The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis

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

OBJECTIVE

We sought to develop computer vision methods to quantify aggregates of cells in synovial tissue and compare these with clinical and gene expression parameters.

METHODS

We assembled a computer vision pipeline to quantify five features encompassing synovial cell density and aggregates and compared these with pathologist scores, disease classification, autoantibody status, and RNA expression in a cohort of 156 patients with rheumatoid arthritis (RA) and 149 patients with osteoarthritis (OA).

RESULTS

All five features were associated with pathologist scores of synovial lymphocytic inflammation (P < 0.0001). Three features that related to the cells per unit of tissue were significantly increased in patients with both seronegative and seropositive RA compared with those with OA; on the other hand, aggregate features (number and diameter) were significantly increased in seropositive, but not seronegative, RA compared with OA. Aggregate diameter was associated with the gene expression of immunoglobulin heavy-chain genes in the synovial tissue. Compared with blood, synovial immunoglobulin isotypes were skewed from IGHM and IGHD to IGHG3 and IGHG1. Further, patients with RA with high levels of lymphocytic infiltrates in the synovium demonstrated parallel skewing in their blood with a relative decrease in IGHGM (P < 0.002) and IGHD (P < 0.03) and an increase in class-switched immunoglobulin genes IGHG3 (P < 0.03) and IGHG1 (P < 0.002).

CONCLUSION

High-resolution automated identification and quantification of synovial immune cell aggregates uncovered skewing in the synovium from naïve IGHD and IGHM to memory IGHG3 and IGHG1 and revealed that this process is reflected in the blood of patients with high inflammatory synovium.

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

OBJECTIVE

This study was undertaken to understand the mechanistic basis of response to anti-tumor necrosis factor (anti-TNF) therapies and to determine whether transcriptomic changes in the synovium are reflected in peripheral protein markers.

METHODS

Synovial tissue from 46 rheumatoid arthritis (RA) patients was profiled with RNA sequencing before and 12 weeks after treatment with anti-TNF therapies. Pathway and gene signature analyses were performed on RNA expression profiles of synovial biopsies to identify mechanisms that could discriminate among patients with a good response, a moderate response, or no response, according to the American College of Rheumatology (ACR)/EULAR response criteria. Serum proteins encoded by synovial genes that were differentially expressed between ACR/EULAR response groups were measured in the same patients.

RESULTS

Gene signatures predicted which patients would have good responses, and pathway analysis identified elevated immune pathways, including chemokine signaling, Th1/Th2 cell differentiation, and Toll-like receptor signaling, uniquely in good responders. These inflammatory pathways were correspondingly down-modulated by anti-TNF therapy only in good responders. Based on cell signature analysis, lymphocyte, myeloid, and fibroblast cell populations were elevated in good responders relative to nonresponders, consistent with the increased inflammatory pathways. Cell signatures that decreased following anti-TNF treatment were predominately associated with lymphocytes, and fewer were associated with myeloid and fibroblast populations. Following anti-TNF treatment, and only in good responders, several peripheral inflammatory proteins decreased in a manner that was consistent with corresponding synovial gene changes.

CONCLUSION

Collectively, these data suggest that RA patients with robust responses to anti-TNF therapies are characterized at baseline by immune pathway activation, which decreases following anti-TNF treatment. Understanding mechanisms that define patient responsiveness to anti-TNF treatment may assist in development of predictive markers of patient response and earlier treatment options.

Gene Ontology Analysis Highlights Biological Processes Influencing Non-Response to Anti-TNF Therapy in Rheumatoid Arthritis

Anti-TNF therapy has significantly improved disease control in rheumatoid arthritis, but a fraction of rheumatoid arthritis patients do not respond to anti-TNF therapy or lose response over time. Moreover, the mechanisms underlying non-response to anti-TNF therapy remain largely unknown. To date, many single biomarkers of response to anti-TNF therapy have been published but they have not yet been analyzed as a system of interacting nodes. The aim of our study is to systematically elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis using the gene ontologies of previously published predictive biomarkers. Gene networks were constructed based on published biomarkers and then enriched gene ontology terms were elucidated in subgroups using gene ontology software tools. Our results highlight the novel role of proteasome-mediated protein catabolic processes (p = 2.91 × 10⁻¹⁵) and plasma lipoproteins (p = 4.55 × 10⁻¹¹) in anti-TNF therapy response. The results of our gene ontology analysis help elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis and encourage further study of the highlighted processes.

Network analysis of synovial RNA sequencing identifies gene-gene interactions predictive of response in rheumatoid arthritis

BACKGROUND

To determine whether gene-gene interaction network analysis of RNA sequencing (RNA-Seq) of synovial biopsies in early rheumatoid arthritis (RA) can inform our understanding of RA pathogenesis and yield improved treatment response prediction models.

METHODS

We utilized four well curated pathway repositories obtaining 10,537 experimentally evaluated gene-gene interactions. We extracted specific gene-gene interaction networks in synovial RNA-Seq to characterize histologically defined pathotypes in early RA and leverage these synovial specific gene-gene networks to predict response to methotrexate-based disease-modifying anti-rheumatic drug (DMARD) therapy in the Pathobiology of Early Arthritis Cohort (PEAC). Differential interactions identified within each network were statistically evaluated through robust linear regression models. Ability to predict response to DMARD treatment was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

Analysis comparing different histological pathotypes showed a coherent molecular signature matching the histological changes and highlighting novel pathotype-specific gene interactions and mechanisms. Analysis of responders vs non-responders revealed higher expression of apoptosis regulating gene-gene interactions in patients with good response to conventional synthetic DMARD. Detailed analysis of interactions between pairs of network-linked genes identified the SOCS2/STAT2 ratio as predictive of treatment success, improving ROC area under curve (AUC) from 0.62 to 0.78. We identified a key role for angiogenesis, observing significant statistical interactions between NOS3 (eNOS) and both CAMK1 and eNOS activator AKT3 when comparing responders and non-responders. The ratio of CAMKD2/NOS3 enhanced a prediction model of response improving ROC AUC from 0.63 to 0.73.

CONCLUSIONS

We demonstrate a novel, powerful method which harnesses gene interaction networks for leveraging biologically relevant gene-gene interactions leading to improved models for predicting treatment response.

Therapeutic Benefit in Rheumatoid Cachexia Illustrated Using a Novel Primary Human Triple Cell Coculture Model

Background

The loss of muscle mass in rheumatoid arthritis (RA), termed rheumatoid cachexia, is predicted to result from the complex interactions between different cell types involved in the maintenance of skeletal muscle mass, namely, myoblasts, fibroblasts, and macrophages. The complexity within the muscle is further highlighted by the incidence of nonresponsiveness to current RA treatment strategies.

Method

This study aimed at determining differences in the cellular responses in a novel human primary cell triple coculture model exposed to serum collected from nonarthritic controls (NC), RA treatment naïve (RATN), and RA treatment-nonresponding (RATNR) patients. Bone morphogenetic protein-7 (BMP-7) was investigated as a treatment option.

Results

Plasma analysis indicated that samples were indeed representative of healthy and RA patients—notably, the RATNR patients additionally exhibited dysregulated IL-6/IL-10 correlations. Coculture exposure to serum from RATNR patients demonstrated increased cellular growth (p < 0.001), while both hepatocyte growth factor (p < 0.01) and follistatin (p < 0.001) were reduced when compared to NC. Furthermore, decreased concentration of markers of extracellular matrix formation, transforming growth factor-β (TGF-β; p < 0.05) and fibronectin (p < 0.001), but increased collagen IV (p < 0.01) was observed following RATNR serum exposure. Under healthy conditions, BMP-7 exhibited potentially beneficial results in reducing fibrosis-generating TGF-β (p < 0.05) and fibronectin (p < 0.05). BMP-7 further exhibited protective potential in the RA groups through reversing the aberrant tendencies observed especially in the RATNR serum-exposed group.

Conclusion

Exposure of the triple coculture to RATN and RATNR serum resulted in dysregulated myoblast proliferation and growth, and ECM impairment, which was reversed by BMP-7 treatment.

Insights Gained and Future Outlook From scRNAseq Studies in Autoimmune Rheumatic Diseases

Autoimmune rheumatic diseases have a major impact on public health as one of the most common morbidities, and many of these disorders involve both local and systemic manifestations with severe consequences for patient health and quality of life. However, treatment options for many of these diseases remain inadequate for a substantial portion of patients, and progress in developing novel therapeutics has been slow. This lack of progress can be largely attributed to an insufficient understanding of the complex mechanisms driving pathogenesis. Recently, the emergence of single-cell RNA sequencing (scRNAseq) has offered a powerful new tool for interrogating rheumatic diseases, with the potential to assess biological heterogeneity and individual cell function in rheumatic diseases. In this review, we discuss the major insights gained from current scRNAseq interrogations of human rheumatic diseases. We highlight novel cell populations and key molecular signatures uncovered, and also raise a number of hypotheses for follow-up study that may be of interest to the field. We also provide an outlook into two emerging single-cell technologies (repertoire sequencing and spatial transcriptomics) that have yet to be utilized in the field of rheumatic diseases, but which offer immense potential in expanding our understanding of immune and stromal cell behavior. We hope that scRNAseq may serve as a wellspring for the generation and interrogation of novel hypotheses regarding autoreactive lymphocytes and tissue infiltration patterns, and help uncover novel avenues for therapeutic development.

EULAR points to consider for minimal reporting requirements in synovial tissue research in rheumatology

BACKGROUND

Synovial tissue research has become widely developed in several rheumatology centres, however, large discrepancies exist in the way synovial tissue is handled and, more specifically, how data pertaining to biopsy procedure, quality check and experimental results are reported in the literature. This heterogeneity hampers the progress of research in this rapidly expanding field. In that context, under the umbrella of European Alliance of Associations for Rheumatology, we aimed at proposing points to consider (PtC) for minimal reporting requirements in synovial tissue research.

METHODS

Twenty-five members from 10 countries across Europe and USA met virtually to define the key areas needing evaluation and formulating the research questions to inform a systematic literature review (SLR). The results were presented during a second virtual meeting where PtC were formulated and agreed.

RESULTS

Study design, biopsy procedures, tissue handling, tissue quality control and tissue outcomes (imaging, DNA/RNA analysis and disaggregation) were identified as important aspects for the quality of synovial tissue research. The SLR interrogated four databases, retrieved 7654 abstracts and included 26 manuscripts. Three OPs and nine PtC were formulated covering the following areas: description of biopsy procedure, overarching clinical design, patient characteristics, tissue handling and processing, quality control, histopathology, transcriptomic analyses and single-cell technologies.

CONCLUSIONS

These PtC provide guidance on how research involving synovial tissue should be reported to ensure a better evaluation of results by readers, reviewers and the broader scientific community. We anticipate that these PtC will enable the field to progress in a robust and transparent manner over the coming years.

Cellular and molecular diversity in Rheumatoid Arthritis

Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease. RA mainly affects synovial joints, with inflammation of the synovial membrane (synovitis), characterised by neo-angiogenesis, hyperplasia of lining layer, and immune cell infiltration that drive local inflammation and, if untreated, can lead to joint destruction and disability. In parallel to the well-known clinical heterogeneity, the underlying synovitis can also be significantly heterogeneous, both at cellular and molecular level, which can at least in part explain why despite the availability of highly effective treatment options, a large proportion of patients are resistant to some individual treatments. The assimilation of recent high-throughput data from analysis at the single-cell level with rigorous and high-quality clinical outcomes obtained from large randomised clinical trials support the definition of disease and treatment response endotypes. Looking ahead, the integration of histological and molecular signatures from the diseased tissue into clinical algorithms may help decision making in the management of patients with Rheumatoid Arthritis in clinical practice.

Deep phenotyping of synovial molecular signatures by integrative systems analysis in rheumatoid arthritis

OBJECTIVE

RA encompasses a complex, heterogeneous and dynamic group of diseases arising from molecular and cellular perturbations of synovial tissues. The aim of this study was to decipher this complexity using an integrative systems approach and provide novel insights for designing stratified treatments.

METHODS

An RNA sequencing dataset of synovial tissues from 152 RA patients and 28 normal controls was imported and subjected to filtration of differentially expressed genes, functional enrichment and network analysis, non-negative matrix factorization, and key driver analysis. A naïve Bayes classifier was applied to the independent datasets to investigate the factors associated with treatment outcome.

RESULTS

A matrix of 1241 upregulated differentially expressed genes from RA samples was classified into three subtypes (C1-C3) with distinct molecular and cellular signatures. C3 with prominent immune cells and proinflammatory signatures had a stronger association with the presence of ACPA and showed a better therapeutic response than C1 and C2, which were enriched with neutrophil and fibroblast signatures, respectively. C2 was more occupied by synovial fibroblasts of destructive phenotype and carried highly expressed key effector molecules of invasion and osteoclastogenesis. CXCR2, JAK3, FYN and LYN were identified as key driver genes in C1 and C3. HDAC, JUN, NFKB1, TNF and TP53 were key regulators modulating fibroblast aggressiveness in C2.

CONCLUSIONS

Deep phenotyping of synovial heterogeneity captured comprehensive and discrete pathophysiological attributes of RA regarding clinical features and treatment response. This result could serve as a template for future studies to design stratified approaches for RA patients.

Translational Research Studies Unraveling the Origins of Psoriatic Arthritis: Moving Beyond Skin and Joints

Patients with psoriatic arthritis (PsA) are suffering from a decreased quality of life despite currently available treatments. In the latest years, novel therapies targeting the IL-17/IL-23 and TNF pathways improved clinical outcome. Despite this, remission of disease is not achieved in a considerable group of patients, continuous treatment is very often required to reach clinical remission, and prevention of PsA in patients with psoriasis (PsO) is currently impossible. A better understanding of PsA pathogenesis is required to develop novel treatment strategies that target inflammation and destruction more effectively and at an early stage of the disease, or even before clinically manifest disease. The skin is considered as one of the sites of onset of immune activation, triggering the inflammatory cascade in PsA. PsO develops into PsA in 30% of the PsO patients. Influenced by environmental and genetic factors, the inflammatory process in the skin, entheses, and/or gut may evolve into synovial tissue inflammation, characterized by influx of immune cells. The exact role of the innate and adaptive immune cells in disease pathogenesis is not completely known. The involvement of activated IL-17A+ T cells could implicate early immunomodulatory events generated in lymphoid organs thereby shaping the pathogenic inflammatory response leading to disease. In this perspective article, we provide the reader with an overview of the current literature regarding the immunological changes observed during the earliest stages of PsA. Moreover, we will postulate future areas of translational research aimed at increasing our knowledge on the molecular mechanisms driving disease development, which will aid the identification of novel potential therapeutic targets to limit the progression of PsA.

Will rheumatologists ever pick up the arthroscope again?

Conditions prompting physicians and surgeons first adapting endoscopes to peer into joints were mainly the sort of synovial conditions that would concern today's rheumatologists. Rheumatologists were among the pre-World War II pioneers developing and documenting arthroscopy. The post-War father of modern arthroscopy, Watanabe, found rheumatologists among his early students, who took back the technique to their home countries, teaching orthopedists and rheumatologists alike. Rheumatologists described and analyzed the intra-articular features of their common diseases in the '60s and '70s. A groundswell of interest from academic rheumatologists in adapting arthroscopy grew considerably in the '90s with development of "needle scopes" that could be used in an office setting. Rheumatologists helped conduct the very trials the findings of which reduced demand for their arthroscopic services by questioning the efficacy of arthroscopic debridement in osteoarthritis (OA) and also developing biological compounds that greatly reduced the call for any resective intervention in inflammatory arthropathies. The arthroscope has proven an excellent tool for viewing and sampling synovium and continues to serve this purpose at several international research centers. While cartilage is now imaged mainly by magnetic resonance imaging, some OA features - such as a high prevalence of visible calcinosis - beg further arthroscopy-directed investigation. A new generation of "needle scopes" with far superior optics awaits future investigators, should they develop interest.

Multiomics and Machine Learning Accurately Predict Clinical Response to Adalimumab and Etanercept Therapy in Patients With Rheumatoid Arthritis

OBJECTIVE

To predict response to anti-tumor necrosis factor (anti-TNF) prior to treatment in patients with rheumatoid arthritis (RA), and to comprehensively understand the mechanism of how different RA patients respond differently to anti-TNF treatment.

METHODS

Gene expression and/or DNA methylation profiling on peripheral blood mononuclear cells (PBMCs), monocytes, and CD4+ T cells obtained from 80 RA patients before they began either adalimumab (ADA) or etanercept (ETN) therapy was studied. After 6 months, treatment response was evaluated according to the European League Against Rheumatism criteria for disease response. Differential expression and methylation analyses were performed to identify the response-associated transcription and epigenetic signatures. Using these signatures, machine learning models were built by random forest algorithm to predict response prior to anti-TNF treatment, and were further validated by a follow-up study.

RESULTS

Transcription signatures in ADA and ETN responders were divergent in PBMCs, and this phenomenon was reproduced in monocytes and CD4+ T cells. The genes up-regulated in CD4+ T cells from ADA responders were enriched in the TNF signaling pathway, while very few pathways were differential in monocytes. Differentially methylated positions (DMPs) were strongly hypermethylated in responders to ETN but not to ADA. The machine learning models for the prediction of response to ADA and ETN using differential genes reached an overall accuracy of 85.9% and 79%, respectively. The models using DMPs reached an overall accuracy of 84.7% and 88% for ADA and ETN, respectively. A follow-up study validated the high performance of these models.

CONCLUSION

Our findings indicate that machine learning models based on molecular signatures accurately predict response before ADA and ETN treatment, paving the path toward personalized anti-TNF treatment.

Synovial biopsies in clinical practice and research: current developments and perspectives

Synovial biopsy techniques have developed and widely expanded over the past few years, in particular due to the development of ultrasound-guided procedures. This article reviews the different techniques, clinical applications, and the latest advances in translational research as well as current challenges and perspectives. The first part focuses on different techniques available for biopsy, along with their feasibility, success rate, tolerance, and training requirements. In the second part, clinical applications are described. Data on diagnostic performances are reported, especially regarding septic arthritis. Translational research applications are described and explained in the final part, from the early histological studies and the first description of pathotype to more recent technologies involving -omics. Latest developments involving single-cell RNA sequence analysis have allowed the discovery of new cell subpopulations with remarkable roles in RA pathophysiology. These studies pave the ground for the discovery of new therapeutic targets and the implementation of personalized therapy in RA.

Key Point •This review provides an overview of synovial biopsy techinques and applications especially in clinical and translational research.

Paired Rheumatoid Arthritis Synovial Biopsies From Small and Large Joints Show Similar Global Transcriptomic Patterns With Enrichment of Private Specificity TCRB and TCR Signaling Pathways

Objectives

We explored histological and transcriptomic profiles of paired synovial biopsies from rheumatoid arthritis (RA) patients, in order to assess homogeneity in synovial tissue at the individual level.

Methods

Synovial biopsies were performed simultaneously in one small and one large joint per patient using needle-arthroscopy for the knee and ultrasound-guided biopsy for the hand or wrist. Synovium from individuals with osteoarthritis was used as controls. Paraffin-embedded samples were stained for CD3, CD20, and CD68. Total RNA was hybridized on high-density microarrays. TCRB variable sequences were obtained from synovial and blood RNA samples.

Results

Twenty paired biopsies from 10 RA patients with active disease were analyzed. Semi-quantification of histological markers showed a positive correlation for synovial hyperplasia, inflammatory infiltrates and CD3-positive T cells between pairs. Pairwise comparison of transcriptomic profiles showed similar expression of RA-related molecular pathways (TCR signaling, T cell costimulation and response to TNFα). T cells clonotypes were enriched in all but one joints compared to blood, regardless of the magnitude of T cell infiltration. Enriched clonotypes were shared between pairs (23-100%), but this was less the case in pairs of joints displaying weaker T cell signatures and more pronounced germinal center-like transcriptomic profiles.

Conclusion

Cellular and molecular alterations in RA synovitis are similar between small and large joints from the same patient. Interindividual differences in magnitude of T cell infiltrates and distribution of enriched T cell clonotypes support the concept of distinct synovial pathotypes in RA that are associated with systemic versus local antigen-driven activation of T cells.

Disease-Specific Autoantibodies Induce Trained Immunity in RA Synovial Tissues and Its Gene Signature Correlates with the Response to Clinical Therapy

Much evidence suggests that trained immunity is inappropriately activated in the synovial tissue in rheumatoid arthritis (RA), but the underlying mechanism remains unclear. Here, we describe how RA-specific autoantibody deposits can train human monocytes to exert the hyperactive inflammatory response, particularly via the exacerbated release of tumor necrosis factor α (TNFα). Comparative transcriptomic analysis by plate-bound human IgG (cIgG) or β-glucan indicated that metabolic shift towards glycolysis is a crucial mechanism for trained immunity. Moreover, the cIgG-trained gene signatures were enriched in synovial tissues from patients with ACPA- (anticitrullinated protein antibody-) positive arthralgia and undifferentiated arthritis, and early RA and established RA bore a great resemblance to the myeloid pathotype, suggesting a historical priming event in vivo. Additionally, the expression of the cIgG-trained signatures is higher in the female, older, and ACPA-positive populations, with a predictive role in the clinical response to infliximab. We conclude that RA-specific autoantibodies can train monocytes in the inflamed lesion as early as the asymptomatic stage, which may not merely improve understanding of disease progression but may also suggest therapeutic and/or preventive strategies for autoimmune diseases.

Lower peripheral helper T cell levels in the synovium are associated with a better response to anti-TNF therapy in rheumatoid arthritis

Background

The mechanisms by which only some rheumatoid arthritis (RA) patients respond favorably to TNF blockade are still poorly characterized. The goal of this study was to identify biological features that explain this differential response using a multilevel transcriptome analysis of the synovial membrane.

Methods

Synovial samples from 11 patients on anti-TNF therapy were obtained by arthroscopy at baseline and week 20. Analysis of the synovial transcriptome was performed at the gene, pathway, and cell-type levels. Newly characterized pathogenic cell types in RA, peripheral helper T cells (T_PH), and CD34-THY1+ fibroblasts were estimated using a cell-type deconvolution approach. T_PH association was validated using immunofluorescence. External validation was performed on an independent dataset.

Results

After multiple-test correction, 16 and 4 genes were differentially expressed at baseline and week 20, respectively. At the pathway level, 86 and 17 biological processes were significantly enriched at baseline and week 20, respectively. Longitudinal expression changes were associated with a drastic decrease of innate immune activity (P < 5e−30), and an activation of the bone and cartilage regeneration processes (P < 5e−10). Cell-type deconvolution revealed a significant association between low T_PH cells at baseline and a better response (P = 0.026). Lower T_PH cells were maintained in good responders up to week 20 (P = 0.032). Immunofluorescent analyses confirmed the accuracy of the cell-type estimation (r² = 0.58, P = 0.005) and an association with response. T_PH association with anti-TNF response was validated in an independent sample of RA patients (P = 0.0040).

Conclusions

A lower abundance in the synovial membrane of the pathogenic T cell type newly associated with RA, peripheral helper T lymphocyte, is associated with a good response to anti-TNF therapy. Major changes in the myeloid cell compartment were also observed in response to therapy. The results of this study could help develop more effective therapies aimed at treating the pathogenic mechanisms in RA that are currently not well targeted by anti-TNF agents.

Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes

There is a current imperative to unravel the hierarchy of molecular pathways that drive the transition of early to established disease in rheumatoid arthritis (RA). Herein, we report a comprehensive RNA sequencing analysis of the molecular pathways that drive early RA progression in the disease tissue (synovium), comparing matched peripheral blood RNA-seq in a large cohort of early treatment-naive patients, namely, the Pathobiology of Early Arthritis Cohort (PEAC). We developed a data exploration website (https://peac.hpc.qmul.ac.uk/) to dissect gene signatures across synovial and blood compartments, integrated with deep phenotypic profiling. We identified transcriptional subgroups in synovium linked to three distinct pathotypes: fibroblastic pauci-immune pathotype, macrophage-rich diffuse-myeloid pathotype, and a lympho-myeloid pathotype characterized by infiltration of lymphocytes and myeloid cells. This is suggestive of divergent pathogenic pathways or activation disease states. Pro-myeloid inflammatory synovial gene signatures correlated with clinical response to initial drug therapy, whereas plasma cell genes identified a poor prognosis subgroup with progressive structural damage.

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Deep phenotyping and RNA-seq of early rheumatoid arthritis individuals pre-treatment

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Synovial plasma cell gene expression predicts future progressive joint damage on X-ray

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Blood interferon gene signature associates with synovial B and plasma cell infiltration

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Interactive website enables RNA-seq and clinical data to be fully explored

Gene Signatures of Early Response to Anti-TNF Drugs in Pediatric Inflammatory Bowel Disease

Around a 20–30% of inflammatory bowel disease (IBD) patients are diagnosed before they are 18 years old. Anti-TNF drugs can induce and maintain remission in IBD, however, up to 30% of patients do not respond. The aim of the work was to identify markers that would predict an early response to anti-TNF drugs in pediatric patients with IBD. The study population included 43 patients aged <18 years with IBD who started treatment with infliximab or adalimumab. Patients were classified into primary responders (n = 27) and non-responders to anti-TNF therapy (n = 6). Response to treatment could not be analyzed in 10 patients. Response was defined as a decrease in over 15 points in the disease activity indexes from week 0 to week 10 of infliximab treatment or from week 0 to week 26 of adalimumab treatment. The expression profiles of nine genes in total RNA isolated from the whole-blood of pediatric IBD patients taken before biologic administration and after 2 weeks were analyzed using qPCR and the 2^−∆∆Ct method. Before initiation and after 2 weeks of treatment the expression of SMAD7 was decreased in patients who were considered as non-responders (p value < 0.05). Changes in expression were also observed for TLR2 at T0 and T2, although that did not reach the level of statistical significance. In addition, the expression of DEFA5 decreased 1.75-fold during the first 2 weeks of anti-TNF treatment in responders, whereas no changes were observed in non-responders. Expression of the SMAD7 gene is a pharmacogenomic biomarker of early response to anti-TNF agents in pediatric IBD. TLR2 and DEFA5 need to be validated in larger studies.

A Pauci-Immune Synovial Pathotype Predicts Inadequate Response to TNFα-Blockade in Rheumatoid Arthritis Patients

Objectives: To assess whether the histopathological features of the synovium before starting treatment with the TNFi certolizumab-pegol could predict clinical outcome and examine the modulation of histopathology by treatment. Methods: Thirty-seven RA patients fulfilling UK NICE guidelines for biologic therapy were enrolled at Barts Health NHS trust and underwent synovial sampling of an actively inflamed joint using ultrasound-guided needle biopsy before commencing certolizumab-pegol and after 12-weeks. At 12-weeks, patients were categorized as responders if they had a DAS28 fall >1.2. A minimum of 6 samples was collected for histological analysis. Based on H&E and immunohistochemistry (IHC) staining for CD3 (T cells), CD20 (B cells), CD138 (plasma cells), and CD68 (macrophages) patients were categorized into three distinct synovial pathotypes (lympho-myeloid, diffuse-myeloid, and pauci-immune). Results: At baseline, as per inclusion criteria, DAS28 mean was 6.4 ± 0.9. 94.6% of the synovial tissue was retrieved from the wrist or a metacarpophalangeal joint. Histological pathotypes were distributed as follows: 58% lympho-myeloid, 19.4% diffuse-myeloid, and 22.6% pauci-immune. Patients with a pauci-immune pathotype had lower levels of CRP but higher VAS fatigue compared to lympho- and diffuse-myeloid. Based on DAS28 fall >1.2, 67.6% of patients were deemed as responders and 32.4% as non-responders. However, by categorizing patients according to the baseline synovial pathotype, we demonstrated that a significantly higher number of patients with a lympho-myeloid and diffuse-myeloid pathotype in comparison with pauci-immune pathotype [83.3% (15/18), 83.3 % (5/6) vs. 28.6% (2/7), p = 0.022) achieved clinical response to certolizumab-pegol. Furthermore, we observed a significantly higher level of post-treatment tender joint count and VAS scores for pain, fatigue and global health in pauci-immune in comparison with lympho- and diffuse-myeloid patients but no differences in the number of swollen joints, ESR and CRP. Finally, we confirmed a significant fall in the number of CD68+ sublining macrophages post-treatment in responders and a correlation between the reduction in the CD20+ B-cells score and the improvement in the DAS28 at 12-weeks. Conclusions: The analysis of the synovial histopathology may be a helpful tool to identify among clinically indistinguishable patients those with lower probability of response to TNFα-blockade.

New Developments in Transcriptomic Analysis of Synovial Tissue

Transcriptomic technologies are constantly changing and improving, resulting in an ever increasing understanding of gene expression in health and disease. These technologies have been used to investigate the pathological changes occurring in the joints of rheumatoid arthritis patients, leading to discoveries of disease mechanisms, and novel potential therapeutic targets. Microarrays were initially used on both whole tissue and cell subsets to investigate research questions, with bulk RNA sequencing allowing for further elaboration of these findings. A key example is the classification of pathotypes in rheumatoid arthritis using RNA sequencing that had previously been discovered using microarray and histology. Single-cell sequencing has now delivered a step change in understanding of the diversity and function of subpopulations of cells, in particular synovial fibroblasts. Future technologies, such as high resolution spatial transcriptomics, will enable step changes integrating single cell transcriptomic and geographic data to provide an integrated understanding of synovial pathology.

Molecular profiling of rheumatoid arthritis patients reveals an association between innate and adaptive cell populations and response to anti-tumor necrosis factor

Background

The goal of this study is to use comprehensive molecular profiling to characterize clinical response to anti-TNF therapy in a real-world setting and identify reproducible markers differentiating good responders and non-responders in rheumatoid arthritis (RA).

Methods

Whole-blood mRNA, plasma proteins, and glycopeptides were measured in two cohorts of biologic-naïve RA patients (n = 40 and n = 36) from the Corrona CERTAIN (Comparative Effectiveness Registry to study Therapies for Arthritis and Inflammatory coNditions) registry at baseline and after 3 months of anti-TNF treatment. Response to treatment was categorized by EULAR criteria. A cell type-specific data analysis was conducted to evaluate the involvement of the most common immune cell sub-populations. Findings concordant between the two cohorts were further assessed for reproducibility using selected NCBI-GEO datasets and clinical laboratory measurements available in the CERTAIN database.

Results

A treatment-related signature suggesting a reduction in neutrophils, independent of the status of response, was indicated by a high level of correlation (ρ = 0.62; p < 0.01) between the two cohorts. A baseline, response signature of increased innate cell types in responders compared to increased adaptive cell types in non-responders was identified in both cohorts. This result was further assessed by applying the cell type-specific analysis to five other publicly available RA datasets. Evaluation of the neutrophil-to-lymphocyte ratio at baseline in the remaining patients (n = 1962) from the CERTAIN database confirmed the observation (odds ratio of good/moderate response = 1.20 [95% CI = 1.03–1.41, p = 0.02]).

Conclusion

Differences in innate/adaptive immune cell type composition at baseline may be a major contributor to response to anti-TNF treatment within the first 3 months of therapy.

A Combined Transcriptomic and Genomic Analysis Identifies a Gene Signature Associated With the Response to Anti-TNF Therapy in Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) is the most frequent autoimmune disease involving the joints. Although anti-TNF therapies have proven effective in the management of RA, approximately one third of patients do not show a significant clinical response. The objective of this study was to identify new genetic variation associated with the clinical response to anti-TNF therapy in RA.

Methods: We performed a sequential multi-omic analysis integrating different sources of molecular information. First, we extracted the RNA from synovial biopsies of 11 RA patients starting anti-TNF therapy to identify gene coexpression modules (GCMs) in the RA synovium. Second, we analyzed the transcriptomic association between each GCM and the clinical response to anti-TNF therapy. The clinical response was determined at week 14 using the EULAR criteria. Third, we analyzed the association between the GCMs and anti-TNF response at the genetic level. For this objective, we used genome-wide data from a cohort of 348 anti-TNF treated patients from Spain. The GCMs that were significantly associated with the anti-TNF response were then tested for validation in an independent cohort of 2,706 anti-TNF treated patients. Finally, the functional implication of the validated GCMs was evaluated via pathway and cell type epigenetic enrichment analyses.

Results: A total of 149 GCMs were identified in the RA synovium. From these, 13 GCMs were found to be significantly associated with anti-TNF response (P < 0.05). At the genetic level, we detected two of the 13 GCMs to be significantly associated with the response to adalimumab (P = 0.0015) and infliximab (P = 0.021) in the Spain cohort. Using the independent cohort of RA patients, we replicated the association of the GCM associated with the response to adalimumab (P = 0.0019). The validated module was found to be significantly enriched for genes involved in the nucleotide metabolism (P = 2.41e-5) and epigenetic marks from immune cells, including CD4+ regulatory T cells (P = 0.041).

Conclusions: These findings show the existence of a drug-specific genetic basis for anti-TNF response, thereby supporting treatment stratification in the search for response biomarkers in RA.

Computational deconvolution of synovial tissue cellular composition: presence of adipocytes in synovial tissue decreased during arthritis pathogenesis and progression

Osteoarthritis (OA) and rheumatoid arthritis (RA) are the most common forms of arthritis. The synovial tissue is the major site of inflammation of OA and RA and consists of diverse cells. Synovial tissue cell composition changes during arthritis pathogenesis and progression have not been systematically characterized and may provide critical insights into disease processes. In this study we aimed at systematically examining cellular changes in synovial tissue. Publicly available synovial tissue transcriptomic data sets were used. We computationally estimated cell compositions in synovial tissue based on transcriptomic data and compared cell compositions in different diseases or at different disease stages. Synovial fibroblasts, macrophages, adipocytes, and immune cells were the major cell types in all synovial tissue. Both OA and RA patients had a significantly lower adipocyte fraction compared with healthy controls. The decrease trend was also observed during OA and RA progression. The fraction of monocytes was also increased in both OA and RA arthritis patients, consistent with the observations that inflammation involved in both OA and RA. But the monocyte fraction in RAs was much higher than the ones in healthy controls and OAs. The M2 macrophage fraction was reduced in RA compared with OA, the reduction trend continued during RA progression from the early- to the late-stage. There were consistent cell composition differences between different types or stages of arthritis. Both in RA and OA, the new discovery of changes in the adipocyte and M2 macrophage fractions has potential leading to novel therapeutic development.

Clinical Applications of Synovial Biopsy

The synovial tissue is a primary target of multiple diseases characterized by different pathogenic mechanisms, including infective, deposition, neoplastic, and chronic immune-inflammatory pathologies. Synovial biopsy can have a relevant role in differential diagnosis of specific conditions in clinical practice, although its exploitation remains relatively limited. In particular, no validated synovial-tissue-derived biomarkers are currently available in the clinic to aid in the diagnosis and management in most frequent forms of chronic inflammatory arthropathies, namely rheumatoid arthritis (RA) and the spondyloarthritides (SpA). In this brief review, we will discuss the current spectrum of clinical applications of synovial biopsy in routine rheumatologic care and will provide an analysis of the perspectives for its potential exploitation in patients with chronic inflammatory arthritides.

Utilizing a PTPN22 gene signature to predict response to targeted therapies in rheumatoid arthritis

Despite the development of several targeted therapies for rheumatoid arthritis (RA), there is still no reliable drug-specific predictor to assist rheumatologists in selecting the most effective targeted therapy for each patient. Recently, a gene signature caused by impaired induction of PTPN22 in anti-CD3 stimulated peripheral blood mononuclear cells (PBMC) was observed in healthy at-risk individuals. However, the downstream target genes of PTPN22 and the molecular mechanisms regulating its expression are still poorly understood. Here we report that the PTPN22 gene signature is also present in PBMC from patients with active RA and can be reversed after effective treatment. The expression of PTPN22 correlates with that of more than 1000 genes in Th cells of anti-CD3 stimulated PBMC of healthy donors and is inhibited by TNFα or CD28 signals, but not IL-6, through distinct mechanisms. In addition, the impaired induction of PTPN22 in PBMC of patients with active RA can be normalized in vitro by several targeted therapies. More importantly, the in vitro normalization of PTPN22 expression correlates with clinical response to the targeted therapies in a longitudinal RA cohort. Thus, in vitro normalization of PTPN22 expression by targeted therapies can potentially be used to predict clinical response.

Synovial Tissue Biopsy Research

Synovial tissue is a key structure in diarthrodial joints and is the primary target of inflammation in autoimmune arthritis. The study of synovial tissue has developed significantly in the last two decades as arthroscopic and ultrasonographic techniques have allowed visualization and access to synovial biopsy. Further progress in synovial tissue processing and analysis has improved studies of disease pathogenesis, biomarker discovery, and molecular therapeutic targeting with increasingly specialized analytical and technological approaches. In September 2018 the first course on Synovial Tissue Biopsies was convened in Brussels, in this Mini Review these approaches will be described and I will summarize how synovial tissue research advanced.

Synovial Tissue: Turning the Page to Precision Medicine in Arthritis

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease targeting the joints. Current treatment strategies are based on clinical, biological and radiological features, yet still fail to reach the goal of early low disease activity in a significant number of cases. Hence, there is a need for refining current treatment algorithms, using accurate markers of response to therapy. Because RA induces histological and molecular alterations in the synovium even before apparition of clinical symptoms, synovial biopsies are a promising tool in the search of such new biomarkers. Histological and molecular characteristics of RA synovitis are heterogeneous. Variations in synovial lining layer hyperplasia, in cellular infiltration of the sublining by immune cells of myeloid and lymphoid lineages, and in molecular triggers of these features are currently categorized using well-defined pathotypes: myeloid, lymphoid, fibroid and pauci-immune. Here, we first bring the plasticity of RA synovitis under scrutiny, i.e., how variations in synovial characteristics are associated with relevant clinical features (disease duration, disease activity, effects of therapies, disease severity). Primary response to a specific drug could be, at least theoretically, related to the representation of the molecular pathway targeted by the drug in the synovium. Alternatively, absence of primary response to a specific agent could be due to disease severity, i.e., overrepresentation of all synovial molecular pathways driving disease activity overwhelming the capacity of any drug to block them. Using this theoretical frame, we will highlight how the findings of previous studies trying to link response to therapy with synovial changes provide promising perspectives on bridging the gap to personalized medicine in RA.

Synovial Tissue Heterogeneity in Rheumatoid Arthritis and Changes With Biologic and Targeted Synthetic Therapies to Inform Stratified Therapy

The treatment of rheumatoid arthritis (RA) has been transformed with the introduction of biologic disease modifying anti-rheumatic drugs (bDMARD) and more recently, targeted synthetic DMARD (tsDMARD) therapies in the form of janus-kinase inhibitors. Nevertheless, response to these agents varies such that a trial and error approach is adopted; leading to poor patient quality of life, and long-term outcomes. There is thus an urgent need to identify effective biomarkers to guide treatment selection. A wealth of research has been invested in this field but with minimal progress. Increasingly recognized is the importance of evaluating synovial tissue, the primary site of RA, as opposed to peripheral blood-based investigation. In this mini-review, we summarize the literature supporting synovial tissue heterogeneity, the conceptual basis for stratified therapy. This includes recognition of distinct synovial pathobiological subtypes and associated molecular pathways. We also review synovial tissue studies that have been conducted to evaluate the effect of individual bDMARD and tsDMARD on the cellular and molecular characteristics, with a view to identifying tissue predictors of response. Initial observations are being brought into the clinical trial landscape with stratified biopsy trials to validate toward implementation. Furthermore, development of tissue based omics technology holds still more promise in advancing our understanding of disease processes and guiding future drug selection.

Compendium of synovial signatures identifies pathologic characteristics for predicting treatment response in rheumatoid arthritis patients

Rheumatoid arthritis (RA) is therapeutically challenging due to patient heterogeneity and variability. Herein we describe a novel integration of RA synovial genome-scale transcriptomic profiling of different patient cohorts that can be used to provide predictive insights on drug responses. A normalized compendium consisting of 256 RA synovial samples that cover an intersection of 11,769 genes from 11 datasets was build and compared with similar datasets derived from OA patients and healthy controls. Differentially expression genes (DEGs) that were identified in three independent methods were fed into functional network analysis, with subsequent grouping of the samples based on a non-negative matrix factorization method. RA-relevant pathway activation scores and four machine learning classification techniques supported the generation of a predictive model of patient treatment response. We identified 876 up-regulated DEGs including 24 known genetic risk factors and 8 drug targets. DEG-based subgrouping revealed 3 distinct RA patient clusters with distinct activity signatures for RA-relevant pathways. In the case of infliximab, we constructed a classifier of drug response that was highly accurate with an AUC/AUPR of 0.92/0.86. The most informative pathways in achieving this performance were the NFκB-, FcεRI- TCR-, and TNF signaling pathways. Similarly, the expression of the HMMR, PRPF4B, EVI2A, RAB27A, MALT1, SNX6, and IFIH1 genes contributed in predicting the patient outcome. Construction and analysis of normalized synovial transcriptomic compendia can provide useful insights for understanding RA-related pathway involvement and drug responses for individual patients.

Liquid biopsies to guide therapeutic decisions in rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic, immune-mediated inflammatory disease that has transitioned from a debilitating disease to a chronic, controllable disease. This has been possible due to the introduction of new treatment strategies like "treat-to-target," in which the clinician treats the patient aggressively enough to reach low disease activity or remission, and the introduction of new therapeutic agents, such as biological therapies, which can lead to the prevention of damage by early diagnosis and initiation of treatment. Attention is now being directed toward identifying the optimal treatment for each patient, one that will be the most efficient and have the least number of side effects. Much work has been done to find serologic and synovial biomarkers of response to various RA treatments. Proteomics, genomics and, in the past few years, metabolomics, have all been used in the quest of identifying these biomarkers. Blood-based liquid biopsies provide a minimally invasive alternative to synovial biopsies to identify cellular and molecular signatures that can be used to longitudinally monitor response and allow for personalized medicine approach. Liquid biopsies are comprised of cell-free DNA, immune circulating cells, and extracellular vesicles, and are being increasingly and successfully used in the field of oncology for diagnosis, progression, prognosis, and prediction of response to treatment. Recently, researchers have also begun investigating the usefulness of liquid biopsies in the field of rheumatology; in this review, we will focus on the potential of liquid biopsy blood samples as biomarkers of response to treatment in patients with RA.

Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue

Background

Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.

Methods

Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq.

Results

Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4⁺ and CD8⁺ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.

Conclusions

We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1631-y) contains supplementary material, which is available to authorized users.

A Multicenter Retrospective Analysis Evaluating Performance of Synovial Biopsy Techniques in Patients With Inflammatory Arthritis: Arthroscopic Versus Ultrasound-Guided Versus Blind Needle Biopsy

OBJECTIVE

To evaluate whether the choice of synovial biopsy technique (arthroscopy, blind needle [BN] biopsy, ultrasound [US]-guided portal and forceps [P&F], or US-guided needle biopsy [NB]) translates to significant variation in synovial tissue quality and quantity, with the aim of informing recommendations for the choice of synovial sampling technique within clinical trials.

METHODS

In total, 159 procedures from 5 academic rheumatology centers were evaluated. Hematoxylin and eosin-stained, paraffin-embedded synovial tissue sections from patients with inflammatory arthritis were assessed in order to determine the proportion of graded synovial fragments, total area of graded synovial tissue, and synovitis score per procedure. RNA quantity (μg of RNA) and quality (RNA integrity number) per procedure were also assessed in the synovial samples.

RESULTS

In this study, 84 of the 159 procedures performed on large joints at baseline (25 arthroscopic, 35 US-P&F, 11 US-NB, and 13 BN biopsies), 41 of the 159 procedures performed on small joints at baseline (11 US-P&F, 20 US-NB, and 10 BN biopsies), and 34 sequential biopsy procedures were evaluated. Compared to all other techniques evaluated in the small and large joints, fewer small joint BN biopsies and a significantly lower proportion of large joint BN biopsies yielded graded synovial tissue. No significant difference in either the proportion of graded tissue samples or total graded synovial tissue area between the US-NB and arthroscopic large joint procedures was demonstrated. Among the sequential biopsy procedures evaluated (small joint US-NB, large joint arthroscopy, US-P&F biopsy, and BN biopsy), no significant difference in the proportion of graded synovial tissue or total graded synovial tissue area was demonstrated. All procedures yielded RNA of significant quality and quantity for subsequent transcriptomic analysis.

CONCLUSION

These data support the integration of US-guided methods along with arthroscopic biopsy for clinical trial protocols in which sequential sampling of synovium from the large and small joints is needed for both histologic and molecular analysis. BN biopsy may be considered if graded synovial tissue is not required for subsequent analyses.

A novel gene and pathway-level subtyping analysis scheme to understand biological mechanisms in complex disease: a case study in rheumatoid arthritis

Complex diseases have heterogeneous underlying molecular mechanisms. In order to improve the diagnosis and treatment of disease, it is vital to stratify patients into homogeneous subgroups that share a similar disease etiology. In this study, we performed gene-level subtyping analysis on two independent Rheumatoid Arthritis gene expression cohorts from different ethnic groups to discover the possible disease mechanisms associated with each subtype. Also, a novel pathway-level analysis is proposed to increase the subtyping robustness and facilitate biological interpretation. This approach could stratify RA patients into two robust and homogeneous groups with differing activation of central signal transduction pathways and pro-inflammatory cytokines in the pathogenesis of RA. Such a methodology can help understand disease mechanisms at play in different patient sub-populations and also potentially explain why some patients don't respond to anti-TNF treatment.

Prediction of Response to Targeted Treatment in Rheumatoid Arthritis

Rheumatoid arthritis is an autoimmune syndrome presenting with chronic inflammation of the joints. Patients with the same diagnosis can present with different phenotypes. In some patients severe joint inflammation and early joint destruction are observed, whereas a milder phenotype can be seen in others. Conversely, patients with the same signs and symptoms may exhibit different immunological and molecular abnormalities. Since the introduction of early treatment in clinical practice, the treat to target principle, and new medicines such as biologic disease-modifying antirheumatic drugs, clinical remission can be achieved early in the disease course, albeit not in all patients. The clinical response and efficacy of biologic disease-modifying antirheumatic drugs vary among different individuals. Therefore, there is a need to develop a more personalized approach toward treatment to achieve rapid remission in every patient to prevent disability and restore and maintain quality of life, without unnecessary adverse effects, in a cost-effective manner. The latest data from explorative studies of predictive markers of response are discussed here, together with a preliminary treatment algorithm based on currently available knowledge.

Pathogenetic insights from the treatment of rheumatoid arthritis

Rheumatoid arthritis is a chronic autoimmune disease that causes progressive articular damage, functional loss, and comorbidity. The development of effective biologics and small-molecule kinase inhibitors in the past two decades has substantially improved clinical outcomes. Just as understanding of pathogenesis has led in large part to the development of drugs, so have mode-of-action studies of these specific immune-targeted agents revealed which immune pathways drive articular inflammation and related comorbidities. Cytokine inhibitors have definitively proven a critical role for tumour necrosis factor α and interleukin 6 in disease pathogenesis and possibly also for granulocyte-macrophage colony-stimulating factor. More recently, clinical trials with Janus kinase (JAK) inhibitors have shown that cytokine receptors that signal through the JAK/STAT signalling pathway are important for disease, informing the pathogenetic function of additional cytokines (such as the interferons). Finally, successful use of costimulatory blockade and B-cell depletion in the clinic has revealed that the adaptive immune response and the downstream events initiated by these cells participate directly in synovial inflammation. Taken together, it becomes apparent that understanding the effects of specific immune interventions can elucidate definitive molecular or cellular nodes that are essential to maintain complex inflammatory networks that subserve diseases like rheumatoid arthritis.

Application of omics in predicting anti-TNF efficacy in rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by progressive joint erosion. Tumor necrosis factor (TNF) antagonists are the most widely used biological disease-modifying anti-rheumatic drug in RA. However, there continue to be one third of RA patients who have poor or no response to TNF antagonists. Following consideration of the uncertainty of therapeutic effects and the high price of TNF antagonists, it is worthy to predict the treatment responses before anti-TNF therapy. According to the comparisons between the responders and non-responders to TNF antagonists by omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, rheumatologists are eager to find significant biomarkers to predict the effect of TNF antagonists in order to optimize the personalized treatment in RA.

Can Synovial Pathobiology Integrate with Current Clinical and Imaging Prediction Models to Achieve Personalized Health Care in Rheumatoid Arthritis?

Although great progress has been made in the past decade toward understanding the pathogenesis of rheumatoid arthritis (RA), clinicians remain some distance from a goal of personalized health care. The capacity to diagnose RA early, predict prognosis, and moreover predict response to biologic therapies has been a research focus for many years. How currently available clinical prediction models can facilitate such goals is reviewed in this article. In addition, the role of current imaging techniques in this regard is also discussed. Finally, the authors review the current literature regarding synovial biomarkers and consider whether integration of synovial pathobiology into clinical prediction algorithms may enhance their predictive value.

Is there a role of synovial biopsy in drug development?

Rheumatoid arthritis (RA) is an autoimmune disease which causes significant pain, joint deformity, functional disability. The pathological hallmark of RA is inflammation of the synovium characterized by involvement of inflammatory and resident stromal cells, soluble mediators and signalling pathways leading to irreversible joint destruction. The treatment goal in RA has evolved over the last decade towards a target of disease remission that is achieved in less than a third of patients in clinical trials. The lack of therapeutic response to current treatments is suggestive of alternative drivers of RA pathogenesis that might serve as promising therapeutic targets. There are data to justify the use of synovial tissue in early drug development. Synovial tissue represents an appropriate compartment to be studied in patients with inflammatory arthritis and provides information that is distinct from peripheral blood. Modern techniques have made the procedure much more accessible and ultrasound guided biopsies represent a safe and acceptable option. Advances in analytic technologies allowing transcriptomic level of analysis can provide unique inside to target organ/tissue following the exposure to investigational medicinal product. However, there are still caveats with regard to both the choice of technique and analytical methods. Therefore the significance of synovial biopsy remains to be determined in future clinical trials. The aim of the current debate is to explore the potential for accessing and evaluating synovial tissue in early drug development, to summarize lessons we have learned from clinical trials and to discuss the challenges that have arisen so far.

Immunopathology of synovitis: from histology to molecular pathways

Increased knowledge about pathological processes active in inflammatory joint diseases is needed to initiate personalized medicine based on targeted treatments in the future. The molecular and cellular pathways that are active during joint inflammation may differ between the various inflammatory joint diseases, between different patient subgroups within one disease, or even between different stages of the disease in a single patient. In this review, we evaluate synovial inflammation in terms of descriptive histopathology through to more functional studies on human synovial tissue inflammation in RA and SpA, in phenotypic subgroups of RA and SpA patients, and during the disease course of both diseases.

Evaluation of Minimally Invasive, Ultrasound-guided Synovial Biopsy Techniques by the OMERACT Filter--Determining Validation Requirements

OBJECTIVE

Because limited data currently support the clinical utility of peripherally expressed biomarkers in guiding treatment decisions for patients with rheumatoid arthritis, the search has turned to the disease tissue. The strategic aim of the Outcome Measures in Rheumatology (OMERACT) synovitis working group over the years has been to develop novel diagnostic and prognostic synovial biomarkers. A critical step in this process is to refine and validate minimally invasive, technically simple, robust techniques to sample synovial tissue, for use both in clinical trials and routine clinical practice. The objective of the synovitis working group (SWG) at OMERACT 12 (2014) was to examine whether recently developed ultrasound (US)-guided synovial biopsy techniques could be validated according to the OMERACT filter for future clinical use recommendation.

METHODS

The SWG examined whether current data reporting US-guided synovial biopsy of both large and small joints addressed the OMERACT filters of truth, discrimination, and feasibility.

RESULTS

There are currently limited data examining the performance of US-guided synovial biopsy, mainly from observational studies. Thus, it remains critical to evaluate its performance, within the clinical trials context, against the current gold standard of arthroscopic biopsy, with particular reference to: (1) synovial tissue yield, (2) capacity to determine treatment response as measured by a validated synovial biomarker, and (3) tolerability of the procedure.

CONCLUSION

We summarize the discrete work packages agreed to as requirements to validate US-guided synovial biopsy and therefore lead to a global consensus on the use of synovial biopsy for research and clinical practice.

Inflammatory cytokines epigenetically regulate rheumatoid arthritis fibroblast-like synoviocyte activation by suppressing HDAC5 expression

OBJECTIVES

Epigenetic modifications play an important role in the regulation of gene transcription and cellular function. Here, we examined if pro-inflammatory factors present in the inflamed joint of patients with rheumatoid arthritis (RA) could regulate histone deacetylase (HDAC) expression and function in fibroblast-like synoviocytes (FLS).

METHODS

Protein acetylation in synovial tissue was assessed by immunohistochemistry. The mRNA levels of HDAC family members and inflammatory mediators in the synovial tissue and the changes in HDAC expression in RA FLS were measured by quantitative (q) PCR. FLS were either transfected with HDAC5 siRNA or transduced with adenoviral vector encoding wild-type HDAC5 and the effects of HDAC5 manipulation were examined by qPCR arrays, ELISA and ELISA-based assays.

RESULTS

Synovial class I HDAC expression was associated with local expression of tumour necrosis factor (TNF) and matrix metalloproteinase-1, while class IIa HDAC5 expression was inversely associated with parameters of disease activity (erythrocyte sedimentation rate, C-reactive protein, Disease Activity Score in 28 Joints). Interleukin (IL)-1β or TNF stimulation selectively suppressed HDAC5 expression in RA FLS, which was sufficient and required for optimal IFNB, CXCL9, CXCL10 and CXCL11 induction by IL-1β, associated with increased nuclear accumulation of the transcription factor, interferon regulatory factor 1(IRF1).

CONCLUSIONS

Inflammatory cytokines suppress RA FLS HDAC5 expression, promoting nuclear localisation of IRF1 and transcription of a subset of type I interferon response genes. Our results identify HDAC5 as a novel inflammatory mediator in RA, and suggest that strategies rescuing HDAC5 expression in vivo, or the development of HDAC inhibitors not affecting HDAC5 activity, may have therapeutic applications in RA treatment.

Divergent gene activation in peripheral blood and tissues of patients with rheumatoid arthritis, psoriatic arthritis and psoriasis following infliximab therapy

Objective

The immune inflammatory disorders rheumatoid arthritis (RA), psoriatic arthritis (PsA) and psoriasis (Ps) share common pathologic features and show responsiveness to anti-tumor necrosis factor (TNF) agents yet they are phenotypically distinct. The aim of this study was to examine if anti-TNF therapy is associated with divergent gene expression profiles in circulating cells and target tissues of patients with these diseases.

Methods

Peripheral blood CD14⁺ and CD14⁻ cells were isolated from 9 RA, 12 PsA and 10 Ps patients before and after infliximab (IFX) treatment. Paired synovial (n = 3, RA, PsA) and skin biopsies (n = 5, Ps) were also collected. Gene expression was analyzed by microarrays.

Results

26 out of 31 subjects responded to IFX. The transcriptional response of CD14⁺ cells to IFX was unique for the three diseases, with little overlap (<25%) in significantly changed gene lists (with PsA having the largest number of changed genes). In Ps, altered gene expression was more pronounced in lesional skin (relative to paired, healthy skin) compared to blood (relative to healthy controls). Marked suppression of up-regulated genes in affected skin was noted 2 weeks after therapy but the expression patterns differed from uninvolved skin. Divergent patterns of expression were noted between the blood cells and skin or synovial tissues in individual patients. Functions that promote cell differentiation, proliferation and apoptosis in all three diseases were enriched. RA was enriched in functions in CD14⁻ cells, PsA in CD14⁺ cells and Ps in both CD14⁺ and CD14⁻ cells, however, the specific functions showed little overlap in the 3 disorders.

Conclusion

Divergent patterns of altered gene expression are observed in RA, PsA and Ps patients in blood cells and target organs in IFX responders. Differential gene expression profiles in the blood do not correlate with those in target organs.

Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics

INTRODUCTION

Rheumatoid arthritis (RA) is a complex and clinically heterogeneous autoimmune disease. Currently, the relationship between pathogenic molecular drivers of disease in RA and therapeutic response is poorly understood.

METHODS

We analyzed synovial tissue samples from two RA cohorts of 49 and 20 patients using a combination of global gene expression, histologic and cellular analyses, and analysis of gene expression data from two further publicly available RA cohorts. To identify candidate serum biomarkers that correspond to differential synovial biology and clinical response to targeted therapies, we performed pre-treatment biomarker analysis compared with therapeutic outcome at week 24 in serum samples from 198 patients from the ADACTA (ADalimumab ACTemrA) phase 4 trial of tocilizumab (anti-IL-6R) monotherapy versus adalimumab (anti-TNFα) monotherapy.

RESULTS

We documented evidence for four major phenotypes of RA synovium - lymphoid, myeloid, low inflammatory, and fibroid - each with distinct underlying gene expression signatures. We observed that baseline synovial myeloid, but not lymphoid, gene signature expression was higher in patients with good compared with poor European league against rheumatism (EULAR) clinical response to anti-TNFα therapy at week 16 (P =0.011). We observed that high baseline serum soluble intercellular adhesion molecule 1 (sICAM1), associated with the myeloid phenotype, and high serum C-X-C motif chemokine 13 (CXCL13), associated with the lymphoid phenotype, had differential relationships with clinical response to anti-TNFα compared with anti-IL6R treatment. sICAM1-high/CXCL13-low patients showed the highest week 24 American College of Rheumatology (ACR) 50 response rate to anti-TNFα treatment as compared with sICAM1-low/CXCL13-high patients (42% versus 13%, respectively, P =0.05) while anti-IL-6R patients showed the opposite relationship with these biomarker subgroups (ACR50 20% versus 69%, P =0.004).

CONCLUSIONS

These data demonstrate that underlying molecular and cellular heterogeneity in RA impacts clinical outcome to therapies targeting different biological pathways, with patients with the myeloid phenotype exhibiting the most robust response to anti-TNFα. These data suggest a path to identify and validate serum biomarkers that predict response to targeted therapies in rheumatoid arthritis and possibly other autoimmune diseases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01119859

Gene expression analysis in RA: towards personalized medicine

Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathogenesis. Inflammation is the main feature of RA; however, many biological processes are involved at different stages of the disease. Gene expression signatures offer management tools to meet the current needs for personalization of RA patients' care. This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools, reinforcing the need for harmonization if gene expression signatures are to become a useful clinical tool in personalized medicine for RA patients.

New learnings on the pathophysiology of RA from synovial biopsies

PURPOSE OF REVIEW

To critically appraise the literature related to the pathophysiology of rheumatoid arthritis (RA) focusing on the contribution of synovial tissue pathology (synovitis) in determining diverse clinical outcome/therapeutic response.

RECENT FINDINGS

RA synovitis is highly heterogeneous with diverse cellular and molecular signatures (pathotypes) emerging as potential taxonomic classifiers of disease phenotypes.The challenge is to understand mechanistically the sophisticated interplay between systemic disease 'initiators' and joint-specific 'localizing/perpetuating' factors leading to disparate coupling of inflammation/tissue-destructive pathways and disease outcome. Synovial tissue analysis has been instrumental in enhancing understanding of R0A pathogenesis and developing targeted DMARD-biologic therapies. The next step is to elucidate the relationship of different synovial pathotypes/molecular signatures with therapeutic response/resistance in randomized clinical trials in order to develop effective therapies for 'resistant' patients. The development of ultrasound-guided synovial biopsy as a rapid, safe and well tolerated procedure that enables synovial tissue collection from most joints/patients will facilitate such studies.

SUMMARY

RA is a heterogeneous clinical and pathobiological entity. Specific pathways within synovial tissues are emerging as associated with diverse clinical evolution and therapeutic response/resistance that, if confirmed in randomized clinical trials, may lead to the development of synovial tissue analysis as a potential clinical tool for patient stratification.

Short communication: a mutation in the 3' untranslated region diminishes microRNA binding and alters expression of the OLR1 gene

The oxidized low-density lipoprotein (lectin-like) receptor 1 (OLR1) gene plays an important role in the degradation of the oxidized low-density lipoprotein, which causes damage to the arterial endothelium. Previous studies have shown that a single nucleotide polymorphism (SNP) in the 3' untranslated region (UTR) of OLR1 was associated with milk production and health traits in dairy cattle and with loin eye area and marbling depth in Qinchuan beef cattle. However, the mechanisms by which this SNP affects these traits are not well understood. MicroRNA (miRNA or mir) are small noncoding RNA that regulate gene expression by binding to target mRNA at their UTR to degrade or to repress translation of the target transcript. We hypothesized that miRNA bind to the 3' UTR of OLR1 to cause expression changes of the gene. To test this hypothesis, the Bos taurus autosome (bta)-mir-370miRNA was selected for this study based on bioinformatics prediction analysis. Two vectors that included A or C nucleotides of the 3' UTR SNP and 1 control vector were co-transfected with the vector of bta-miR-370 into human embryonic kidney 293 (HEK293) cells. Results of the dual-luciferase reporter assay showed that the activity of luciferase was significantly lower in cells transfected with the A nucleotide vector than that of the C nucleotide and control vectors. The assay also indicated that activity of miRNA bta-mir-370 was associated with a differential allelic regulation of OLR1 expression. These results imply that the 3' UTR SNP of the OLR1 gene is a strong candidate marker for selection in cattle breeding programs.