Synovial Inflammatory Pathways Characterize Anti-TNF-Responsive Rheumatoid Arthritis Patients

Discovery and validation of anti-arthritic ingredients and mechanisms of Qingfu Juanbi Tang, a Chinese herbal formulation, on rheumatoid arthritis

ETHNOPHARMACOLOGICAL RELEVANCE

Qingfu Juanbi Tang (QFJBT), a novel and improved Chinese herbal formulation, has surged in recent years for its potential in the therapy of rheumatoid arthritis (RA). Anti-arthritic effects and underlying molecular mechanisms of QFJBT have increasingly become a focal point in research.

AIM OF THE STUDY

This study utilized network pharmacology, molecular docking, and experimental validation to elucidate effective ingredients and anti-arthritic mechanisms of QFJBT.

MATERIALS AND METHODS

Targets associated with QFJBT and RA were identified from relevant databases and standardized using the Uniprot for gene nomenclature. A "QFJBT-ingredient-target network" and a "Venn diagram of QFJBT and RA targets" were created from the data. The overlap in the Venn diagram highlighted potential targets of QFJBT in the treatment of RA. These targets were subjected to PPI network, GO, and KEGG pathway analysis. The findings were subsequently confirmed through molecular docking and pharmacological experiments to propose the mechanism of action of QFJBT.

RESULTS

The study identified 236 active ingredients in QFJBT, with 120 predicted to be effective against RA. Molecular docking showed high binding affinity of key targets (JUN, PTGS2, and TNF-α) with bioactive compounds (rhein, sinomenine, calycosin, and paeoniflorin) of QFJBT. Pharmacodynamic evaluation demonstrated the effects of QFJBT at the dose of 4.56 g/kg in ameliorating symptoms of AIA rats and in reducing levels of JUN, PTGS2, and TNF-α in synovial tissues. In vitro studies further exhibited that rhein, paeoniflorin, sinomenine, calycosin, and QFJBT-containing serum significantly inhibited abnormal proliferation of RA fibroblast-like synoviocytes. Interestingly, rhein and paeoniflorin specifically decreased p-JUN/JUN expression and TNF-α release, respectively, while sinomenine and calycosin selectively increased PTGS2 expression. Consistently, QFJBT-containing serum demonstrated similar effects as those active ingredients identified in QFJBT did.

CONCLUSIONS

QFJBT, QFJBT-containing serum, and its active ingredients (rhein, paeoniflorin, sinomenine, and calycosin) suppress inflammatory responses in RA. Anti-arthritic effects of QFJBT and its active ingredients are likely linked to their modulatory impact on identified hub targets.

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.

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.

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.

Celastrol-loaded bovine serum albumin nanoparticles target inflamed neutrophils for improved rheumatoid arthritis therapy

Inflammatory neutrophils (INEs), motivated by cytokines, continue to migrate into the inflamed joints, driving the development of RA. Hence, inducing apoptosis of INEs to reduce recruitment at inflamed joints is an effective strategy for the treatment of RA. However, simply apoptotic INEs may trigger the release of neutrophil extracellular traps (NETs) and accelerate the inflammatory process. To overcome these drawbacks, an RGD-modified bovine serum albumin (BSA) nanoparticles (CBR NPs) was fabricated to selectively target INEs in situ for intracellular delivery of CLT. Studies have demonstrated that CBR NPs can selectively target circulating INEs and induce INEs apoptosis. Meanwhile, CBR NPs inhibited the activation of NETs via NF-κB pathway and the release of Cit-H3 thereby blocking the release process of NETs. In collagen-induced arthritis (CIA) mouse model, CBR NPs suppressed the inflammatory response, and reduced the toxic effects of CLT. In summary, this study shed light on an innovative approach to treat RA by inducing apoptosis of circulating INEs and inhibiting NETs. STATEMENT OF SIGNIFICANCE: RGD-modified bovine serum albumin (BSA) nanoparticles for delivering celastrol, abbreviated as CBR NPs, were constructed to inhibit the infiltration of circulating inflammatory neutrophils (INEs) into inflamed joints while inhibiting the release of NETs to alleviate tissue damage. CBR NPs were prepared for the first time to induce apoptosis of INEs; CBR NPs could inhibit the release of NETs while inducing apoptosis of INEs in vivo and vitro cellular experiments; CBR NPs had favorable anti-inflammatory effects and low toxicity side-effects in collagen-induced arthritis (CIA) mouse models. The application of nanotechnology to induce apoptosis of INEs while inhibiting the release of NETs was a promising approach for the treatment of RA.

High-grade synovitis associates with clinical markers and response to therapy in chronic inflammatory arthritis: post hoc analysis of a synovial biomarkers prospective cohort study

Background

Inflammatory arthritis (IAs), such as rheumatoid arthritis (RA) and psoriatic arthritis (PsA), are characterized by the presence of chronic synovitis. The Krenn's synovitis score (KSS), a simple tool detectable by haematoxylin/eosin staining of synovial biopsy samples, allows the discrimination between high-grade and low-grade synovitis. The aim of this study was to identify the clinical associations of KSS and to evaluate the relationship between high-grade synovitis and treatment response in IA patients.

Methods

Clinical, laboratory and ultrasound data were retrieved from RA and PsA patients recruited in the prospective MATRIX cohort study. Inclusion criteria were age≥18 years, RA or PsA diagnosis, and presence of active disease with eligibility to start/modify therapy. Patients underwent ultrasound-guided synovial biopsy of one of the most involved joints before starting/modifying treatment according to treat-to-target strategy. The samples were analysed by an expert pathologist for KSS calculation. Univariable and multivariable logistic regression analyses were performed to evaluate the relationship between KSS and baseline variables. The association between KSS and treatment response at 24 weeks of follow-up was investigated in univariable logistic regression analysis.

Results

53 patients, 34 RA and 19 PsA, completed 24 weeks of follow-up after synovial biopsy. Patients were either treatment naïve (N=6, 11%), csDMARDs-experienced (N=46, 87%) or b/tsDMARDs-experienced (N=20, 38%). Median KSS was 6.00 (Q1-Q3 4.00-7.00) in RA and 4.00 (3.00-6.00) in PsA (p=0.040), and inflammatory infiltrates score was significantly higher in RA than in PsA patients (median 3.00 vs 2.00, p=0.021). In multivariable analysis, synovial effusion in the biopsied joint (OR 9.26, 95%CI 2.12-53.91) and erythrocyte sedimentation rate (ESR) (OR 1.04, 95%CI 1.01-1.08) associated with high KSS. High-grade synovitis significantly associated with a higher probability of achieving DAS28 remission, ACR20/50 response, and Boolean2.0 remission, independently from diagnosis.

Conclusion

Several markers of pro-inflammatory pathways associated with the presence of high-grade synovitis, and patients with higher KSS shared a higher probability of treatment targets achievement in the follow up. The integration of a simple and feasible tool like KSS in the clinical and prognostic stratification of patients with IA might help in intercepting patients with a disease more prone to respond to available treatment paradigms.

Metabolic reprogramming by Syntenin-1 directs RA FLS and endothelial cell-mediated inflammation and angiogenesis

A novel rheumatoid arthritis (RA) synovial fluid protein, Syntenin-1, and its receptor, Syndecan-1 (SDC-1), are colocalized on RA synovial tissue endothelial cells and fibroblast-like synoviocytes (FLS). Syntenin-1 exacerbates the inflammatory landscape of endothelial cells and RA FLS by upregulating transcription of IRF1/5/7/9, IL-1β, IL-6, and CCL2 through SDC-1 ligation and HIF1α, or mTOR activation. Mechanistically, Syntenin-1 orchestrates RA FLS and endothelial cell invasion via SDC-1 and/or mTOR signaling. In Syntenin-1 reprogrammed endothelial cells, the dynamic expression of metabolic intermediates coincides with escalated glycolysis along with unchanged oxidative factors, AMPK, PGC-1α, citrate, and inactive oxidative phosphorylation. Conversely, RA FLS rewired by Syntenin-1 displayed a modest glycolytic-ATP accompanied by a robust mitochondrial-ATP capacity. The enriched mitochondrial-ATP detected in Syntenin-1 reprogrammed RA FLS was coupled with mitochondrial fusion and fission recapitulated by escalated Mitofusin-2 and DRP1 expression. We found that VEGFR1/2 and Notch1 networks are responsible for the crosstalk between Syntenin-1 rewired endothelial cells and RA FLS, which are also represented in RA explants. Similar to RA explants, morphological and transcriptome studies authenticated the importance of VEGFR1/2, Notch1, RAPTOR, and HIF1α pathways in Syntenin-1 arthritic mice and their obstruction in SDC-1 deficient animals. Consistently, dysregulation of SDC-1, mTOR, and HIF1α negated Syntenin-1 inflammatory phenotype in RA explants, while inhibition of HIF1α impaired synovial angiogenic imprint amplified by Syntenin-1. In conclusion, since the current therapies are ineffective on Syntenin-1 and SDC-1 expression in RA synovial tissue and blood, targeting this pathway and its interconnected metabolic intermediates may provide a novel therapeutic strategy.

The benefits and pitfalls of machine learning for biomarker discovery

Prospects for the discovery of robust and reproducible biomarkers have improved considerably with the development of sensitive omics platforms that can enable measurement of biological molecules at an unprecedented scale. With technical barriers to success lowering, the challenge is now moving into the analytical domain. Genome-wide discovery presents a problem of scale and multiple testing as standard statistical methods struggle to distinguish signal from noise in increasingly complex biological systems. Machine learning and AI methods are good at finding answers in large datasets, but they have a tendency to overfit solutions. It may be possible to find a local answer or mechanism in a specific patient sample or small group of samples, but this may not generalise to wider patient populations due to the high likelihood of false discovery. The rise of explainable AI offers to improve the opportunity for true discovery by providing explanations for predictions that can be explored mechanistically before proceeding to costly and time-consuming validation studies. This review aims to introduce some of the basic concepts of machine learning and AI for biomarker discovery with a focus on post hoc explanation of predictions. To illustrate this, we consider how explainable AI has already been used successfully, and we explore a case study that applies AI to biomarker discovery in rheumatoid arthritis, demonstrating the accessibility of tools for AI and machine learning. We use this to illustrate and discuss some of the potential challenges and solutions that may enable AI to critically interrogate disease and response mechanisms.

Ferroptosis-Related Molecular Clusters and Diagnostic Model in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by synovitis, joint damage and deformity. A newly described type of cell death, ferroptosis, has an important role in the pathogenesis of RA. However, the heterogeneity of ferroptosis and its association with the immune microenvironment in RA remain unknown. Synovial tissue samples from 154 RA patients and 32 healthy controls (HCs) were obtained from the Gene Expression Omnibus database. Twelve of twenty-six ferroptosis-related genes (FRGs) were differentially expressed between RA patients and HCs. Furthermore, the patterns of correlation among the FRGs were significantly different between the RA and HC groups. RA patients were classified into two distinct ferroptosis-related clusters, of which cluster 1 had a higher abundance of activated immune cells and a corresponding lower ferroptosis score. Enrichment analysis suggested that tumor necrosis factor-α signaling via nuclear factor-κB was upregulated in cluster 1. RA patients in cluster 1 responded better to anti-tumor necrosis factor (anti-TNF) therapy, which was verified by the GSE 198520 dataset. A diagnostic model to identify RA subtypes and immunity was constructed and verified, in which the area under the curve values in the training (70%) and validation (30%) cohorts were 0.849 and 0.810, respectively. This study demonstrated that there were two ferroptosis clusters in RA synovium that exhibited distinct immune profiles and ferroptosis sensitivity. Additionally, a gene scoring system was constructed to classify individual RA patients.

Evaluation of the Synovial Effects of Biological and Targeted Synthetic DMARDs in Patients with Psoriatic Arthritis: A Systematic Literature Review and Meta-Analysis

The aims of this systematic literature review (SLR) were to identify the effects of approved biological and targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) on synovial membrane of psoriatic arthritis (PsA) patients, and to determine the existence of histological/molecular biomarkers of response to therapy. A search was conducted on MEDLINE, Embase, Scopus, and Cochrane Library (PROSPERO:CRD42022304986) to retrieve data on longitudinal change of biomarkers in paired synovial biopsies and in vitro studies. A meta-analysis was conducted by adopting the standardized mean difference (SMD) as a measure of the effect. Twenty-two studies were included (19 longitudinal, 3 in vitro). In longitudinal studies, TNF inhibitors were the most used drugs, while, for in vitro studies, JAK inhibitors or adalimumab/secukinumab were assessed. The main technique used was immunohistochemistry (longitudinal studies). The meta-analysis showed a significant reduction in both CD3+ lymphocytes (SMD -0.85 [95% CI -1.23; -0.47]) and CD68+ macrophages (sublining, sl) (SMD -0.74 [-1.16; -0.32]) in synovial biopsies from patients treated for 4-12 weeks with bDMARDs. Reduction in CD3+ mostly correlated with clinical response. Despite heterogeneity among the biomarkers evaluated, the reduction in CD3+/CD68+sl cells during the first 3 months of treatment with TNF inhibitors represents the most consistent variation reported in the literature.

Follicular dendritic cell differentiation is associated with distinct synovial pathotype signatures in rheumatoid arthritis

Follicular dendritic cells (FDCs) fundamentally contribute to the formation of synovial ectopic lymphoid-like structures in rheumatoid arthritis (RA) which is associated with poor clinical prognosis. Despite this critical role, regulation of FDC development in the RA synovium and its correlation with synovial pathotype differentiation remained largely unknown. Here, we demonstrate that CNA.42⁺ FDCs distinctively express the pericyte/fibroblast-associated markers PDGFR-β, NG2, and Thy-1 in the synovial perivascular space but not in established follicles. In addition, synovial RNA-Seq analysis revealed that expression of the perivascular FDC markers was strongly correlated with PDGF-BB and fibroid synovitis, whereas TNF-α/LT-β was significantly associated with lymphoid synovitis and expression of CR1, CR2, and FcγRIIB characteristic of mature FDCs in lymphoid follicles. Moreover, PDGF-BB induced CNA.42⁺ FDC differentiation and CXCL13 secretion from NG2⁺ synovial pericytes, and together with TNF-α/LT-β conversely regulated early and late FDC differentiation genes in unsorted RA synovial fibroblasts (RASF) and this was confirmed in flow sorted stromal cell subsets. Furthermore, RASF TNF-αR expression was upregulated by TNF-α/LT-β and PDGF-BB; and TNF-α/LT-β-activated RASF retained ICs and induced B cell activation in in vitro germinal center reactions typical of FDCs. Additionally, FDCs trapped peptidyl citrulline, and strongly correlated with IL-6 expression, and plasma cell, B cell, and T cell infiltration of the RA synovium. Moreover, synovial FDCs were significantly associated with RA disease activity and radiographic features of tissue damage. To the best of our knowledge, this is the first report describing the reciprocal interaction between PDGF-BB and TNF-α/LT-β in synovial FDC development and evolution of RA histological pathotypes. Selective targeting of this interplay could inhibit FDC differentiation and potentially ameliorate RA in clinically severe and drug-resistant patients.