ST) and plasma were collected. Oxylipins were determined by liquid chromatography with tandem mass spectrometry and were classified into groups according to their PUFA precursor and enzyme. The expression of CD20, CD68, CD3, and CD138 was obtained to describe synovial histology. Cell-specific expression of oxylipin-related genes was identified by examining available synovial single-cell RNA sequencing data.

RESULTS

We included a total of 32 ST and 26 paired-plasma samples. A total of 71 oxylipins were identified in ST, but only 24 were identified in plasma. Only levels of 9,10-dihydroxyoctadecenoic acid and tetranor-Prostaglandin FM had a significant positive correlation between plasma and ST. Several oxylipins and oxylipin-related genes were differentially expressed among synovial phenotypes. Specifically, several 5-lipoxygenase (LOX)-derived oxylipins were statistically elevated in the lympho-myeloid phenotype and associated with B cell expression in rheumatoid arthritis samples.

CONCLUSION

The lack of correlation between ST and plasma oxylipins suggests that ST lipid profiling better characterizes active pathways in treated joints. Synovial 5-LOX-derived oxylipins were highly expressed in lympho-myeloid-enriched synovium. Combination therapy with 5-LOX inhibitors to improve refractory inflammation may be needed in patients with this histologic group.

CCR4 predicts the efficacy of abatacept in rheumatoid arthritis patients through the estimation of Th17 and Treg cell abundance

OBJECTIVES

Predicting the efficacy of biological disease-modifying antirheumatic drugs is challenging. In this study, we aimed to explore markers that predict the efficacy of abatacept in rheumatoid arthritis (RA) patients.

METHODS

Thirty RA patients receiving abatacept were recruited, and peripheral blood mononuclear cells from the participants were subjected to DNA microarray analysis. The expression of CC chemokine receptor 4 (CCR4), which was selected by the result of DNA microarray, was determined by flow cytometry in 16 newly diagnosed treatment-naïve RA patients. CCR4 expression on each helper T-cell subset was also measured.

RESULTS

CCR4 was upregulated in the abatacept responder. The expression levels of CCR4 were significantly correlated with the improvement of the Clinical Disease Activity Index. CCR4 expression was predominantly observed in CD4+ T cells in peripheral blood mononuclear cells. The percentage of CCR4-expressing CD4+ T cells was significantly higher in RA patients than in healthy individuals. Interestingly, Th17 and Treg cells expressed high levels of CCR4 compared to non-Th17-related helper T cells.

CONCLUSIONS

CCR4 is a Th17- and Treg-related gene, and the high CCR4 expression in peripheral blood samples may predict the efficacy of abatacept in RA.

Machine Learning Prediction of Treatment Response to Biological Disease-Modifying Antirheumatic Drugs in Rheumatoid Arthritis

Background: Disease-modifying antirheumatic drugs (bDMARDs) have shown efficacy in treating Rheumatoid Arthritis (RA). Predicting treatment outcomes for RA is crucial as approximately 30% of patients do not respond to bDMARDs and only half achieve a sustained response. This study aims to leverage machine learning to predict both initial response at 6 months and sustained response at 12 months using baseline clinical data. Methods: Baseline clinical data were collected from 154 RA patients treated at the University Hospital in Erlangen, Germany. Five machine learning models were compared: Extreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), K-nearest neighbors (KNN), Support Vector Machines (SVM), and Random Forest. Nested cross-validation was employed to ensure robustness and avoid overfitting, integrating hyperparameter tuning within its process. Results: XGBoost achieved the highest accuracy for predicting initial response (AUC-ROC of 0.91), while AdaBoost was the most effective for sustained response (AUC-ROC of 0.84). Key predictors included the Disease Activity Score-28 using erythrocyte sedimentation rate (DAS28-ESR), with higher scores at baseline associated with lower response chances at 6 and 12 months. Shapley additive explanations (SHAP) identified the most important baseline features and visualized their directional effects on treatment response and sustained response. Conclusions: These findings can enhance RA treatment plans and support clinical decision-making, ultimately improving patient outcomes by predicting response before starting medication.

Tailoring the treatment of inflammatory rheumatic diseases by a better stratification and characterization of the clinical patient heterogeneity. Findings from a systematic literature review and experts' consensus

Inflammatory rheumatic diseases are different pathologic conditions associated with a deregulated immune response, codified along a spectrum of disorders, with autoinflammatory and autoimmune diseases as two-end phenotypes of this continuum. Despite pathogenic differences, inflammatory rheumatic diseases are commonly managed with a limited number of immunosuppressive drugs, sometimes with partial evidence or transferring physicians' knowledge in different patients. In addition, several randomized clinical trials, enrolling these patients, did not meet the primary pre-established outcomes and these findings could be linked to the underlying molecular diversities along the spectrum of inflammatory rheumatic disorders. In fact, the resulting patient heterogeneity may be driven by differences in underlying molecular pathology also resulting in variable responses to immunosuppressive drugs. Thus, the identification of different clinical subsets may possibly overcome the major obstacles that limit the development more effective therapeutic strategies for these patients with inflammatory rheumatic diseases. This clinical heterogeneity could require a diverse therapeutic management to improve patient outcomes and increase the frequency of clinical remission. Therefore, the importance of better patient stratification and characterization is increasingly pointed out according to the precision medicine principles, also suggesting a new approach for disease treatment. In fact, based on a better proposed patient profiling, clinicians could more appropriately balance the therapeutic management. On these bases, we synthetized and discussed the available literature about the patient profiling in regard to therapy in the context of inflammatory rheumatic diseases, mainly focusing on randomized clinical trials. We provided an overview of the importance of a better stratification and characterization of the clinical heterogeneity of patients with inflammatory rheumatic diseases identifying this point as crucial in improving the management of these patients.

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.

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.

Advancing precision rheumatology: applications of machine learning for rheumatoid arthritis management

Rheumatoid arthritis (RA) is an autoimmune disease causing progressive joint damage. Early diagnosis and treatment is critical, but remains challenging due to RA complexity and heterogeneity. Machine learning (ML) techniques may enhance RA management by identifying patterns within multidimensional biomedical data to improve classification, diagnosis, and treatment predictions. In this review, we summarize the applications of ML for RA management. Emerging studies or applications have developed diagnostic and predictive models for RA that utilize a variety of data modalities, including electronic health records, imaging, and multi-omics data. High-performance supervised learning models have demonstrated an Area Under the Curve (AUC) exceeding 0.85, which is used for identifying RA patients and predicting treatment responses. Unsupervised learning has revealed potential RA subtypes. Ongoing research is integrating multimodal data with deep learning to further improve performance. However, key challenges remain regarding model overfitting, generalizability, validation in clinical settings, and interpretability. Small sample sizes and lack of diverse population testing risks overestimating model performance. Prospective studies evaluating real-world clinical utility are lacking. Enhancing model interpretability is critical for clinician acceptance. In summary, while ML shows promise for transforming RA management through earlier diagnosis and optimized treatment, larger scale multisite data, prospective clinical validation of interpretable models, and testing across diverse populations is still needed. As these gaps are addressed, ML may pave the way towards precision medicine in RA.

Five-year follow-up of patients with difficult-to-treat rheumatoid arthritis

OBJECTIVES

To elucidate the long-term outcomes of patients with difficult-to-treat rheumatoid arthritis (D2T RA).

METHODS

We collected data on the clinical course of patients who had been identified as D2T RA in 2018 until 2023. We stratified the patients according to outcomes at the last visit: resolved D2T RA, persistent D2T RA, and mortality. We compared their clinical characteristics and investigated the predictive factors for the resolution of D2T RA or mortality. Furthermore, we investigated the impact of the causes of D2T RA identified in 2018, multidrug resistance, comorbidities, and socioeconomic factors on outcomes in 2023.

RESULTS

Of 173 patients identified as D2T RA in 2018, 150 were included in the analysis. Among them, D2T RA was resolved in 67 (45%), 75 (50%) remained as D2T RA, and 8 (5%) died. Patients with resolved D2T RA were significantly younger at the latest visit (p= 0.02), had a higher proportion of treatment changes during five years (p= 0.002), and had a higher proportion of interleukin-6 receptor inhibitors use in 2023 (p= 0.04) than those in patients with persistent D2T RA or those who died. D2T RA resolved in 38% of patients with multidrug resistance, mainly with treatment changes. Rheumatic disease comorbidity index and glucocorticoid dose escalation were independent risk factors for mortality (odds ratio [OR], 3.50; p= 0.02 and OR, 31.9; p= 0.002, respectively).

CONCLUSION

Further modifications in RA treatment are useful for resolving D2T RA. Multiple comorbidities and glucocorticoid use are associated with mortality.

Bispecific T cell engager therapy for refractory rheumatoid arthritis

Bispecific T cell engagers (BiTEs) kill B cells by engaging T cells. BiTEs are highly effective in acute lymphoblastic leukemia. Here we treated six patients with multidrug-resistant rheumatoid arthritis (RA) with the CD19xCD3 BiTE blinatumomab under compassionate use. Low doses of blinatumomab led to B cell depletion and concomitant decrease of T cells, documenting their engager function. Treatment was safe, with brief increase in body temperature and acute phase proteins during first infusion but no signs of clinically relevant cytokine-release syndrome. Blinatumomab led to a rapid decline in RA clinical disease activity in all patients, improved synovitis in ultrasound and FAPI-PET-CT and reduced autoantibodies. High-dimensional flow cytometry analysis of B cells documented an immune reset with depletion of activated memory B cells, which were replaced by nonclass-switched IgD-positive naïve B cells. Together, these data suggest the feasibility and potential for BiTEs to treat RA. This approach warrants further exploration on other B-cell-mediated autoimmune diseases.

Reasons for multiple biologic and targeted synthetic DMARD switching and characteristics of treatment refractory rheumatoid arthritis

OBJECTIVE

Switching biologic and targeted synthetic DMARD (b/tsDMARD) medications occurs commonly in RA patients, however data are limited on the reasons for these changes. The objective of the study was to identify and categorize reasons for b/tsDMARD switching and investigate characteristics associated with treatment refractory RA.

METHODS

In a multi-hospital RA electronic health record (EHR) cohort, we identified RA patients prescribed ≥1 b/tsDMARD between 2001 and 2017. Consistent with the EULAR "difficult to treat" (D2T) RA definition, we further identified patients who discontinued ≥2 b/tsDMARDs with different mechanisms of action. We performed manual chart review to determine reasons for medication discontinuation. We defined "treatment refractory" RA as not achieving low disease activity (<3 tender or swollen joints on <7.5 mg of daily prednisone equivalent) despite treatment with two different b/tsDMARD mechanisms of action. We compared demographic, lifestyle, and clinical factors between treatment refractory RA and b/tsDMARD initiators not meeting D2T criteria.

RESULTS

We identified 6040 RA patients prescribed ≥1 b/tsDMARD including 404 meeting D2T criteria. The most common reasons for medication discontinuation were inadequate response (43.3 %), loss of efficacy (25.8 %), and non-allergic adverse events (13.7 %). Of patients with D2T RA, 15 % had treatment refractory RA. Treatment refractory RA patients were younger at b/tsDMARD initiation (mean 47.2 vs. 55.2 years, p < 0.001), more commonly female (91.8% vs. 76.1 %, p = 0.006), and ever smokers (68.9% vs. 49.9 %, p = 0.005). No RA clinical factors differentiated treatment refractory RA patients from b/tsDMARD initiators.

CONCLUSIONS

In a large EHR-based RA cohort, the most common reasons for b/tsDMARD switching were inadequate response, loss of efficacy, and nonallergic adverse events (e.g. infections, leukopenia, psoriasis). Clinical RA factors were insufficient for differentiating b/tsDMARD responders from nonresponders.

Fibroblast: A Novel Target for Autoimmune and Inflammatory Skin Diseases Therapeutics

Fibroblasts are crucial components of the skin structure. They were traditionally believed to maintain the skin's structure by producing extracellular matrix and other elements. Recent research illuminated that fibroblasts can respond to external stimuli and exhibit diverse functions, such as the secretion of pro-inflammatory factors, adipogenesis, and antigen presentation, exhibiting remarkable heterogeneity and plasticity. This revelation positions fibroblasts as active contributors to the pathogenesis of skin diseases, challenging the traditional perspective that views fibroblasts solely as structural entities. Based on their diverse functions, fibroblasts can be categorized into six subtypes: pro-inflammatory fibroblasts, myofibroblasts, adipogenic fibroblasts, angiogenic fibroblasts, mesenchymal fibroblasts, and antigen-presenting fibroblasts. Cytokines, metabolism, and epigenetics regulate functional abnormalities in fibroblasts. The dynamic changes fibroblasts exhibit in different diseases and disease states warrant a comprehensive discussion. We focus on dermal fibroblasts' aberrant manifestations and pivotal roles in inflammatory and autoimmune skin diseases, including psoriasis, vitiligo, lupus erythematosus, scleroderma, and atopic dermatitis, and propose targeting aberrantly activated fibroblasts as a potential therapeutic strategy for inflammatory and autoimmune skin diseases.

Targeting pathogenic fibroblast-like synoviocyte subsets in rheumatoid arthritis

Fibroblast-like synoviocytes (FLSs) play a central role in RA pathogenesis and are the main cellular component in the inflamed synovium of patients with rheumatoid arthritis (RA). FLSs are emerging as promising new therapeutic targets in RA. However, fibroblasts perform many essential functions that are required for sustaining tissue homeostasis. Direct targeting of general fibroblast markers on FLSs is challenging because fibroblasts in other tissues might be altered and side effects such as reduced wound healing or fibrosis can occur. To date, no FLS-specific targeted therapies have been applied in the clinical management of RA. With the help of high-throughput technologies such as scRNA-seq in recent years, several specific pathogenic FLS subsets in RA have been identified. Understanding the characteristics of these pathogenic FLS clusters and the mechanisms that drive their differentiation can provide new insights into the development of novel FLS-targeting strategies for RA. Here, we discuss the pathogenic FLS subsets in RA that have been elucidated in recent years and potential strategies for targeting pathogenic FLSs.

Clinical implications of synovial tissue phenotypes in rheumatoid arthritis

Autoimmune forms of inflammatory arthritis, such as Rheumatoid Arthritis (RA), are clinically heterogeneous in presentation and disease course. Treatment-related outcomes vary despite patient exposure to similar treatment strategies. It is likely that variation seen in synovial pathogenesis influences outcomes and is heterogeneous outcomes influenced by patient factors, including environmental exposures, microbiota, behaviors, timely access to therapy, and synovial cell variation. Patients' unique complex factors manifest as specific synovial phenotypes characterized by clusters of synovial cell types and states. Precision medicine aims to use such clinical and biological data to identify the right treatment for the right patient at the right time, enabling patients to achieve sustained remission. Identifying synovial targets susceptible to a given treatment, enabling the choice of effective therapy for a given patient, will realize the goals of precision medicine. Over the last 7 years, improved acquisition and processing of synovial tissue obtained by ultra-sound guided biopsy has enabled researchers to define synovial pathotypes using histologic features and predominant cell types associated with clinical manifestations. Technical advances have enabled single-cell simultaneous sequencing of proteins and gene expression that, through increasingly sophisticated bioinformatics methods, have taken transcriptional and proteomic data to identify diverse and novel cell types and states that cluster in the RA synovium to further define patient subgroups. Synovial pathotypes and endotypes are now integrated into clinical studies and trials to explain clinical heterogeneity in disease course and treatment response. Rapidly evolving clinical-translational research has linked an expanded understanding of RA synovial pathogenesis with clinically meaningful subgroups and treatment outcomes and the clinical heterogeneity in RA.

Synovial and serum B cell signature of autoantibody-negative rheumatoid arthritis vs autoantibody-positive rheumatoid arthritis and psoriatic arthritis

OBJECTIVES

Autoantibody-negative RA differs from autoantibody-positive RA in several clinical aspects, possibly underpinned by pathogenetic differences. At present, the role of adaptive immune responses in autoantibody-negative RA remains unclear. Here, we investigated the synovial and serum immunophenotype indicative of B lymphocyte involvement across the spectrum of autoantibody-positive and -negative chronic arthritides.

METHODS

Ultrasound-guided synovial biopsies were retrieved from 131 patients: 43 autoantibody-positive RA, 35 autoantibody-negative RA, 25 polyarticular PsA and 28 oligoarticular PsA. Samples were analysed for the degree of histological inflammation, B lymphocyte infiltration and the distribution of different pathotypes (lympho-myeloid, myeloid, pauci-immune). Serum levels of the B cell chemoattractant CXCL13 were compared among groups.

RESULTS

Synovitis scores and CD68+ sublining macrophage infiltration were comparable irrespective of clinical diagnosis and disease subtype. In contrast, the degree of B lymphocyte infiltration and the frequency of lympho-myeloid synovitis in autoantibody-negative RA were lower than those of autoantibody-positive RA (mean [s.d.] 1.8 [1] vs 2.4 [0.6], P = 0.03, and 38.2% vs 62.9%, P = 0.07, respectively), and similar to polyarticular PsA. Oligoarticular PsA had the lowest B cell scores. Serum CXCL13 was associated with lympho-myeloid synovitis and followed a similar gradient, with the highest levels in autoantibody-positive RA, intermediate and comparable levels in autoantibody-negative RA and polyarticular PsA, and low levels in oligoarticular PsA.

CONCLUSIONS

The synovial and serum immunophenotype indicative of B lymphocyte involvement in autoantibody-negative RA differs from that of autoantibody-positive RA and more closely resembles that observed in polyarticular PsA. The pathobiological stratification of chronic inflammatory arthritides beyond clinical diagnosis may fuel personalized treatment strategies.

Serum and Tissue Biomarkers Associated With Composite of Relevant Endpoints for Sjögren Syndrome (CRESS) and Sjögren Tool for Assessing Response (STAR) to B Cell-Targeted Therapy in the Trial of Anti-B Cell Therapy in Patients With Primary Sjögren Syndrome (TRACTISS)

OBJECTIVE

This study aimed to identify peripheral and salivary gland (SG) biomarkers of response/resistance to B cell depletion based on the novel concise Composite of Relevant Endpoints for Sjögren Syndrome (cCRESS) and candidate Sjögren Tool for Assessing Response (STAR) composite endpoints.

METHODS

Longitudinal analysis of peripheral blood and SG biopsies was performed pre- and post-treatment from the Trial of Anti-B Cell Therapy in Patients With Primary Sjögren Syndrome (TRACTISS) combining flow cytometry immunophenotyping, serum cytokines, and SG bulk RNA sequencing.

RESULTS

Rituximab treatment prevented the worsening of SG inflammation observed in the placebo arm, by inhibiting the accumulation of class-switched memory B cells within the SG. Furthermore, rituximab significantly down-regulated genes involved in immune-cell recruitment, lymphoid organization alongside antigen presentation, and T cell co-stimulatory pathways. In the peripheral compartment, rituximab down-regulated immunoglobulins  and auto-antibodies together with pro-inflammatory cytokines and chemokines. Interestingly, patients classified as responders  according to STAR displayed significantly higher baseline levels of C-X-C motif chemokine ligand-13 (CXCL13), interleukin (IL)-22, IL-17A, IL-17F, and tumor necrosis factor-α (TNF-α), whereas a longitudinal analysis of serum T cell-related cytokines showed a selective reduction in both STAR and cCRESS responder patients. Conversely, cCRESS response was better associated with biomarkers of SG immunopathology, with cCRESS-responders showing a significant decrease in SG B cell infiltration and reduced expression of transcriptional gene modules related to T cell costimulation, complement activation, and Fcγ-receptor engagement. Finally, cCRESS and STAR response were associated with a significant improvement in SG exocrine function linked to transcriptional evidence of SG epithelial and metabolic restoration.

CONCLUSION

Rituximab modulates both peripheral and SG inflammation, preventing the deterioration of exocrine function with functional and metabolic restoration of the glandular epithelium. Response assessed by newly developed cCRESS and STAR criteria was associated with differential modulation of peripheral and SG biomarkers, emerging as novel tools for patient stratification.

Notch ligands are biomarkers of anti-TNF response in RA patients

Notch and its ligands play a critical role in rheumatoid arthritis (RA) pathogenesis. Hence, studies were conducted to delineate the functional significance of the Notch pathway in RA synovial tissue (ST) cells and the influence of RA therapies on their expression. Morphological studies reveal that JAG1, DLL4, and Notch1 are highly enriched in RA ST lining and sublining CD68+CD14+ MΦs. JAG1 and DLL4 transcription is jointly upregulated in RA MΦs reprogrammed by TLR4/5 ligation and TNF, whereas Syntenin-1 exposure expands JAG1, DLL4, and Notch1 expression levels in these cells. Single-cell RNA-seq data exhibit that JAG1 and Notch3 are overexpressed on all fibroblast-like synoviocyte (FLS) subpopulations, in parallel, JAG2, DLL1, and Notch1 expression levels are modest on RA FLS and are predominately potentiated by TLR4 ligation. Intriguingly, JAG1, DLL1/4, and Notch1/3 are presented on RA endothelial cells, and their expression is mutually reconfigured by TLR4/5 ligation in the endothelium. Synovial JAG1/JAG2/DLL1 or Notch1/3 transcriptomes were unchanged in patients who received disease-modifying anti-rheumatic drugs (DMARDs) or IL-6R Ab therapy regardless of disease activity score. Uniquely, RA MΦs and endothelial cells rewired by IL-6 displayed DLL4 transcriptional upregulation, and IL-6R antibody treatment disrupted RA ST DLL4 transcription in good responders compared to non-responders or moderate responders. Nevertheless, the JAG1/JAG2/DLL1/DLL4 transcriptome was diminished in anti-TNF good responders with myeloid pathotype and was unaltered in the fibroid pathotype except for DLL4. Taken together, our findings suggest that RA myeloid Notch ligands can serve as markers for anti-TNF responsiveness and trans-activate Notch receptors expressed on RA FLS and/or endothelial cells.

Smoking and osteoimmunology: Understanding the interplay between bone metabolism and immune homeostasis

Smoking continues to pose a global threat to morbidity and mortality in populations. The detrimental impact of smoking on health and disease includes bone destruction and immune disruption in various diseases. Osteoimmunology, which explores the communication between bone metabolism and immune homeostasis, aims to reveal the interaction between the osteoimmune systems in disease development. Smoking impairs the differentiation of mesenchymal stem cells and osteoblasts in bone formation while promoting osteoclast differentiation in bone resorption. Furthermore, smoking stimulates the Th17 response to increase inflammatory and osteoclastogenic cytokines that promote the receptor activator of NF-κB ligand (RANKL) signaling in osteoclasts, thus exacerbating bone destruction in periodontitis and rheumatoid arthritis. The pro-inflammatory role of smoking is also evident in delayed bone fracture healing and osteoarthritis development. The osteoimmunological therapies are promising in treating periodontitis and rheumatoid arthritis, but further research is still required to block the smoking-induced aggravation in these diseases.

Translational potential

This review summarizes the adverse effect of smoking on mesenchymal stem cells, osteoblasts, and osteoclasts and elucidates the smoking-induced exacerbation of periodontitis, rheumatoid arthritis, bone fracture healing, and osteoarthritis from an osteoimmune perspective. We also propose the therapeutic potential of osteoimmunological therapies for bone destruction aggravated by smoking.

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.

Difficult-to-Treat Psoriatic Arthritis: A Conceptual Approach

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Autoimmunity to stromal-derived autoantigens in rheumatoid ectopic germinal centers exacerbates arthritis and affects clinical response

Ectopic lymphoid structures (ELSs) in the rheumatoid synovial joints sustain autoreactivity against locally expressed autoantigens. We recently identified recombinant monoclonal antibodies (RA-rmAbs) derived from single, locally differentiated rheumatoid arthritis (RA) synovial B cells, which specifically recognize fibroblast-like synoviocytes (FLSs). Here, we aimed to identify the specificity of FLS-derived autoantigens fueling local autoimmunity and the functional role of anti-FLS antibodies in promoting chronic inflammation. A subset of anti-FLS RA-rmAbs reacting with a 60 kDa band from FLS extracts demonstrated specificity for HSP60 and partial cross-reactivity to other stromal autoantigens (i.e., calreticulin/vimentin) but not to citrullinated fibrinogen. Anti-FLS RA-rmAbs, but not anti-neutrophil extracellular traps rmAbs, exhibited pathogenic properties in a mouse model of collagen-induced arthritis. In patients, anti-HSP60 antibodies were preferentially detected in RA versus osteoarthritis (OA) synovial fluid. Synovial HSPD1 and CALR gene expression analyzed using bulk RNA-Seq and GeoMx-DSP closely correlated with the lympho-myeloid RA pathotype, and HSP60 protein expression was predominantly observed around ELS. Moreover, we observed a significant reduction in synovial HSP60 gene expression followed B cell depletion with rituximab that was strongly associated with the treatment response. Overall, we report that synovial stromal-derived autoantigens are targeted by pathogenic autoantibodies and are associated with specific RA pathotypes, with potential value for patient stratification and as predictors of the response to B cell-depleting therapies.

Clinical Phenotypes, Serological Biomarkers, and Synovial Features Defining Seropositive and Seronegative Rheumatoid Arthritis: A Literature Review

Rheumatoid arthritis (RA) is a chronic autoimmune disorder which can lead to long-term joint damage and significantly reduced quality of life if not promptly diagnosed and adequately treated. Despite significant advances in treatment, about 40% of patients with RA do not respond to individual pharmacological agents and up to 20% do not respond to any of the available medications. To address this large unmet clinical need, several recent studies have focussed on an in-depth histological and molecular characterisation of the synovial tissue to drive the application of precision medicine to RA. Currently, RA patients are clinically divided into "seropositive" or "seronegative" RA, depending on the presence of routinely checked antibodies. Recent work has suggested that over the last two decades, long-term outcomes have improved significantly in seropositive RA but not in seronegative RA. Here, we present up-to-date differences in epidemiology, clinical features, and serological biomarkers in seronegative versus seropositive RA and discuss how histological and molecular synovial signatures, revealed by recent large synovial biopsy-based clinical trials, may be exploited to refine the classification of RA patients, especially in the seronegative group.

Impact of age and cardiovascular risk factors on the incidence of adverse events in patients with rheumatoid arthritis treated with Janus Kinase inhibitors: data from a real-life multicentric cohort

Inhibiting Janus Kinases (JAK) is a crucial therapeutic strategy in rheumatoid arthritis (RA). However, the use of JAK inhibitors has recently raised serious safety concerns. The study aims to evaluate the safety profile of JAKi in patients with RA and identify potential risk factors (RFs) for adverse events (AEs). Data of RA patients treated with JAKi in three Italian centers from January 2017 to December 2022 were retrospectively analyzed. 182 subjects (F:117, 64.3%) underwent 193 treatment courses. 78.6% had at least one RF, including age ≥ 65 years, obesity, smoking habit, hypertension, dyslipidemia, hyperuricemia, diabetes, previous VTE or cancer, and severe mobility impairment. We identified 70 AEs (28/100 patients/year), among which 15 were serious (6/100 patients/year). A high disease activity was associated with AEs occurrence (p = 0.03 for CDAI at T0 and T6; p = 0.04 for SDAI at T0 and T6; p = 0.01 and p = 0.04 for DAS28ESR at T6 and T12, respectively). No significant differences in AEs occurrence were observed after stratification by JAKi molecules (p = 0.44), age groups (p = 0.08) nor presence of RFs (p > 0.05 for all of them). Neither the presence of any RFs, nor the cumulative number of RFs shown by the patient, nor age ≥ 65 did predict AEs occurrence. Although limited by the small sample size and the limited number of cardiovascular events, our data do not support the correlation between cardiovascular RFs-including age-and a higher incidence of AEs during JAKi therapy. The role of uncontrolled disease activity in AEs occurrence should by emphasized.

Axl and MerTK regulate synovial inflammation and are modulated by IL-6 inhibition in rheumatoid arthritis

The TAM tyrosine kinases, Axl and MerTK, play an important role in rheumatoid arthritis (RA). Here, using a unique synovial tissue bioresource of patients with RA matched for disease stage and treatment exposure, we assessed how Axl and MerTK relate to synovial histopathology and disease activity, and their topographical expression and longitudinal modulation by targeted treatments. We show that in treatment-naive patients, high AXL levels are associated with pauci-immune histology and low disease activity and inversely correlate with the expression levels of pro-inflammatory genes. We define the location of Axl/MerTK in rheumatoid synovium using immunohistochemistry/fluorescence and digital spatial profiling and show that Axl is preferentially expressed in the lining layer. Moreover, its ectodomain, released in the synovial fluid, is associated with synovial histopathology. We also show that Toll-like-receptor 4-stimulated synovial fibroblasts from patients with RA modulate MerTK shedding by macrophages. Lastly, Axl/MerTK synovial expression is influenced by disease stage and therapeutic intervention, notably by IL-6 inhibition. These findings suggest that Axl/MerTK are a dynamic axis modulated by synovial cellular features, disease stage and treatment.

Unmet need in rheumatology: reports from the Advances in Targeted Therapies meeting, 2023

The Advances in Targeted Therapies meets annually, convening experts in the field of rheumatology to both provide scientific updates and identify existing scientific gaps within the field. To review the major unmet scientific needs in rheumatology. The 23rd annual Advances in Targeted Therapies meeting convened with more than 100 international basic scientists and clinical researchers in rheumatology, immunology, infectious diseases, epidemiology, molecular biology and other specialties relating to all aspects of immune-mediated inflammatory diseases. We held breakout sessions in five rheumatological disease-specific groups including: rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondyloarthritis (axSpa), systemic lupus erythematosus (SLE), systemic sclerosis (SSc) and vasculitis, and osteoarthritis (OA). In each group, experts were asked to identify and prioritise current unmet needs in clinical and translational research. An overarching theme across all disease states is the continued need for clinical trial design innovation with regard to therapeutics, endpoint and disease endotypes. Within RA, unmet needs comprise molecular classification of disease pathogenesis and activity, pre-/early RA strategies, more refined pain profiling and innovative trials designs to deliver on precision medicine. Continued scientific questions within PsA include evaluating the genetic, immunophenotypic, clinical signatures that predict development of PsA in patients with psoriasis, and the evaluation of combination therapies for difficult-to-treat disease. For axSpA, there continues to be the need to understand the role of interleukin-23 (IL-23) in pathogenesis and the genetic relationship of the IL-23-receptor polymorphism with other related systemic inflammatory diseases (eg, inflammatory bowel disease). A major unmet need in the OA field remains the need to develop the ability to reliably phenotype and stratify patients for inclusion in clinical trials. SLE experts identified a number of unmet needs within clinical trial design including the need for allowing endpoints that reflect pharmacodynamic/functional outcomes (eg, inhibition of type I interferon pathway activation; changes in urine biomarkers). Lastly, within SSc and vasculitis, there is a lack of biomarkers that predict response or disease progression, and that allow patients to be stratified for therapies. There remains a strong need to innovate clinical trial design, to identify systemic and tissue-level biomarkers that predict progression or response to therapy, endotype disease, and to continue developing therapies and therapeutic strategies for those with treatment-refractory disease. This document, based on expert consensus, should provide a roadmap for prioritising scientific endeavour in the field of rheumatology.

Macrophage: Hidden Criminal in Therapy Resistance

BACKGROUND

Although substantial efforts have been made by researchers to develop drugs, a disappointing reality is that the emergence of drug resistance is an unavoidable reality for the majority of patients. In recent years, emerging evidence suggests a connection between drug resistance and immune dysregulation.

SUMMARY

As a ubiquitously distributed, versatile innate immune cell, macrophages play essential roles in maintaining tissue homeostasis in a steady state. Nevertheless, it is becoming aware that macrophages undermine the action of therapeutic drugs across various disease types. Reprogramming macrophage function has been proven to be effective in restoring patient responsiveness to treatment. Herein, we comprehensively reviewed how macrophages respond to drugs and the mechanisms by which they contribute to treatment unresponsiveness in cancer, inflammatory diseases, and metabolic diseases. In addition, future prospects in macrophage-based combination therapy were discussed.

KEY MESSAGES

Targeting macrophages is a promising strategy for overcoming drug resistance in immune disorders.

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.

Pathophysiology and stratification of treatment-resistant rheumatoid arthritis

Early diagnosis and timely therapeutic intervention are clinical challenges of rheumatoid arthritis (RA), especially for treatment-resistant or difficult-to-treat patients. Little is known about the immunological mechanisms involved in refractory RA. In this review, we summarize previous research findings on the immunological mechanisms of treatment-resistant RA. Genetic prediction of treatment-resistant RA is challenging. Patients with and without anti-cyclic citrullinated peptide autoantibodies are considered part of distinct subgroups, especially regarding long-term clinical prognosis and treatment responses. B cells, T cells and other immune cells and fibroblasts are of pathophysiological importance and are associated with treatment responses. Finally, we propose a new hypothesis that stratifies patients with RA into two subgroups with distinct immunological pathologies based on our recent immunomics analysis of RA. One RA subgroup with a favorable prognosis is characterized by increased interferon signaling. Another subgroup with a worse prognosis is characterized by enhanced acquired immune responses. Increases in dendritic cell precursors and diversified autoreactive anti-modified protein antibodies may have pathophysiological roles, especially in the latter subgroup. These findings that improve treatment response predictions might contribute to future precision medicine for RA.

Advancing Rheumatology Care Through Machine Learning

Rheumatologic diseases are marked by their complexity, involving immune-, metabolic- and mechanically mediated processes which can affect different organ systems. Despite a growing arsenal of targeted medications, many rheumatology patients fail to achieve full remission. Assessing disease activity remains challenging, as patients prioritize different symptoms and disease phenotypes vary. This is also reflected in clinical trials where the efficacy of drugs is not necessarily measured in an optimal way with the traditional outcome assessment. The recent COVID-19 pandemic has catalyzed a digital transformation in healthcare, embracing telemonitoring and patient-reported data via apps and wearables. As a further driver of digital medicine, electronic medical record (EMR) providers are actively engaged in developing algorithms for clinical decision support, heralding a shift towards patient-centered, decentralized care. Machine learning algorithms have emerged as valuable tools for handling the increasing volume of patient data, promising to enhance treatment quality and patient well-being. Convolutional neural networks (CNN) are particularly promising for radiological image analysis, aiding in the detection of specific lesions such as erosions, sacroiliitis, or osteoarthritis, with several FDA-approved applications. Clinical predictions, including numerical disease activity forecasts and medication choices, offer the potential to optimize treatment strategies. Numeric predictions can be integrated into clinical workflows, allowing for shared decision making with patients. Clustering patients based on disease characteristics provides a personalized care approach. Digital biomarkers, such as patient-reported outcomes and wearables data, offer insights into disease progression and therapy response more flexibly and outside patient consultations. In association with patient-reported outcomes, disease-specific digital biomarkers via image recognition or single-camera motion capture enables more efficient remote patient monitoring. Digital biomarkers may also play a major role in clinical trials in the future as continuous, disease-specific outcome measurement facilitating decentralized studies. Prediction models can help with patient selection in clinical trials, such as by predicting high disease activity. Efforts are underway to integrate these advancements into clinical workflows using digital pathways and remote patient monitoring platforms. In summary, machine learning, digital biomarkers, and advanced imaging technologies hold immense promise for enhancing clinical decision support and clinical trials in rheumatology. Effective integration will require a multidisciplinary approach and continued validation through prospective studies.

Rheumatoid arthritis: pathogenesis and therapeutic advances

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the unresolved synovial inflammation for tissues-destructive consequence, which remains one of significant causes of disability and labor loss, affecting about 0.2-1% global population. Although treatments with disease-modifying antirheumatic drugs (DMARDs) are effective to control inflammation and decrease bone destruction, the overall remission rates of RA still stay at a low level. Therefore, uncovering the pathogenesis of RA and expediting clinical transformation are imminently in need. Here, we summarize the immunological basis, inflammatory pathways, genetic and epigenetic alterations, and metabolic disorders in RA, with highlights on the abnormality of immune cells atlas, epigenetics, and immunometabolism. Besides an overview of first-line medications including conventional DMARDs, biologics, and small molecule agents, we discuss in depth promising targeted therapies under clinical or preclinical trials, especially epigenetic and metabolic regulators. Additionally, prospects on precision medicine based on synovial biopsy or RNA-sequencing and cell therapies of mesenchymal stem cells or chimeric antigen receptor T-cell are also looked forward. The advancements of pathogenesis and innovations of therapies in RA accelerates the progress of RA treatments.

A single cell atlas of frozen shoulder capsule identifies features associated with inflammatory fibrosis resolution

Frozen shoulder is a spontaneously self-resolving chronic inflammatory fibrotic human disease, which distinguishes the condition from most fibrotic diseases that are progressive and irreversible. Using single-cell analysis, we identify pro-inflammatory MERTKlowCD48+ macrophages and MERTK + LYVE1 + MRC1+ macrophages enriched for negative regulators of inflammation which co-exist in frozen shoulder capsule tissues. Micro-cultures of patient-derived cells identify integrin-mediated cell-matrix interactions between MERTK+ macrophages and pro-resolving DKK3+ and POSTN+ fibroblasts, suggesting that matrix remodelling plays a role in frozen shoulder resolution. Cross-tissue analysis reveals a shared gene expression cassette between shoulder capsule MERTK+ macrophages and a respective population enriched in synovial tissues of rheumatoid arthritis patients in disease remission, supporting the concept that MERTK+ macrophages mediate resolution of inflammation and fibrosis. Single-cell transcriptomic profiling and spatial analysis of human foetal shoulder tissues identify MERTK + LYVE1 + MRC1+ macrophages and DKK3+ and POSTN+ fibroblast populations analogous to those in frozen shoulder, suggesting that the template to resolve fibrosis is established during shoulder development. Crosstalk between MerTK+ macrophages and pro-resolving DKK3+ and POSTN+ fibroblasts could facilitate resolution of frozen shoulder, providing a basis for potential therapeutic resolution of persistent fibrotic diseases.

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.