Synovial tissue features associated with poor prognosis in inflammatory arthritis

BACKGROUND

Inflammatory arthritis encompasses a group of immune-mediated diseases characterized by chronic joint inflammation. Despite having pathogenic mechanisms in common, the prognosis of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and undifferentiated arthritis (UA) could be different regarding progression to chronic, to erosive, or to self-limited disease. Our aim was to evaluate the potential association of synovial tissue (ST) inflammatory cell infiltrate, the presence of ectopic lymphoid neogenesis (LN +) structures, and poor prognosis factors (PPF) in patients with RA, PsA, and UA.

METHODS

We conducted a retrospective study including patients with active arthritis (RA, PsA, UA) who had ST obtained by rheumatological arthroscopy or ultrasound-guided biopsy. Clinical, demographic, and immunohistochemical data of the synovium was evaluated. Patients with biological therapy at the time of synovial biopsy were excluded. PPF in patients with RA and UA were defined by the presence of anti-cyclic citrullinated peptide antibodies and/or rheumatoid factor, development of bone erosions, or requirement of biological therapy during the follow-up. PPF in patients with PsA were defined as the presence of high levels of acute-phase reactants (ESR/CRP), dactylitis or nail involvement at the time of biopsy, development of bone erosion, or requirement of biological therapy during the follow-up.

RESULTS

A total of 88 patients were included: 26 RA, 33 PsA, and 29 UA. All patients were followed up for 5 years after the biopsy. Fourteen (53.84%) RA patients had PPF, and 17 (65.38%) had LN + . LN + was associated with PPF (p 0.038) and biologic therapy initiation (p 0.018). A total of 14 (43.75%) PsA patients had PPF. CD15 infiltrate (410.68 [SD 477.63] cells/mm2) was associated with PPF (p 0.008) in PsA patients. Sixteen (55.17%) patients with UA had PPF, and 13 (44.82%) had LN + . In this group, synovial CD68 + macrophages cells density was negatively correlated with DAS28-CRP (r =  - 0.346, p 0.042).

CONCLUSIONS

The presence of LN + and higher CD15 + polymorphonuclear cells infiltrate was associated with PPF in RA and PsA, respectively. No associations were found for UA. These findings suggest a great heterogeneity of the ST features and its pathogenic implications in the subtypes of inflammatory 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.

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

BACKGROUND

We sought to identify features that distinguish osteoarthritis (OA) and rheumatoid arthritis (RA) hematoxylin and eosin (H&E)-stained synovial tissue samples.

METHODS

We compared fourteen pathologist-scored histology features and computer vision-quantified cell density (147 OA and 60 RA patients) in H&E-stained synovial tissue samples from total knee replacement (TKR) explants. A random forest model was trained using disease state (OA vs RA) as a classifier and histology features and/or computer vision-quantified cell density as inputs.

RESULTS

Synovium from OA patients had increased mast cells and fibrosis (p < 0.001), while synovium from RA patients exhibited increased lymphocytic inflammation, lining hyperplasia, neutrophils, detritus, plasma cells, binucleate plasma cells, sub-lining giant cells, fibrin (all p < 0.001), Russell bodies (p = 0.019), and synovial lining giant cells (p = 0.003). Fourteen pathologist-scored features allowed for discrimination between OA and RA, producing a micro-averaged area under the receiver operating curve (micro-AUC) of 0.85±0.06. This discriminatory ability was comparable to that of computer vision cell density alone (micro-AUC = 0.87±0.04). Combining the pathologist scores with the cell density metric improved the discriminatory power of the model (micro-AUC = 0.92±0.06). The optimal cell density threshold to distinguish OA from RA synovium was 3400 cells/mm2, which yielded a sensitivity of 0.82 and specificity of 0.82.

CONCLUSIONS

H&E-stained images of TKR explant synovium can be correctly classified as OA or RA in 82% of samples. Cell density greater than 3400 cells/mm2 and the presence of mast cells and fibrosis are the most important features for making this distinction.

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.

A Review of Compartmentalised Inflammation and Tertiary Lymphoid Structures in the Pathophysiology of Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, immune-mediated, demyelinating disease of the central nervous system (CNS). The most common form of MS is a relapsing–remitting disease characterised by acute episodes of demyelination associated with the breakdown of the blood–brain barrier (BBB). In the relapsing–remitting phase there is often relative recovery (remission) from relapses characterised clinically by complete or partial resolution of neurological symptoms. In the later and progressive stages of the disease process, accrual of neurological disability occurs in a pathological process independent of acute episodes of demyelination and is accompanied by a trapped or compartmentalised inflammatory response, most notable in the connective tissue spaces of the vasculature and leptomeninges occurring behind an intact BBB. This review focuses on compartmentalised inflammation in MS and in particular, what we know about meningeal tertiary lymphoid structures (TLS; also called B cell follicles) which are organised clusters of immune cells, associated with more severe and progressive forms of MS. Meningeal inflammation and TLS could represent an important fluid or imaging marker of disease activity, whose therapeutic abrogation might be necessary to stop the most severe outcomes of disease.

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.

Role of tertiary lymphoid organs in the regulation of immune responses in the periphery

Tertiary lymphoid organs (TLOs) are collections of immune cells resembling secondary lymphoid organs (SLOs) that form in peripheral, non-lymphoid tissues in response to local chronic inflammation. While their formation mimics embryologic lymphoid organogenesis, TLOs form after birth at ectopic sites in response to local inflammation resulting in their ability to mount diverse immune responses. The structure of TLOs can vary from clusters of B and T lymphocytes to highly organized structures with B and T lymphocyte compartments, germinal centers, and lymphatic vessels (LVs) and high endothelial venules (HEVs), allowing them to generate robust immune responses at sites of tissue injury. Although our understanding of the formation and function of these structures has improved greatly over the last 30 years, their role as mediators of protective or pathologic immune responses in certain chronic inflammatory diseases remains enigmatic and may differ based on the local tissue microenvironment in which they form. In this review, we highlight the role of TLOs in the regulation of immune responses in chronic infection, chronic inflammatory and autoimmune diseases, cancer, and solid organ transplantation.

The Neuroimmune Interplay in Joint Pain: The Role of Macrophages

Chronic pain associated with joint disorders, such as rheumatoid arthritis (RA), osteoarthritis (OA) and implant aseptic loosening (AL), is a highly debilitating symptom that impacts mobility and quality of life in affected patients. The neuroimmune crosstalk has been demonstrated to play a critical role in the onset and establishment of chronic pain conditions. Immune cells release cytokines and immune mediators that can activate and sensitize nociceptors evoking pain, through interaction with receptors in the sensory nerve terminals. On the other hand, sensory and sympathetic nerve fibers release neurotransmitters that bind to their specific receptor expressed on surface of immune cells, initiating an immunomodulatory role. Macrophages have been shown to be key players in the neuroimmune crosstalk. Moreover, macrophages constitute the dominant immune cell population in RA, OA and AL. Importantly, the targeting of macrophages can result in anti-nociceptive effects in chronic pain conditions. Therefore, the aim of this review is to discuss the nature and impact of the interaction between the inflammatory response and nerve fibers in these joint disorders regarding the genesis and maintenance of pain. The role of macrophages is highlighted. The alteration in the joint innervation pattern and the inflammatory response are also described. Additionally, the immunomodulatory role of sensory and sympathetic neurotransmitters is revised.

Inside the Joint of Inflammatory Arthritis Patients: Handling and Processing of Synovial Tissue Biopsies for High Throughput Analysis

Inflammatory arthritis is a chronic systemic autoimmune disease of unknown etiology, which affects the joints. If untreated, these diseases can have a detrimental effect on the patient's quality of life, leading to disabilities, and therefore, exhibit a significant socioeconomic impact and burden. While studies of immune cell populations in arthritis patient's peripheral blood have been informative regarding potential immune cell dysfunction and possible patient stratification, there are considerable limitations in identifying the early events that lead to synovial inflammation. The joint, as the site of inflammation and the local microenvironment, exhibit unique characteristics that contribute to disease pathogenesis. Understanding the contribution of immune and stromal cell interactions within the inflamed joint has been met with several technical challenges. Additionally, the limited availability of synovial tissue biopsies is a key incentive for the utilization of high-throughput techniques in order to maximize information gain. This review aims to provide an overview of key methods and novel techniques that are used in the handling, processing and analysis of synovial tissue biopsies and the potential synergy between these techniques. Herein, we describe the utilization of high dimensionality flow cytometric analysis, single cell RNA sequencing, ex vivo functional assays and non-intrusive metabolic characterization of synovial cells on a single cell level based on fluorescent lifetime imaging microscopy. Additionally, we recommend important points of consideration regarding the effect of different storage and handling techniques on downstream analysis of synovial tissue samples. The introduction of new powerful techniques in the study of synovial tissue inflammation, brings new challenges but importantly, significant opportunities. Implementation of novel approaches will accelerate our path toward understanding of the mechanisms involved in the pathogenesis of inflammatory arthritis and lead to the identification of new avenues of therapeutic intervention.

Three-dimensional spatial transcriptomics uncovers cell type localizations in the human rheumatoid arthritis synovium

The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA is spatially labeled in situ with barcodes in a transcriptome-wide fashion, to study local tissue interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-Seq data coupled to cell type-specific localization patterns at and around organized structures of infiltrating leukocyte cells in the synovium. Combining morphological features and high-throughput spatially resolved transcriptomics may be able to provide higher statistical power and more insights into monitoring disease severity and treatment-specific responses in seropositive and seronegative rheumatoid arthritis.

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.

Molecular and Cellular Heterogeneity in Rheumatoid Arthritis: Mechanisms and Clinical Implications

Rheumatoid arthritis is an autoimmune disease that exhibits significant clinical heterogeneity. There are various treatments for rheumatoid arthritis, including disease-modifying anti-rheumatic drugs (DMARDs), glucocorticoids, non-steroidal anti-inflammatory drugs (NSAIDs), and inflammatory cytokine inhibitors (ICI), typically associated with differentiated clinical effects and characteristics. Personalized responsiveness is observed to the standard treatment due to the pathophysiological heterogeneity in rheumatoid arthritis, resulting in an overall poor prognosis. Understanding the role of individual variation in cellular and molecular mechanisms related to rheumatoid arthritis will considerably improve clinical care and patient outcomes. In this review, we discuss the source of pathophysiological heterogeneity derived from genetic, molecular, and cellular heterogeneity and their possible impact on precision medicine and personalized treatment of rheumatoid arthritis. We provide emphasized description of the heterogeneity derived from mast cells, monocyte cell, macrophage fibroblast-like synoviocytes and, interactions within immune cells and with inflammatory cytokines, as well as the potential as a new therapeutic target to develop a novel treatment approach. Finally, we summarize the latest clinical trials of treatment options for rheumatoid arthritis and provide a suggestive framework for implementing preclinical and clinical experimental results into clinical practice.

Precision Medicine for Rheumatoid Arthritis: The Right Drug for the Right Patient-Companion Diagnostics

Despite the growing number of biologic and JAK inhibitor therapeutic agents available to treat various systemic autoimmune illnesses, the lack of a validated companion diagnostic (CDx) to accurately predict drug responsiveness for an individual results in many patients being treated for years with expensive, ineffective, or toxic drugs. This review will focus primarily on rheumatoid arthritis (RA) therapeutics where the need is greatest due to poor patient outcomes if the optimum drug is delayed. We will review current FDA-approved biologic and small molecule drugs and why RA patients switch these medications. We will discuss the sampling of various tissues for potential CDx and review early results from studies investigating drug responsiveness utilizing advanced technologies including; multiplex testing of cytokines and proteins, autoantibody profiling, genomic analysis, proteomics, miRNA analysis, and metabolomics. By using these new technologies for CDx the goal is to improve RA patient outcomes and achieve similar successes like those seen in oncology using precision medicine guided therapeutics.

Reactivation of latent tuberculosis with TNF inhibitors: critical role of the beta 2 chain of the IL-12 receptor

Tumor necrosis factor (TNF) inhibitors have improved a lot the treatment of numerous diseases, with the well-known example of rheumatoid arthritis (RA). In the early 2000s, postmarketing data quickly revealed an alarming number of severe tuberculosis (TB) under such treatment. These findings were consistent with previous results in mice where TNF is essential for lymph node formation and granuloma organization. The effects of TNF inhibition on RA synovium structure are very similar to those on granuloma, with changes in cellular interactions, cytokine, and chemokine production. In addition to the role of TNF in granuloma, the interleukin (IL)-12/interferon (IFN)-γ pathway is required for an efficient host defense against TB. Primary and secondary immunodeficiencies affecting this pathway lead to severe bacillus Calmette-Guérin (BCG) reaction or full TB. Any chronic inflammation as in RA induces a systemic Th1 defect that predisposes to TB through specific downregulation of the IL-12Rß2 chain. When TNF inhibitors are initiated, this transiently increases this risk of TB, through effects on cellular interactions in a latent TB granuloma. At a later stage, when a better control disease activity is obtained, the risk of TB is reduced but not abrogated. Given the clear benefit from TNF inhibition, latent TB infection screening at baseline is essential for an optimal safety.

Adaptive immunity in the joint of rheumatoid arthritis

Adaptive immunity plays central roles in the pathogenesis of rheumatoid arthritis (RA), as it is regarded as an autoimmune disease. Clinical investigations revealed infiltrations of B cells in the synovium, especially those with ectopic lymphoid neogenesis, associate with disease severity. While some B cells in the synovium differentiate into plasma cells producing autoantibodies such as anti-citrullinated protein antibody, others differentiate into effector B cells producing proinflammatory cytokines and expressing RANKL. Synovial B cells might also be important as antigen-presenting cells. Synovial T cells are implicated in the induction of antibody production as well as local inflammation. In the former, a recently identified CD4 T cell subset, peripheral helper T (Tph), which is characterized by the expression of PD-1 and production of CXCL13 and IL-21, is implicated, while the latter might be mediated by Th1-like CD4 T cell subsets that can produce multiple proinflammatory cytokines, including IFN-γ, TNF-α, and GM-CSF, and express cytotoxic molecules, such as perforin, granzymes and granulysin. CD8 T cells in the synovium are able to produce large amount of IFN-γ. However, the involvement of those lymphocytes in the pathogenesis of RA still awaits verification. Their antigen-specificity also needs to be clarified.

Treatment expectations as a possible prognostic factor for DMARD response in rheumatoid arthritis: a prospective cohort study

Background:

The prediction of the individual’s response to disease modifying antirheumatic drugs (DMARDs) in rheumatoid arthritis (RA) is challenging and often limited. Here we evaluated the influence of patients’ expectations towards a change in treatment with DMARD on clinical outcome in RA.

Methods:

One hundred patients (74 female) with RA (2010 ACR/EULAR classification criteria) and an upcoming change in DMARD treatment due to non-response or adverse effects were included. Patients’ treatment beliefs, health-related quality of life and treatment expectations were measured using the Beliefs about Medicines Questionnaire (BMQ), the Short Form 36, and self-designed questions about expectations before treatment initiation (T0), and DAS28-CRP was calculated at T0 and after 4 months (T4). Associations between patients’ beliefs and expectations and changes in DAS28-CRP (T0 to T4, ΔDAS28-CRP) were explored by regression analyses after multiple imputation.

Results:

A total of 99 patients were included, of whom 84 completed all questionnaires. Thirty-six percent of all variability in treatment response (ΔDAS28-CRP) was explained by expectations assessed with the questionnaires and the C-reactive protein (CRP)-value at T0. Among these, the expected improvement rate, with 10.5%, as well as the CRP-value at T0, with 10.6%, had the greatest positive effect whereas the fear of adverse effects, with 11.4%, and the BMQ.concern scale, with 9.0%, had the greatest negative impact on ΔDAS28.

Conclusion:

Patients’ expectations towards newly induced DMARD therapies influence clinical response and may serve as possible explanatory factors for treatment response affecting subjective and objective outcome parameters.

Clinical trial registration number:

DRKS00017005

Tertiary Lymphoid Structures: Diversity in Their Development, Composition, and Role

Lymph node stromal cells coordinate the adaptive immune response in secondary lymphoid organs, providing both a structural matrix and soluble factors that regulate survival and migration of immune cells, ultimately promoting Ag encounter. In several inflamed tissues, resident fibroblasts can acquire lymphoid-stroma properties and drive the formation of ectopic aggregates of immune cells, named tertiary lymphoid structures (TLSs). Mature TLSs are functional sites for the development of adaptive responses and, consequently, when present, can have an impact in both autoimmunity and cancer conditions. In this review, we go over recent findings concerning both lymph node stromal cells and TLSs function and formation and further describe what is currently known about their role in disease, particularly their potential in tolerance.

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.

Tertiary Lymphoid Organs in Rheumatoid Arthritis

Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease. RA mainly affects the joints, with inflammation of the synovial membrane, characterized by hyperplasia, neo-angiogenesis, and immune cell infiltration that drives 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. In particular, in about 40% of patients with RA, synovitis is characterized by a dense lymphocytic infiltrate that can acquire the features of fully functional tertiary lymphoid organs (TLO). These structures amplify autoimmunity and inflammation locally associated with worse prognosis and potential implications for treatment response. Here, we will review the current knowledge on TLO in RA, with a focus on their pathogenetic and clinical relevance.

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.

Assessing prognosis and prediction of treatment response in early rheumatoid arthritis: systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, debilitating disease associated with reduced quality of life and substantial costs. It is unclear which tests and assessment tools allow the best assessment of prognosis in people with early RA and whether or not variables predict the response of patients to different drug treatments.

OBJECTIVE

To systematically review evidence on the use of selected tests and assessment tools in patients with early RA (1) in the evaluation of a prognosis (review 1) and (2) as predictive markers of treatment response (review 2).

DATA SOURCES

Electronic databases (e.g. MEDLINE, EMBASE, The Cochrane Library, Web of Science Conference Proceedings; searched to September 2016), registers, key websites, hand-searching of reference lists of included studies and key systematic reviews and contact with experts.

STUDY SELECTION

Review 1 - primary studies on the development, external validation and impact of clinical prediction models for selected outcomes in adult early RA patients. Review 2 - primary studies on the interaction between selected baseline covariates and treatment (conventional and biological disease-modifying antirheumatic drugs) on salient outcomes in adult early RA patients.

RESULTS

Review 1 - 22 model development studies and one combined model development/external validation study reporting 39 clinical prediction models were included. Five external validation studies evaluating eight clinical prediction models for radiographic joint damage were also included. c-statistics from internal validation ranged from 0.63 to 0.87 for radiographic progression (different definitions, six studies) and 0.78 to 0.82 for the Health Assessment Questionnaire (HAQ). Predictive performance in external validations varied considerably. Three models [(1) Active controlled Study of Patients receiving Infliximab for the treatment of Rheumatoid arthritis of Early onset (ASPIRE) C-reactive protein (ASPIRE CRP), (2) ASPIRE erythrocyte sedimentation rate (ASPIRE ESR) and (3) Behandelings Strategie (BeSt)] were externally validated using the same outcome definition in more than one population. Results of the random-effects meta-analysis suggested substantial uncertainty in the expected predictive performance of models in a new sample of patients. Review 2 - 12 studies were identified. Covariates examined included anti-citrullinated protein/peptide anti-body (ACPA) status, smoking status, erosions, rheumatoid factor status, C-reactive protein level, erythrocyte sedimentation rate, swollen joint count (SJC), body mass index and vascularity of synovium on power Doppler ultrasound (PDUS). Outcomes examined included erosions/radiographic progression, disease activity, physical function and Disease Activity Score-28 remission. There was statistical evidence to suggest that ACPA status, SJC and PDUS status at baseline may be treatment effect modifiers, but not necessarily that they are prognostic of response for all treatments. Most of the results were subject to considerable uncertainty and were not statistically significant.

LIMITATIONS

The meta-analysis in review 1 was limited by the availability of only a small number of external validation studies. Studies rarely investigated the interaction between predictors and treatment.

SUGGESTED RESEARCH PRIORITIES

Collaborative research (including the use of individual participant data) is needed to further develop and externally validate the clinical prediction models. The clinical prediction models should be validated with respect to individual treatments. Future assessments of treatment by covariate interactions should follow good statistical practice.

CONCLUSIONS

Review 1 - uncertainty remains over the optimal prediction model(s) for use in clinical practice. Review 2 - in general, there was insufficient evidence that the effect of treatment depended on baseline characteristics.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042402.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

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.

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.

Antibody-based targeted delivery of interleukin-4 synergizes with dexamethasone for the reduction of inflammation in arthritis

Objectives

We have previously reported that F8-IL4, a fusion protein consisting of the F8 antibody specific to the alternatively-spliced extra domain A of fibronectin and of murine IL-4, cures mice with established arthritis, when used in combination with dexamethasone (DXM). The goal of this study was to assess whether other therapeutic agents, besides DXM, could induce cures in combination with F8-IL4 and to elucidate which leucocytes are most affected by the pharmacological treatment.

Methods

We performed therapy experiments in mice with CIA, using intravenous administrations of F8-IL4 in combination with DXM, MTX, murine cytotoxic T-lymphocyte-associated protein 4 fused to the fragment crystallizable portion of murine IgG2a, as well as mAbs to murine IL17A or the p40 subunit of murine IL12/IL23. Histology and immunohistochemistry for the identification of the various leucocytes were performed on the paws of mice euthanized at different therapy time points.

Results

Only the use of F8-IL4 in combination with DXM induced complete remissions, while all other combinations did not lead to cures. The light microscopical evaluation of paws with arthritis revealed a predominant infiltration of neutrophils, which substantially decreased 24 h after treatment with F8-IL4 and DXM.

Conclusion

The combination of F8-IL4 with DXM promotes a rapid anti-arthritic action by potently inhibiting neutrophil activity. A fully human analogue of F8-IL4 may find clinical utility for the treatment of neutrophil-driven chronic inflammatory conditions.

Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data

OBJECTIVE

In this study, we sought to refine histologic scoring of rheumatoid arthritis (RA) synovial tissue by training with gene expression data and machine learning.

METHODS

Twenty histologic features were assessed in 129 synovial tissue samples (n = 123 RA patients and n = 6 osteoarthritis [OA] patients). Consensus clustering was performed on gene expression data from a subset of 45 synovial samples. Support vector machine learning was used to predict gene expression subtypes, using histologic data as the input. Corresponding clinical data were compared across subtypes.

RESULTS

Consensus clustering of gene expression data revealed 3 distinct synovial subtypes, including a high inflammatory subtype characterized by extensive infiltration of leukocytes, a low inflammatory subtype characterized by enrichment in pathways including transforming growth factor β, glycoproteins, and neuronal genes, and a mixed subtype. Machine learning applied to histologic features, with gene expression subtypes serving as labels, generated an algorithm for the scoring of histologic features. Patients with the high inflammatory synovial subtype exhibited higher levels of markers of systemic inflammation and autoantibodies. C-reactive protein (CRP) levels were significantly correlated with the severity of pain in the high inflammatory subgroup but not in the others.

CONCLUSION

Gene expression analysis of RA and OA synovial tissue revealed 3 distinct synovial subtypes. These labels were used to generate a histologic scoring algorithm in which the histologic scores were found to be associated with parameters of systemic inflammation, including the erythrocyte sedimentation rate, CRP level, and autoantibody levels. Comparison of gene expression patterns to clinical features revealed a potentially clinically important distinction: mechanisms of pain may differ in patients with different synovial subtypes.

Right drug, right patient, right time: aspiration or future promise for biologics in rheumatoid arthritis?

Individualising biologic disease-modifying anti-rheumatic drugs (bDMARDs) to maximise outcomes and deliver safe and cost-effective care is a key goal in the management of rheumatoid arthritis (RA). Investigation to identify predictive tools of bDMARD response is a highly active and prolific area of research. In addition to clinical phenotyping, cellular and molecular characterisation of synovial tissue and blood in patients with RA, using different technologies, can facilitate predictive testing. This narrative review will summarise the literature for the available bDMARD classes and focus on where progress has been made. We will also look ahead and consider the increasing use of ‘omics’ technologies, the potential they hold as well as the challenges, and what is needed in the future to fully realise our ambition of personalised bDMARD 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.

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.

Persistence of Disease-Associated Anti-Citrullinated Protein Antibody-Expressing Memory B Cells in Rheumatoid Arthritis in Clinical Remission

OBJECTIVE

In rheumatoid arthritis (RA), autoreactive B cells are pathogenic drivers and sources of anti-citrullinated protein antibodies (ACPAs) that are a diagnostic biomarker and predictor of worse long-term prognosis. Yet, the immunobiologic significance of persistent ACPA production at the cellular level is poorly understood. This study was undertaken to investigate the representation of ACPA-expressing switched-memory B cells in RA.

METHODS

In a cross-sectional study of RA patients, we investigated the presence of continued defects in immune homeostasis as a function of disease activity. Using an enzyme-linked immunosorbent assay (ELISA) and a sensitive multiplex bead-based immunoassay, we characterized fine binding antibody specificities in sera, synovial fluid (SF), and B cell culture supernatants. In this manner, we determined the frequency and epitope reactivity patterns of ACPAs produced by SF B cells and switched-memory blood B cells and compared the latter to serum ACPA levels and disease activity scores.

RESULTS

Cultured B cells from SF were shown to spontaneously secrete ACPAs, while constitutive IgG autoantibody production by peripheral blood mononuclear cells (PBMCs) was substantially less frequent. After in vitro stimulation, PBMCs secreted IgG ACPA that was overwhelmingly from switched-memory B cells, across all patient groups treated with methotrexate and/or a tumor necrosis factor inhibitor. Intriguingly, the frequencies of ACPA-expressing switched-memory B cells significantly correlated with serum IgG anti-cyclic citrullinated peptide 3 (r = 0.57, P = 0.003). Moreover, treatment-induced clinical remission had little or no effect on the circulating burden of switched-memory ACPA-expressing B cells, in part explaining the continued dysregulation of humoral immunity.

CONCLUSION

Our findings rationalize why therapeutic cessation most often results in disease reactivation and clinical flare. Hence, a clinical disease activity score is not a reliable indicator of the resolution of pathologic recirculating B cell autoimmunity.

Ectopic lymphoid neogenesis in rheumatic autoimmune diseases

Ectopic lymphoid neogenesis often occurs in the target tissues of patients with chronic rheumatic autoimmune diseases such as rheumatoid arthritis, Sjögren syndrome and other connective tissue disorders, including systemic lupus erythematosus and myositis. However, the mechanisms of ectopic lymphoid-like structure (ELS) formation and function are not entirely understood. For example, it is unclear whether ELSs indicate distinct disease phenotypes or whether they are evolutionary manifestations of chronic inflammation. Also unclear is why ELSs form in some patients but not in others. Nonetheless, ELSs frequently display functional features of ectopic germinal centres and can actively contribute to the maintenance of autoimmunity through the production of disease-specific autoantibodies; furthermore, they seem to influence disease severity and response to both synthetic and biologic DMARDs. In this Review, we discuss current knowledge and gaps in understanding of ELS formation and function including their prevalence in the above rheumatic autoimmune diseases; the mechanisms underlying their formation, maintenance and function, including positive and negative regulatory pathways; their functional relevance in the perpetuation of autoimmunity; their relationship with disease phenotypes, clinical outcomes and response to treatment; and the potential for specific targeting of ELSs through novel therapeutic modalities.

Tertiary lymphoid structures are confined to patients presenting with unifocal Langerhans Cell Histiocytosis

Langerhans cell histiocytosis (LCH) is a neoplastic myeloid disorder with a thus far poorly understood immune component. Tertiary lymphoid structures (TLS) are lymph node-like entities which create an immune-promoting microenvironment at tumor sites. We analyzed the presence and clinical relevance of TLS in n = 104 H&E-stained, therapy-naive LCH lesions of non-lymphoid origin and applied immunohistochemistry to a smaller series. Lymphoid-follicular aggregates were detected in 34/104 (33%) lesions. In line with the lymphocyte recruitment capacity of MECA-79(+) high endothelial venules (HEVs), MECA-79(+)-expressing-LCH lesions (37/77, 48%) contained the most CD3(+) T-lymphocytes (p = 0.003). TLS were identified in 8/15 lesions and contained T-and B-lymphocytes, Follicular Dendritic Cells (FDC), HEVs and the chemokines CXCL13 and CCL21 representing key cellular components and TLS-inducing factors in conventional lymph nodes (LN). Lymphoid-follicular aggregates were most frequently detected in patients presenting with unifocal LCH (24/70, 34%) as compared to patients with poly-ostotic or multi-system LCH (7/30, 23%, p = 0.03). In addition, patients with lymphoid-follicular aggregates-containing lesions had the lowest risk to develop new LCH lesions (p = 0.04). The identification of various stages of TLS formation within LCH lesions may indicate a key role for the immune system in controlling aberrant histiocytes which arise in peripheral tissues.

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h²=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

Rheumatoid arthritis patients respond differently to anti-TNF treatment. Using community-based challenge, the authors show that currently available data does not reveal meaningful genetic predictors of response to anti-TNF therapy, thus confirming clinical observations.

Effects of Rituximab and Infliximab Treatment on Carboxypeptidase B and Its Substrates in RA Synovium

Objective.

We evaluated the synovial effects of 2 potent biologic rheumatoid arthritis (RA) therapies, focusing on their effect on the expression level of carboxypeptidase B (CPB) and its substrates.

Methods.

Patients with RA receiving infliximab (IFX; n = 9) or rituximab (RTX; n = 5) had an arthroscopic synovial biopsy at baseline and 16 weeks posttherapy. Expression of CPB, C5a, osteopontin (OPN), CD3, CD20, CD55, and CD68 was assessed by immunohistochemistry and image analysis, and compared with OA synovium. RA disease activity score was assessed at multiple timepoints. Serial serum samples were analyzed for soluble CPB and C5a levels.

Results.

The baseline clinical characteristics of patients receiving IFX and RTX were similar. At the time of the second biopsy, 50% of patients had achieved a European League Against Rheumatism good or moderate response. At baseline, expression of CPB, C5a, and OPN was markedly higher in RA compared with OA synovium and correlated with mononuclear cell infiltration. There was an overall reduction in synovial expression of CPB, C5a, and OPN paralleling a reduction in mononuclear cell infiltration, but these changes were not associated with clinical response. After an early reduction in serum C5a levels, these returned to baseline levels at later timepoints.

Conclusion.

In response to IFX and RTX treatment, RA synovial expression of CPB, C5a, and OPN decrease independently of the clinical response, reflecting the complex proinflammatory and antiinflammatory effects of this pathway.

Personalized biological treatment for rheumatoid arthritis: a systematic review with a focus on clinical applicability

OBJECTIVES

To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers.

METHODS

A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. The added value was determined by the added value on prior probability for each (bio)marker. Only an increase/decrease in chance of response ⩾15% was considered clinically relevant, whereas in oncology values >25% are common.

RESULTS

Of the 57 eligible studies, 14 (bio)markers were studied in more than one cohort and an overview of the added predictive value of each marker is presented. Of the replicated predictors, none consistently showed an increase/decrease in probability of response ⩾15%. However, positivity of RF and ACPA in case of rituximab and the presence of the TNF-α promoter 308 GG genotype for TNF inhibitor therapy were consistently predictive, yet low in added predictive value. Besides these, 65 (bio)markers studied once showed remarkably high (but not validated) predictive values.

CONCLUSION

We were unable to address clinically useful baseline (bio)markers for use in individually tailored treatment. Some predictors are consistently predictive, yet low in added predictive value, while several others are promising but await replication. The challenge now is to design studies to validate all explored and promising findings individually and in combination to make these (bio)markers relevant to clinical practice.

Predictors of European League Against Rheumatism (EULAR) good response, DAS-28 remission and sustained responses to TNF-inhibitors in rheumatoid arthritis: a prospective study in refractory disease

The aim of this study was to survey factors related to EULAR good response, the DAS-28 definition of remission, ACR 50 response, sustained response to tumor necrosis factor inhibitors (TNF-I) therapy in biologic naïve patients with refractory rheumatoid arthritis. This was a single center observational clinical prospective 2 years' study, EULAR response criteria, DAS 28, HAQ and radiographic changes were recorded. Eighty patients included (64 females and 16 males, mean age was 48.4 + -17.9 years, mean disease duration 7.3 + -5.9 years). At 6 months 70% achieved EULAR good response, 51.8% achieved DAS-28 remission. Good response/sustained responses inversely correlated with baseline DAS-28 and radiographic erosions P <0.05. EULAR good response/remission by 6 months, sustained response at 2 years positively correlated with the decline in RF titers (r = 0.33, P < 0.05 & r = 0.30, P < 0.03 respectively), negatively correlated with the baseline HAQ. Regression analysis identified higher serum hemoglobin concentration, lower baseline HAQ scores, and the absence of radiographic erosions as significant predictors of good as well as sustained responses after adjustment for potential covariates. Methotrexate was associated with favorable responses and remission at 6 months (ORs = 1.13, 1.30 respectively). The study concluded that a lower baseline DAS-28 and HAQ scores, the lack of radiographic erosions favored EULAR good response and were significant predictors of sustained response to TNF-I.

Stratified medicine in inflammatory disorders: From theory to practice

Chronic inflammatory disorders are complex and characterized by significant heterogeneity in molecular, pathological, and clinical features. This heterogeneity poses challenges for the development of targeted molecular interventions for these disorders, as not all patients with a given clinical diagnosis have disease driven by a single dominant molecular pathway, hence not all patients will benefit equally from a given intervention. Biomarkers related to molecular manifestations of disease are increasingly being applied to enable stratified approaches to drug development. Biomarkers may be used to identify which patients are most likely to benefit from an intervention (predictive), identify patients at increased risk of disease progression (prognostic), and monitor biological responsiveness to an intervention (pharmacodynamic). Here we consider how biomarker-guided stratification of patients may increase benefit from targeted therapies for asthma, rheumatoid arthritis and inflammatory bowel diseases.

Moving towards personalized medicine in rheumatoid arthritis

To develop personalized medicine strategies for improvement of patient management in rheumatoid arthritis, the clinical and molecular properties of the individual patients need to be well characterized. A crucial step in this approach is to discover subgroups of patients that are characterized by a good or poor treatment outcome. Dennis and colleagues have identified distinct pretreatment gene expression profiles in affected synovial tissue specimens and a tissue type-related systemic protein pattern which are associated with a positive or negative clinical outcome to monotherapy with adalumimab (anti-TNFα) and tocilizumab (anti-IL-6 receptor). These observations assign biological pathways associated with response outcome and provide evidence for the existence of systemic, easy-to-measure predictive biomarkers for clinical benefit of these biologics.

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.

[Personalized medicine in cytokine-targeted therapy]

Personalized healthcare tries to predict the effectiveness and safety in individual therapeutic approaches by defining individual patient characteristics (biomarkers), while stratification uses diagnostic patterns for groups of patients for prediction of therapeutic response with less adverse reactions caused by the drugs applied. Both methods are implemented in oncology and infectiology and in the therapy of rheumatological diseases there is a need for both. Cytokine-directed therapies are important for the treatment of rheumatological diseases, especially when therapy with conventional disease-modifying antirheumatic drugs (DMARD) has failed. Despite the high potency of these drugs for inhibiting pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), interleukin 1 (IL-1) and IL-6, sufficient responses are only seen in some of the patients. Therefore, stratification and personalized medicine are ways to optimize efficacy and tolerability of biologic therapies. Some initial evidence is available for potential future strategies using molecular and genetic markers for stratified cytokine inhibition.