Transforming clinical trials in rheumatology: towards patient-centric precision medicine

Towards understanding the role of nanomedicine in targeting TNFR2 in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation of the synovium and progressive joint destruction which significantly affects both quality of life and socioeconomic status. Admittedly, various treatments are available, but they are usually accompanied by various side effects, from mild to severe, and potentially with adverse events. Tumour necrosis factor-alpha (TNF-α) plays a crucial role in the pathophysiology of RA. It promotes inflammatory, apoptosis and necroptosis via TNF receptor-1 (TNFR1) but elicit anti-inflammatory effects via TNFR2. Herein, targeting TNFR2 has gained attention in RA studies. Understanding the role of nanomedicine in modulating TNFR2 signalling may be the instrument in development of RA therapies. Nanotechnology has made a significant progress in treating various conditions of diseases since its inception. Due to this, nanomedicine has emerged as a promising therapeutics approach for RA. Recent studies have demonstrated the potential of nanomedicine in RA theranostics, combining therapy and diagnostics for improved treatment outcomes. Owing to the challenges and advancements in the field of nanotechnology, nanoparticles are seen as an applicable candidate in the treatment of RA. In this review, we provide an overview of the role of nanomedicine in targeting TNFR2 for the treatment of RA and highlight the limitations of current therapies as well as the potential of nanocarriers with controlled drug release and active targeting abilities.

Biologics or Janus Kinase Inhibitors in Rheumatoid Arthritis Patients Who are Insufficient Responders to Conventional Anti-Rheumatic Drugs

Rheumatoid arthritis (RA) is a chronic immune-mediated inflammatory disease which can induce progressive disability if not properly treated early. Over the last 20 years, the improvement of knowledge on the pathogenesis of the disease has made available several drugs targeting key elements of the pathogenetic process, which now represent the preferred treatment option after the failure of first-line therapy with conventional drugs such as methotrexate (MTX). To this category of targeted drugs belong anti-cytokine or cell-targeted biological agents and more recently also Janus kinase inhibitors (JAKis). In the absence to date of specific biomarkers to guide the therapeutic choice in the context of true precision medicine, the choice of the first targeted drug after MTX failure is guided by treatment cost (especially after the marketing of biosimilar products) and by the clinical characteristics of the patient (age, sex, comorbidities and compliance) and the disease (presence or absence of autoantibodies and systemic or extra-articular manifestations), which may influence the efficacy and safety profile of the available products. This viewpoint focuses on the decision-making process underlying the personalized approach to RA therapy and will analyse the evidence in the literature supporting the choice of individual products and in particular the differential choice between biological drugs and JAKis.

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

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

FUNDING

None.

Hurdles in new drug development in rheumatic diseases

INTRODUCTION

Rheumatic diseases are heterogenous conditions with multifactorial underlying physiologic pathogeneses. Despite recent progress in the identification and development of advanced therapies primarily focusing on disrupting the immunological abnormalities that cause these conditions, rheumatic disease management remains challenging in a notable proportion of patients, with many exhibiting uncontrolled or refractory disease activity. New and improved therapies are needed to respond to this treatment gap. However, there are important hurdles that can affect the expedited identification and assessment of new treatments.

METHODS

We present a review of key hurdles in the development of antirheumatic agents, as well as possible solutions to these obstacles.

RESULTS

We highlight the challenges presented by incomplete understanding of the complexity of rheumatic disease pathophysiology and the resultant difficulties in the identification, development, and evaluation of new therapies. We further explore the diversity of the underlying disease processes leading to heterogeneity in patient response to treatment, necessitating the re-design of clinical trials of antirheumatic agents to detect efficacy signals and better inform clinical disease management. Finally, emergent strategies and methodologies with potential to improve upon these hurdles are presented.

CONCLUSION

New and modified study designs and research tools that leverage ongoing advancements in the elucidation of rheumatic disease pathogenesis coupled with progress in methods to mine available data will be instrumental in overcoming current hurdles in antirheumatic drug development.

Molecular maps of synovial cells in inflammatory arthritis using an optimized synovial tissue dissociation protocol

In this study, we optimized the dissociation of synovial tissue biopsies for single-cell omics studies and created a single-cell atlas of human synovium in inflammatory arthritis. The optimized protocol allowed consistent isolation of highly viable cells from tiny fresh synovial biopsies, minimizing the synovial biopsy drop-out rate. The synovium scRNA-seq atlas contained over 100,000 unsorted synovial cells from 25 synovial tissues affected by inflammatory arthritis, including 16 structural, 11 lymphoid, and 15 myeloid cell clusters. This synovial cell map expanded the diversity of synovial cell types/states, detected synovial neutrophils, and broadened synovial endothelial cell classification. We revealed tissue-resident macrophage subsets with proposed matrix-sensing (FOLR2+COLEC12high) and iron-recycling (LYVE1+SLC40A1+) activities and identified fibroblast subsets with proposed functions in cartilage breakdown (SOD2highSAA1+SAA2+SDC4+) and extracellular matrix remodeling (SERPINE1+COL5A3+LOXL2+). Our study offers an efficient synovium dissociation method and a reference scRNA-seq resource, that advances the current understanding of synovial cell heterogeneity in inflammatory arthritis.

Unveiling innovative therapeutic strategies and future trajectories on stimuli-responsive drug delivery systems for targeted treatment of breast carcinoma

This comprehensive review delineates the latest advancements in stimuli-responsive drug delivery systems engineered for the targeted treatment of breast carcinoma. The manuscript commences by introducing mammary carcinoma and the current therapeutic methodologies, underscoring the urgency for innovative therapeutic strategies. Subsequently, it elucidates the logic behind the employment of stimuli-responsive drug delivery systems, which promise targeted drug administration and the minimization of adverse reactions. The review proffers an in-depth analysis of diverse types of stimuli-responsive systems, including thermoresponsive, pH-responsive, and enzyme-responsive nanocarriers. The paramount importance of material choice, biocompatibility, and drug loading strategies in the design of these systems is accentuated. The review explores characterization methodologies for stimuli-responsive nanocarriers and probes preclinical evaluations of their efficacy, toxicity, pharmacokinetics, and biodistribution in mammary carcinoma models. Clinical applications of stimuli-responsive systems, ongoing clinical trials, the potential of combination therapies, and the utility of multifunctional nanocarriers for the co-delivery of assorted drugs and therapies are also discussed. The manuscript addresses the persistent challenge of drug resistance in mammary carcinoma and the potential of stimuli-responsive systems in surmounting it. Regulatory and safety considerations, including FDA guidelines and biocompatibility assessments, are outlined. The review concludes by spotlighting future trajectories and emergent technologies in stimuli-responsive drug delivery, focusing on pioneering approaches, advancements in nanotechnology, and personalized medicine considerations. This review aims to serve as a valuable compendium for researchers and clinicians interested in the development of efficacious and safe stimuli-responsive drug delivery systems for the treatment of breast carcinoma.

The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis

Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8 + GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.

Molecular portrait of chronic joint diseases: Defining endotypes toward personalized medicine

Joint diseases affect hundreds of millions of people worldwide, and their prevalence is constantly increasing. To date, despite recent advances in the development of therapeutic options for most rheumatic conditions, a significant proportion of patients still lack efficient disease management, considerably impacting their quality of life. Through the spectrum of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and osteoarthritis (OA) as quintessential and common rheumatic diseases, this review first provides an overview of their epidemiological and clinical features before exploring how the better definition of clinical phenotypes has helped their clinical management. It then discusses the recent progress in understanding the diversity of endotypes underlying disease phenotypes. Finally, this review highlights the current challenges of implementing molecular endotypes towards the personalized management of RA, PsA and OA patients in the future.

Seven-chain adaptive immune receptor repertoire analysis in rheumatoid arthritis reveals novel features associated with disease and clinically relevant phenotypes

BACKGROUND

In rheumatoid arthritis (RA), the activation of T and B cell clones specific for self-antigens leads to the chronic inflammation of the synovium. Here, we perform an in-depth quantitative analysis of the seven chains that comprise the adaptive immune receptor repertoire (AIRR) in RA.

RESULTS

In comparison to controls, we show that RA patients have multiple and strong differences in the B cell receptor repertoire including reduced diversity as well as altered isotype, chain, and segment frequencies. We demonstrate that therapeutic tumor necrosis factor inhibition partially restores this alteration but find a profound difference in the underlying biochemical reactivities between responders and non-responders. Combining the AIRR with HLA typing, we identify the specific T cell receptor repertoire associated with disease risk variants. Integrating these features, we further develop a molecular classifier that shows the utility of the AIRR as a diagnostic tool.

CONCLUSIONS

Simultaneous sequencing of the seven chains of the human AIRR reveals novel features associated with the disease and clinically relevant phenotypes, including response to therapy. These findings show the unique potential of AIRR to address precision medicine in immune-related diseases.

Patterns and determinants of response to novel therapies in juvenile and adult-onset polyarthritis

Biologic and targeted synthetic DMARDs (b/tsDMARDs) have revolutionized the management of multiple rheumatic inflammatory conditions. Among these, polyarticular JIA (pJIA) and RA display similarities in terms of disease pathophysiology and response pattern to b/tsDMARDs. Indeed, the therapeutic efficacy of novel targeted drugs is variable among individual patients, in both RA and pJIA. The mechanisms and determinants of this heterogeneous response are diverse and complex, such that the development of true 'precision'-medicine strategies has proven highly challenging. In this review, we will discuss pathophysiological, patient-specific, drug-specific and environmental factors contributing to individual therapeutic response in pJIA in comparison with what is known in RA. Although some biomarkers have been identified that stratify with respect to the likelihood of either therapeutic response or non-response, few have proved useful in clinical practice so far, likely due to the complexity of treatment-response mechanisms. Consequently, we propose a pragmatic, patient-centred and clinically based approach, i.e. personalized instead of biomarker-based precision medicine in JIA.

Predicting best treatment in rheumatoid arthritis

BACKGROUND

Although targeted biological treatments have transformed the outlook for patients with rheumatoid arthritis (RA), 40% of patients show poor clinical response, and there is an imperative to unravel the molecular pathways and mechanisms underlying non-response and disease progression. 5-20% of RA individuals do not respond to all current medications including biologic and targeted therapies, which suggests that distinct pathogenic processes underlie multi-drug refractoriness.

OBJECTIVES

In this brief review we discuss advances from recent studies in precision medicine in rheumatoid arthritis.

METHODS

Bulk RNA-Sequencing of synovial biopsies from RA individuals combined with histology and deep clinical phenotyping has revealed substantial insights into divergent pathogenic pathways which lead to disease progression and illuminated mechanisms underlying failure to response to specific treatments. Biopsy-driven randomised controlled trials, such as R4RA and the forthcoming STRAP trial, have enabled the development of machine learning predictive models for predicting response to different therapies.

RESULTS

In the Pathobiology of Early Arthritis Cohort (PEAC), gene expression analysis showed that individuals could be classified into three gene expression subgroups which correlated with histopathotypes defined by histological markers: pauci-immune fibroid pathotype characterised by fibroblasts and an absence of immune inflammatory cells; diffuse-myeloid pathotype characterised by macrophage influx; and the lympho-myeloid pathotype delineated by the presence of B cells, but typically containing a complex inflammatory infiltrate with ectopic lymphoid structure formation. In the R4RA biopsy-driven randomised controlled trial, patients were randomised to either rituximab or tocilizumab. Comprehensive analysis of synovial biopsies pre/post-treatment identified gene signatures of response associated with pathogenic pathways which could be tracked over time. A group of true refractory patients were identified who had failed anti-TNF prior to the study (it was an entry criterion) and then subsequently failed both trial biologics during the trial. RNA-Seq analysis and digital spatial profiling identified specific cell types including DKK3+ fibroblasts as being associated with the refractory state. We identified machine learning predictive models based on specific gene signatures which were able to predict future response to therapy as well as the refractory state.

CONCLUSIONS

RNA-sequencing of synovial biopsies has enabled substantial progress in understanding disease endotypes in RA and identifying synovial gene signatures which predict prognosis and future response to treatment.

Immune and molecular landscape behind non-response to Mycophenolate Mofetil and Azathioprine in lupus nephritis therapy

Lupus nephritis (LN) represents one of the most severe complications of systemic lupus erythematosus, leading to end-stage kidney disease in worst cases. Current first-line therapies for LN, including mycophenolate mofetil (MMF) and azathioprine (AZA), fail to induce long-term remission in 60-70% of the patients, evidencing the urgent need to delve into the molecular knowledge-gap behind the non-response to these therapies. A longitudinal cohort of treated LN patients including clinical, cellular and transcriptomic data, was analyzed. Gene-expression signatures behind non-response to different drugs were revealed by differential expression analysis. Drug-specific non-response mechanisms and cell proportion differences were identified. Blood cell subsets mediating non-response were described using single-cell RNASeq data. We show that AZA and MMF non-response implicates different cells and regulatory functions. Mechanistic models were used to suggest add-on therapies to improve their current performance. Our results provide new insights into the molecular mechanisms associated with treatment failures in LN.

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

Background

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

Methods

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

Results

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

Conclusion

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

Disease activity drives transcriptomic heterogeneity in early untreated rheumatoid synovitis

OBJECTIVES

Transcriptomic profiling of synovial tissue from patients with early, untreated rheumatoid arthritis (RA) was used to explore the ability of unbiased, data-driven approaches to define clinically relevant subgroups.

METHODS

RNASeq was performed on 74 samples, with disease activity data collected at inclusion. Principal components analysis (PCA) and unsupervised clustering were used to define patient clusters based on expression of the most variable genes, followed by pathway analysis and inference of relative abundance of immune cell subsets. Histological assessment and multiplex immunofluorescence (for CD45, CD68, CD206) were performed on paraffin sections.

RESULTS

PCA on expression of the (n=894) most variable genes across this series did not divide samples into distinct groups, instead yielding a continuum correlated with baseline disease activity. Two patient clusters (PtC1, n=52; PtC2, n=22) were defined based on expression of these genes. PtC1, with significantly higher disease activity and probability of response to methotrexate therapy, showed upregulation of immune system genes; PtC2 showed upregulation of lipid metabolism genes, described to characterise tissue resident or M2-like macrophages. In keeping with these data, M2-like:M1-like macrophage ratios were inversely correlated with disease activity scores and were associated with lower synovial immune infiltration and the presence of thinner, M2-like macrophage-rich synovial lining layers.

CONCLUSION

In this large series of early, untreated RA, we show that the synovial transcriptome closely mirrors clinical disease activity and correlates with synovial inflammation. Intriguingly, lower inflammation and disease activity are associated with higher ratios of M2:M1 macrophages, particularly striking in the synovial lining layer. This may point to a protective role for tissue resident macrophages in RA.

A Targeted Exosome Therapeutic Confers Both CfDNA Scavenging and Macrophage Polarization for Ameliorating Rheumatoid Arthritis

Only a minority of rheumatoid arthritis (RA) patients achieve disease remission, so the exploration of additional pathogenic factors and the development of new therapeutics are needed. Here, strong correlations among the cell-free DNA (cfDNA) level and the inflammatory response in clinical synovial fluid samples and RA disease activity are discovered. The important role of cfDNA in disease development in a collagen-induced arthritis (CIA) murine model is also demonstrated. Building on these findings, a novel therapeutic based on anti-inflammatory (M2) macrophage-derived exosomes as chassis, that are modified with both oligolysine and matrix metalloproteinase (MMP)-cleavable polyethylene glycol (PEG) on the membrane, is developed. After intravenous injection, PEG-enabled prolonged circulation and C─C motif chemokine ligand-directed accumulation together result in enrichment at inflamed joints. Following subsequent MMP cleavage, the positively charged oligolysine is exposed for cfDNA scavenging, while exosomes induce M2 polarization. By using a classical CIA murine model and a newly established CIA canine model, it is demonstrated that the rationally designed exosome therapeutic substantially suppresses inflammation in joints and provides strong chondroprotection and osteoprotection, revealing its potential for effective CIA amelioration.

Stratification of biological therapies by pathobiology in biologic-naive patients with rheumatoid arthritis (STRAP and STRAP-EU): two parallel, open-label, biopsy-driven, randomised trials

BACKGROUND

Despite highly effective targeted therapies for rheumatoid arthritis, about 40% of patients respond poorly, and predictive biomarkers for treatment choices are lacking. We did a biopsy-driven trial to compare the response to rituximab, etanercept, and tocilizumab in biologic-naive patients with rheumatoid arthritis stratified for synovial B cell status.

METHODS

STRAP and STRAP-EU were two parallel, open-label, biopsy-driven, stratified, randomised, phase 3 trials done across 26 university centres in the UK and Europe. Biologic-naive patients aged 18 years or older with rheumatoid arthritis based on American College of Rheumatology (ACR)-European League Against Rheumatism classification criteria and an inadequate response to conventional synthetic disease-modifying antirheumatic drugs (DMARDs) were included. Following ultrasound-guided synovial biopsy, patients were classified as B cell poor or B cell rich according to synovial B cell signatures and randomly assigned (1:1:1) to intravenous rituximab (1000 mg at week 0 and week 2), subcutaneous tocilizumab (162 mg per week), or subcutaneous etanercept (50 mg per week). The primary outcome was the 16-week ACR20 response in the B cell-poor, intention-to-treat population (defined as all randomly assigned patients), with data pooled from the two trials, comparing etanercept and tocilizumab (grouped) versus rituximab. Safety was assessed in all patients who received at least one dose of study drug. These trials are registered with the EU Clinical Trials Register, 2014-003529-16 (STRAP) and 2017-004079-30 (STRAP-EU).

FINDINGS

Between June 8, 2015, and July 4, 2019, 226 patients were randomly assigned to etanercept (n=73), tocilizumab (n=74), and rituximab (n=79). Three patients (one in each group) were excluded after randomisation because they received parenteral steroids in the 4 weeks before recruitment. 168 (75%) of 223 patients in the intention-to-treat population were women and 170 (76%) were White. In the B cell-poor population, ACR20 response at 16 weeks (primary endpoint) showed no significant differences between etanercept and tocilizumab grouped together and rituximab (46 [60%] of 77 patients vs 26 [59%] of 44; odds ratio 1·02 [95% CI 0·47-2·17], p=0·97). No differences were observed for adverse events, including serious adverse events, which occurred in six (6%) of 102 patients in the rituximab group, nine (6%) of 108 patients in the etanercept group, and three (4%) of 73 patients in the tocilizumab group (p=0·53).

INTERPRETATION

In this biologic-naive population of patients with rheumatoid arthrtitis, the dichotomic classification into synovial B cell poor versus rich did not predict treatment response to B cell depletion with rituximab compared with alternative treatment strategies. However, the lack of response to rituximab in patients with a pauci-immune pathotype and the higher risk of structural damage progression in B cell-rich patients treated with rituximab warrant further investigations into the ability of synovial tissue analyses to inform disease pathogenesis and treatment response.

FUNDING

UK Medical Research Council and Versus Arthritis.

Bayesian sample size determination in basket trials borrowing information between subsets

Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach to sample size determination in basket trials that permit borrowing of information between commensurate subsets. Specifically, we consider a randomized basket trial design where patients are randomly assigned to the new treatment or control within each trial subset ("subtrial" for short). Closed-form sample size formulae are derived to ensure that each subtrial has a specified chance of correctly deciding whether the new treatment is superior to or not better than the control by some clinically relevant difference. Given prespecified levels of pairwise (in)commensurability, the subtrial sample sizes are solved simultaneously. The proposed Bayesian approach resembles the frequentist formulation of the problem in yielding comparable sample sizes for circumstances of no borrowing. When borrowing is enabled between commensurate subtrials, a considerably smaller trial sample size is required compared to the widely implemented approach of no borrowing. We illustrate the use of our sample size formulae with two examples based on real basket trials. A comprehensive simulation study further shows that the proposed methodology can maintain the true positive and false positive rates at desired levels.

Treatable Traits in Systemic Sclerosis

Systemic sclerosis (SSc) is a chronic systemic disease within the spectrum of connective tissue diseases, specifically characterized by vascular abnormalities and inflammatory and fibrotic involvement of the skin and internal organs resulting in high morbidity and mortality. The clinical phenotype of SSc is heterogeneous, and serum autoantibodies together with the extent of skin involvement have a predictive value in the risk stratification. Current recommendations include an organ-based management according to the predominant involvement with only limited individual factors included in the treatment algorithm. Similar to what has been proposed for other chronic diseases, we hypothesize that a "treatable trait" approach based on relevant phenotypes and endotypes could address the unmet needs in SSc stratification and treatment to maximize the outcomes. We provide herein a comprehensive review and a critical discussion of the literature regarding potential treatable traits in SSc, focusing on established and candidate biomarkers, with the purpose of setting the bases for a precision medicine-based approach. The discussion, structured based on the organ involvement, allows to conjugate the pathogenetic mechanisms of tissue injury with the proposed predictors, particularly autoantibodies and other serum biomarkers. Ultimately, we are convinced that precision medicine is the ideal guide to manage a complex condition such as SSc for which available treatments are largely unsatisfactory.

Imaging in inflammatory arthritis: progress towards precision medicine

Imaging techniques such as ultrasonography and MRI have gained ground in the diagnosis and management of inflammatory arthritis, as these imaging modalities allow a sensitive assessment of musculoskeletal inflammation and damage. However, these techniques cannot discriminate between disease subsets and are currently unable to deliver an accurate prediction of disease progression and therapeutic response in individual patients. This major shortcoming of today's technology hinders a targeted and personalized patient management approach. Technological advances in the areas of high-resolution imaging (for example, high-resolution peripheral quantitative computed tomography and ultra-high field MRI), functional and molecular-based imaging (such as chemical exchange saturation transfer MRI, positron emission tomography, fluorescence optical imaging, optoacoustic imaging and contrast-enhanced ultrasonography) and artificial intelligence-based data analysis could help to tackle these challenges. These new imaging approaches offer detailed anatomical delineation and an in vivo and non-invasive evaluation of the immunometabolic status of inflammatory reactions, thereby facilitating an in-depth characterization of inflammation. By means of these developments, the aim of earlier diagnosis, enhanced monitoring and, ultimately, a personalized treatment strategy looms closer.

Inflammation across tissues: can shared cell biology help design smarter trials?

Immune-mediated inflammatory diseases (IMIDs) are responsible for substantial global disease burden and associated health-care costs. Traditional models of research and service delivery silo their management within organ-based medical disciplines. Very often patients with disease in one organ have comorbid involvement in another, suggesting shared pathogenic pathways. Moreover, different IMIDs are often treated with the same drugs (including glucocorticoids, immunoregulators and biologics). Unlocking the cellular basis of these diseases remains a major challenge, leading us to ask why, if these diseases have so much in common, they are not investigated in a common manner. A tissue-based, cellular understanding of inflammation might pave the way for cross-disease, cross-discipline basket trials (testing one drug across two or more diseases) to reduce the risk of failure of early-phase drug development in IMIDs. This new approach will enable rapid assessment of the efficacy of new therapeutic agents in cross-disease translational research in humans.

Synovial biopsies for molecular definition of rheumatoid arthritis and treatment response phenotyping: where can we improve?

INTRODUCTION

The extensive knowledge gained in the cellular and molecular mechanisms underlying Rheumatoid Arthritis (RA) pathogenesis has led to therapeutic advances. However, up to 10-20% of patients fail to respond to multiple therapeutic agents being classified as multi-drugresistant. A key challenge moving forward will be the implementation of synovial biopsies in clinical practice to facilitate the shift from the current trial-and-error strategy toward new forms of clinical trials. Biomarker-driven trials have the potential to improve drug selection and patient stratification, reduce economic costs and unnecessary drug-related toxicity.

AREAS COVERED

This special report explores the clinical and research applications of synovial biopsy, the advancement in the molecular pathobiology of RA to better understand disease pathogenesis and treatment response, and the way forward for the paradigm shift needed.

EXPERT OPINION

In the current era of highly targeted biologic drugs which have dramatically transformed the outlook of RA patients, the use of synovial biopsy represents a valuable practical tool to dissect disease pathogenesis and, consequently, treatment response. In the near future, it is hoped that technological advances will allow for speeding up synovial molecular analysis and that the design of new biomarker-driven trials will enable the allocation of patients to more effective treatment.

Precision medicine in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease that has diverse clinical manifestations, ranging from restricted cutaneous involvement to life-threatening systemic organ involvement. The heterogeneity of pathomechanisms that lead to SLE contributes to between-patient variation in clinical phenotype and treatment response. Ongoing efforts to dissect cellular and molecular heterogeneity in SLE could facilitate the future development of stratified treatment recommendations and precision medicine, which is a considerable challenge for SLE. In particular, some genes involved in the clinical heterogeneity of SLE and some phenotype-related loci (STAT4, IRF5, PDGF genes, HAS2, ITGAM and SLC5A11) have an association with clinical features of the disease. An important part is also played by epigenetic varation (in DNA methylation, histone modifications and microRNAs) that influences gene expression and affects cell function without modifying the genome sequence. Immune profiling can help to identify an individual's specific response to a therapy and can potentially predict outcomes, using techniques such as flow cytometry, mass cytometry, transcriptomics, microarray analysis and single-cell RNA sequencing. Furthermore, the identification of novel serum and urinary biomarkers would enable the stratification of patients according to predictions of long-term outcomes and assessments of potential response to therapy.

The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a CD8+ GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.

Towards molecular-pathology informed clinical trials in childhood arthritis to achieve precision medicine in juvenile idiopathic arthritis

In childhood arthritis, collectively known as Juvenile idiopathic arthritis (JIA), the rapid rise of available licensed biological and targeted small molecule treatments in recent years has led to improved outcomes. However, real-world data from multiple countries and registries show that despite a large number of available drugs, many children and young people continue to suffer flares and experience significant periods of time with active disease for many years. More than 50% of young people with JIA require ongoing immune suppression well into adult life, and they may have to try multiple different treatments in that time. There are currently no validated tools with which to select specific treatments, nor biomarkers of response to assist in such choices, therefore, current management uses essentially a trial-and-error approach. A further consequence of recent progress is a reducing pool of available children or young people who are eligible for new trials. In this review we consider how progress towards a molecular based approach to defining treatment targets and informing trial design in JIA, combined with novel approaches to clinical trials, could provide strategies to maximise discovery and progress, in order to move towards precision medicine for children with arthritis.

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

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

From Bench to Bedside in Rheumatoid Arthritis from the "2022 GISEA International Symposium"

While precision medicine is still a challenge in rheumatic disease, in recent years many advances have been made regarding pathogenesis, the treatment of inflammatory arthropathies, and their interaction. New insight into the role of inflammasome and synovial tissue macrophage subsets as predictors of drug response give hope for future tailored therapeutic strategies and a personalized medicine approach in inflammatory arthropathies. Here, we discuss the main pathogenetic mechanisms and therapeutic approaches towards precision medicine in rheumatoid arthritis from the 2022 International GISEA/OEG Symposium.

Precision medicine: the precision gap in rheumatic disease

For many oncological conditions, the application of timely and patient-tailored targeted therapies, or precision medicine, is a major therapeutic development that has provided considerable clinical benefit. However, despite the application of increasingly sophisticated technologies, alongside advanced bioinformatic and machine-learning algorithms, this success is yet to be replicated for the rheumatic diseases. In rheumatoid arthritis, for example, despite an array of targeted biologic and conventional therapeutics, treatment choice remains largely based on trial and error. The concept of the 'precision gap' for rheumatic disease can help us to identify factors that underpin the slow progress towards the discovery and adoption of precision-medicine approaches for rheumatic disease. In a rheumatic disease such as rheumatoid arthritis, it is possible to identify four themes that have slowed progress, solutions to which should help to close the precision gap. These themes relate to our fundamental understanding of disease pathogenesis, how we determine treatment response, confounders of treatment outcomes and trial design.

Design and analysis of umbrella trials: Where do we stand?

Background

The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting. Despite the existence of several reviews of master protocols, the statistical considerations of umbrella trials have received more limited attention.

Methods

We conduct a systematic review of the literature on umbrella trials, examining both the statistical methods that are available for their design and analysis, and also their use in practice. We pay particular attention to considerations for umbrella designs applied outside of oncology.

Findings

We identified 38 umbrella trials. To date, most umbrella trials have been conducted in early phase settings (73.7%, 28/38) and in oncology (92.1%, 35/38). The quality of statistical information available about conducted umbrella trials to date is poor; for example, it was impossible to ascertain how sample size was determined in the majority of trials (55.3%, 21/38). The literature on statistical methods for umbrella trials is currently sparse.

Conclusions

Umbrella trials have potentially great utility to expedite drug development, including outside of oncology. However, to enable lessons to be effectively learned from early use of such designs, there is a need for higher-quality reporting of umbrella trials. Furthermore, if the potential of umbrella trials is to be realized, further methodological research is required.

Efficacy of Abatacept Versus Tumor Necrosis Factor Inhibitors in Anti-citrullinated Protein Antibody-Positive Patients with Rheumatoid Arthritis: Results from a Korean Nationwide Biologics Registry

INTRODUCTION

To compare the efficacy of abatacept and tumor necrosis factor inhibitor (TNFi) in patients with anti-citrullinated protein antibody (ACPA)-positive rheumatoid arthritis (RA) and identify those who benefit most from abatacept over TNFi.

METHODS

This observational study identified RA patients who were ACPA-positive and initiated abatacept or TNFi from the Korean College of Rheumatology Biologics and Targeted therapy registry. Propensity score (PS) matching was performed to balance baseline confounding in abatacept- or TNFi-treated patients. The major endpoints were changes in Clinical Disease Activity Index (CDAI) and achievement of CDAI remission/low disease activity after 1 year of treatment. Subgroup analysis was mainly performed stratified by prior biologics use.

RESULTS

A total of 291 PS-matched, ACPA-positive RA patients who initiated abatacept (n = 97) and TNFi (n = 194) were included. From baseline CDAI scores of 26.52 in the abatacept group and 26.38 in the TNFi group, the mean changes after 1 year were - 16.78 and - 13.61, respectively (difference - 3.17, p = 0.020). The proportion of patients achieving CDAI remission/low disease activity was 68.0% with abatacept and 52.6% with TNFi (p = 0.013). In the subgroup analysis, patients that were biologics-naïve had better improvement in CDAI after treatment with abatacept than TNFi (difference - 3.35, p = 0.021).

CONCLUSIONS

This real-world study suggests that abatacept may have better clinical response compared to TNFi in patients with established ACPA-positive RA, especially in those that were biologics-naïve.

The promise of precision medicine in rheumatology

Systemic autoimmune rheumatic diseases (SARDs) exhibit extensive heterogeneity in clinical presentation, disease course, and treatment response. Therefore, precision medicine - whereby treatment is tailored according to the underlying pathogenic mechanisms of an individual patient at a specific time - represents the 'holy grail' in SARD clinical care. Current strategies include treat-to-target therapies and autoantibody testing for patient stratification; however, these are far from optimal. Recent innovations in high-throughput 'omic' technologies are now enabling comprehensive profiling at multiple levels, helping to identify subgroups of patients who may taper off potentially toxic medications or better respond to current molecular targeted therapies. Such advances may help to optimize outcomes and identify new pathways for treatment, but there are many challenges along the path towards clinical translation. In this Review, we discuss recent efforts to dissect cellular and molecular heterogeneity across multiple SARDs and future directions for implementing stratification approaches for SARD treatment in the clinic.

Traction of 3D and 4D Printing in the Healthcare Industry: From Drug Delivery and Analysis to Regenerative Medicine

Three-dimensional (3D) printing and 3D bioprinting are promising technologies for a broad range of healthcare applications from frontier regenerative medicine and tissue engineering therapies to pharmaceutical advancements yet must overcome the challenges of biocompatibility and resolution. Through comparison of traditional biofabrication methods with 3D (bio)printing, this review highlights the promise of 3D printing for the production of on-demand, personalized, and complex products that enhance the accessibility, effectiveness, and safety of drug therapies and delivery systems. In addition, this review describes the capacity of 3D bioprinting to fabricate patient-specific tissues and living cell systems (e.g., vascular networks, organs, muscles, and skeletal systems) as well as its applications in the delivery of cells and genes, microfluidics, and organ-on-chip constructs. This review summarizes how tailoring selected parameters (i.e., accurately selecting the appropriate printing method, materials, and printing parameters based on the desired application and behavior) can better facilitate the development of optimized 3D-printed products and how dynamic 4D-printed strategies (printing materials designed to change with time or stimulus) may be deployed to overcome many of the inherent limitations of conventional 3D-printed technologies. Comprehensive insights into a critical perspective of the future of 4D bioprinting, crucial requirements for 4D printing including the programmability of a material, multimaterial printing methods, and precise designs for meticulous transformations or even clinical applications are also given.

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

Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5-20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established. Here, in-depth histological/molecular analyses of R4RA synovial biopsies identify humoral immune response gene signatures associated with response to rituximab and tocilizumab, and a stromal/fibroblast signature in patients refractory to all medications. Post-treatment changes in synovial gene expression and cell infiltration highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms. Using ten-by-tenfold nested cross-validation, we developed machine learning algorithms predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68) and, notably, multidrug resistance (AUC = 0.69). This study supports the notion that disease endotypes, driven by diverse molecular pathology pathways in the diseased tissue, determine diverse clinical and treatment-response phenotypes. It also highlights the importance of integration of molecular pathology signatures into clinical algorithms to optimize the future use of existing medications and inform the development of new drugs for refractory patients.

Longitudinal analysis of blood DNA methylation identifies mechanisms of response to tumor necrosis factor inhibitor therapy in rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a chronic, immune-mediated inflammatory disease of the joints that has been associated with variation in the peripheral blood methylome. In this study, we aim to identify epigenetic variation that is associated with the response to tumor necrosis factor inhibitor (TNFi) therapy.

Methods

Peripheral blood genome-wide DNA methylation profiles were analyzed in a discovery cohort of 62 RA patients at baseline and at week 12 of TNFi therapy. DNA methylation of individual CpG sites and enrichment of biological pathways were evaluated for their association with drug response. Using a novel cell deconvolution approach, altered DNA methylation associated with TNFi response was also tested in the six main immune cell types in blood. Validation of the results was performed in an independent longitudinal cohort of 60 RA patients.

Findings

Treatment with TNFi was associated with significant longitudinal peripheral blood methylation changes in biological pathways related to RA (FDR<0.05). 139 biological functions were modified by therapy, with methylation levels changing systematically towards a signature similar to that of healthy controls. Differences in the methylation profile of T cell activation and differentiation, GTPase-mediated signaling, and actin filament organization pathways were associated with the clinical response to therapy. Cell type deconvolution analysis identified CpG sites in CD4+T, NK, neutrophils and monocytes that were significantly associated with the response to TNFi.

Interpretation

Our results show that treatment with TNFi restores homeostatic blood methylation in RA. The clinical response to TNFi is associated to methylation variation in specific biological pathways, and it involves cells from both the innate and adaptive immune systems.

Funding

The Instituto de Salud Carlos III.

Responding to and Driving Change in Rheumatology: Report from the 12th International Immunology Summit 2021

The coronavirus disease 2019 (COVID-19) pandemic has accelerated changes to rheumatology daily clinical practice. The main goal of the 12th International Immunology Summit, held 25-26 June, 2021 (virtual meeting), was to provide direction for these active changes rather than undergoing change reactively in order to improve patient outcomes. This review describes and explores the concept of change in rheumatology clinical practice based on presentations from the Immunology Summit. Many of the changes to rheumatology practice brought about by the COVID-19 pandemic may be considered as having a positive impact on disease management and may help with the long-term development of more patient-focused treatment. Rheumatologists can contribute key knowledge regarding the use of immunosuppressive agents in the context of the pandemic, and according to the European League Against Rheumatism, they should be involved in any multidisciplinary COVID-19 guideline committees. New technologies, including telemedicine and artificial intelligence, represent an opportunity for physicians to individualise patient treatment and improve disease management. Despite major advances in the treatment of rheumatic diseases, the efficacy of available disease-modifying anti-rheumatic drugs (DMARDs) remains suboptimal and data regarding serological biomarkers are limited. Synovial tissue biomarkers, such as CD68+ macrophages, have shown promise in elucidating pathogenesis and targeting treatment to the individual patient. In spondyloarthritis (SpA) or psoriatic arthritis (PsA), information regarding the effectiveness of the available agents with different mechanisms of action may be integrated to manage patients using a treat-to-target approach. Early diagnosis of SpA and PsA is important for optimisation of treatment response and long-term outcomes. Improving our understanding of disease pathogenesis and practice methods may help reduce diagnostic delays, thereby optimising disease outcomes in patients with rheumatic diseases.

Overcoming barriers for intra-articular delivery of disease-modifying osteoarthritis drugs

Despite four decades of research in intra-articular drug delivery systems (DDS) and two decades of advances in disease-modifying osteoarthritis drugs (DMOADs), there is still no clinically available disease-modifying therapy for osteoarthritis (OA). Multiple barriers compromise intra-articular DMOAD delivery. Although multiple exciting approaches have been developed to overcome these barriers, there are still outstanding questions. We make several recommendations that can help in fully overcoming these barriers. Considering OA heterogeneity, we also propose a patient-centered, bottom-up workflow to guide preclinical development of DDS-based intra-articular DMOAD therapies. Overall, we expect this review to inspire paradigm-shifting innovations for developing next-generation DDS that can enable clinical translation of intra-articular DMOADs.

Single Cell RNA Sequencing in Autoimmune Inflammatory Rheumatic Diseases: Current Applications, Challenges and a Step Toward Precision Medicine

Single cell RNA sequencing (scRNA-seq) represents a new large scale and high throughput technique allowing analysis of the whole transcriptome at the resolution of an individual cell. It has emerged as an imperative method in life science research, uncovering complex cellular networks and providing indices that will eventually lead to the development of more targeted and personalized therapies. The importance of scRNA-seq has been particularly highlighted through the analysis of complex biological systems, in which cellular heterogeneity is a key aspect, such as the immune system. Autoimmune inflammatory rheumatic diseases represent a group of disorders, associated with a dysregulated immune system and high patient heterogeneity in both pathophysiological and clinical aspects. This complicates the complete understanding of underlying pathological mechanisms, associated with limited therapeutic options available and their long-term inefficiency and even toxicity. There is an unmet need to investigate, in depth, the cellular and molecular mechanisms driving the pathogenesis of rheumatic diseases and drug resistance, identify novel therapeutic targets, as well as make a step forward in using stratified and informed therapeutic decisions, which could now be achieved with the use of single cell approaches. This review summarizes the current use of scRNA-seq in studying different rheumatic diseases, based on recent findings from published in vitro, in vivo, and clinical studies, as well as discusses the potential implementation of scRNA-seq in the development of precision medicine in rheumatology.

Artificial intelligence and the future of radiographic scoring in rheumatoid arthritis: a viewpoint

Rheumatoid arthritis is an autoimmune condition that predominantly affects the synovial joints, causing joint destruction, pain, and disability. Historically, the standard for measuring the long-term efficacy of disease-modifying antirheumatic drugs has been the assessment of plain radiographs with scoring techniques that quantify joint damage. However, with significant improvements in therapy, current radiographic scoring systems may no longer be fit for purpose for the milder spectrum of disease seen today. We argue that artificial intelligence is an apt solution to further improve upon radiographic scoring, as it can readily learn to recognize subtle patterns in imaging data to not only improve efficiency, but can also increase the sensitivity to variation in mild disease. Current work in the area demonstrates the feasibility of automating scoring but is yet to take full advantage of the strengths of artificial intelligence. By fully leveraging the power of artificial intelligence, faster and more sensitive scoring could enable the ongoing development of effective treatments for patients with rheumatoid arthritis.

The clinical heterogeneity of adult onset Still's disease may underlie different pathogenic mechanisms. Implications for a personalised therapeutic management of these patients

Adult-onset Still's disease (AOSD) is a rare inflammatory disease of unknown aetiology usually affecting young adults and manifesting with a clinical triad of spiking fever, arthritis, and evanescent cutaneous rash. AOSD may be considered a highly heterogeneous disease, despite a similar clinical presentation, the disease course may be completely different. Some patients may have a single episode of the disease whereas others may evolve toward a chronic course and experience life-threatening complications. On these bases, to dissect the clinical heterogeneity of this disease, four different subsets were identified combining the manifestations at the beginning with possible diverse outcomes over time. Each one of these derived subsets would be characterised by a prominent different clinical feature from others, thus proposing dissimilar underlying pathogenic mechanisms, at least partially. Consequently, a distinct management of AOSD may be suggested to appropriately tailor the therapeutic strategy to these patients, according to principles of the precision medicine. These findings would also provide the rationale to recognise a different genetic and molecular profile of patients with AOSD. Taking together these findings, the basis for a precision medicine approach may be suggested in AOSD, which would drive a tailored therapeutic approach in these patients. A better patient stratification may also help in arranging specific designed studies to improve the management of patients with AOSD. Behind these different clinical phenotypes, distinct endotypes of AOSD may be suggested, probably differing in pathogenesis, outcomes, and response to therapies.

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.

New insights into the pathogenesis of giant cell arteritis: are they relevant for precision medicine?

Giant cell arteritis is a primary granulomatous vasculitis characterised by a strict tissue tropism for large and medium-size vessels, occurring in people older than 50 years. Although considerable progress in understanding some of the pathophysiological mechanisms involved in the pathogenesis of giant cell arteritis has been made in the past 10 years, specific triggers of disease and mechanisms of chronic damage have not yet been identified. The definition of a specific pro-inflammatory hierarchy between the multiple cell types and the different cytokines or chemokines involved in the inflammatory process are still unexplored areas of study. The overall goal of precision medicine is to identify the best possible therapeutic approach for an individual or group of individuals with a given disease. The fundamental prerequisite of this approach is the identification, at baseline, of clinical and imaging findings and of molecular biomarkers that allow a precise stratification of patients and an adequate prediction of the therapeutic response. In this regard, the possibility of obtaining temporal artery biopsies for diagnostic purposes offers incredible exploratory possibilities to define different disease pathotypes potentially susceptible to different therapeutic interventions. In this Series paper, we will describe the most recent evidence relating to the pathogenesis of giant cell arteritis, trying to define, if possible, a new pathogenetic-centred approach to patients with giant cell arteritis.

Possibilities for personalised medicine in rheumatoid arthritis: hype or hope

Knowledge of pathophysiology of rheumatoid arthritis (RA) has improved over the past decades, which resulted in new treatment options and strategies that led to better clinical outcomes. At the same time, we have come to understand that RA is a heterogeneous disease on a clinical as well as a pathophysiological level. Despite this heterogeneity, current management recommendations still adopt a ‘one-size-fits-all’ treatment approach, where ideally individualised treatment, or personalised medicine, is preferred. The first step towards personalised medicine in RA would be to designate different treatment strategies to distinct clinical or molecular phenotypes of patients. This viewpoint discusses current evidence and elaborates on future possibilities for personalised medicine in RA.

Title Current Status of the Search for Biomarkers for Optimal Therapeutic Drug Selection for Patients with Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by destructive synovitis. It is significantly associated with disability, impaired quality of life, and premature mortality. Recently, the development of biological agents (including tumor necrosis factor-α and interleukin-6 receptor inhibitors) and Janus kinase inhibitors have advanced the treatment of RA; however, it is still difficult to predict which drug will be effective for each patient. To break away from the current therapeutic approaches that could be described as a “lottery,” there is an urgent need to establish biomarkers that stratify patients in terms of expected therapeutic responsiveness. This review deals with recent progress from multi-faceted analyses of the synovial tissue in RA, which is now bringing new insights into diverse features at both the cellular and molecular levels and their potential links with particular clinical phenotypes.

From Bed to Bench and Back: TNF-α, IL-23/IL-17A, and JAK-Dependent Inflammation in the Pathogenesis of Psoriatic Synovitis

Psoriatic arthritis (PsA) is a chronic inflammatory immune-mediated disease with a burdensome impact on quality of life and substantial healthcare costs. To date, pharmacological interventions with different mechanisms of action, including conventional synthetic (cs), biological (b), and targeted synthetic (ts) disease-modifying antirheumatic drugs (DMARDs), have been proven efficacious, despite a relevant proportion of failures. The current approach in clinical practice and research is typically "predictive": the expected response is based on stratification according to clinical, imaging, and laboratory data, with a "heuristic" approach based on "trial and error". Several available therapeutic options target the TNF-α pathway, while others are directed against the IL-23/IL-17A axis. Janus kinase inhibitors (JAKis), instead, simultaneously block different pathways, endowing these drugs with a potentially "broad-spectrum" mechanism of action. It is not clear, however, whether targeting a specific pathway (e.g., TNF-α or the IL-23/IL-17 axis) could result in discordant effects over other approaches. In particular, in the case of "refractory to a treatment" patients, other pathways might be hyperactivated, with opposing, synergistic, or redundant biological significance. On the contrary, refractory states could be purely resistant to treatment as a whole. Since chronic synovitis is one of the primary targets of inflammation in PsA, synovial biomarkers could be useful in depicting specific biological characteristics of the inflammatory burden at the single-patient level, and despite not yet being implemented in clinical practice, these biomarkers might help in selecting the proper treatment. In this narrative review, we will provide an up-to-date overview of the knowledge in the field of psoriatic synovitis regarding studies investigating the relationships among different activated proinflammatory processes suitable for targeting by different available drugs. The final objective is to clarify the state of the art in the field of personalized medicine for psoriatic disease, aiming at moving beyond the current treatment schedules toward a patient-centered approach.

Current Status of the Evaluation and Management of Lupus Patients and Future Prospects

The vastly diverse nature of systemic lupus erythematosus (SLE) poses great challenges to clinicians and patients, as well as to research and drug development efforts. Precise management of lupus patients would be advanced by the ability to identify specific abnormalities operative in individual patients at the time of encounter with the clinician. Advances in new technologies and bioinformatics have greatly improved the understanding of the pathophysiology of SLE. Recent research has focused on the discovery and classification of sensitive and specific markers that could aid early accurate diagnosis, better monitoring of disease and identification of appropriate therapy choices based on specific dysregulated molecular pathways. Here, we summarize some of the advances and discuss the challenges in moving toward precise patient-centric management modalities in SLE.