Jebson, B. R., Ingledow, B., Alexiou, V., Kubiak, J., Jenkins, P., Meng, Y., Kartawinata, M., Restuadi, R., Lin, W. Y., Wallace, C., Chu, C. J., Solebo, A. L., Wedderburn, L. R., Rosser, E. C., & CLUSTER Consortium

Abstract

In Juvenile Idiopathic Arthritis (JIA), the most common childhood rheumatic disease, many patients also develop uveitis (JIA-uveitis), risking life-long vision loss. The mechanisms driving uveitis development in JIA remain understudied. Here, we demonstrate that peripheral blood CD19+IgD-CD27- double negative type 1 (DN1) B cells are elevated in JIA-uveitis compared to JIA patients without eye disease (JIA). The B cell receptor (BCR) repertoire was also more clonal and somatically hypermutated in JIA-uveitis and antigen-activated B cells infiltrated chronically inflamed JIA-uveitis eyes. Features of heightened B cell activation were recapitulated in experimental autoimmune uveoretinitis (EAU) and disrupting B and T cell interactions using monoclonal antibodies and transgenic mice suppresses uveitis. Together, these findings support a conceptual shift that uveitis is a primarily T cell driven disease and provide evidence for potential new therapeutic strategies that also consider B cells as drivers in disease pathology.

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Kartawinata, M., Lin, W.-Y., Jebson, B., O’Brien, K., Ralph, E., Welsh, E., Restuadi, R., Rosser, E. C., Deakin, C. T., Wedderburn, L. R., Wallace, C., & CLUSTER Consortium

Objectives
To identify and validate gene expression biomarkers in peripheral blood—measured before treatment—that predict response to methotrexate (MTX) in children with juvenile idiopathic arthritis (JIA).

Methods
RNA sequencing was conducted on sorted immune cell subsets (CD4+, CD8+, CD14+, CD19+) and PBMCs from a discovery cohort (n = 97) and two validation cohorts (n = 26 and n = 47) of non-systemic JIA patients. Gene expression at baseline (pre-MTX) was analyzed for associations with treatment response at 6 months using limma-voom, gene set enrichment analysis, and a 51-gene signature score. A parallel analysis was performed on adult rheumatoid arthritis (RA) data (n = 240) for comparison.

Results
In all three JIA cohorts, high baseline expression of interferon (IFN) alpha and gamma-stimulated genes was significantly associated with better MTX response at 6 months. This IFN-driven gene signature was predictive of good response and showed distinct patterns when compared with adult RA data.

Conclusions
A strong IFN-driven gene expression signature prior to MTX treatment is associated with improved treatment response in children with JIA. These findings support the development of predictive biomarkers to personalize therapy and identify patients who may require treatment escalation beyond MTX.

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Bolton, C., Mahony, C. B., Clay, E., Nisa, P. R., Lomholt, S., Hackland, A., Chin, P. S., Smith, C. G., Alexiou, V., Nguyen, H. D., Thyagarajan, M., Sheikh, Z., Davis, P., Chippington, S., Compeyrot-Lacassagne, S., Davda, S., Foley, C., Turtsevich, I., Ingledow, B., Kupiec, K., Kelly, J., Hanlon, M. M., DiCarlo, E., Jones, L. J., Smith, S. L., Eyre, S., Neag, G., Kemble, S., Madhu, R., Palshikar, M. G., Korsunsky, I., Gao, C., Tran, M., Dendrou, C., Buckley, C. D., Coles, M. C., Raza, K., the MAPJAG Study Group, Gravellese, E., Filer, A., Wei, K., Al-Abadi, E., Rosser, E. C., Wedderburn L. R., Croft, A. P., and the Multiomic Analysis of Paediatric Joint and Gut inflammation (MAPJAG) study group

Until this study, researchers had only examined blood samples and fluid from the joints of children with juvenile idiopathic arthritis (JIA). In this study, to better understand how JIA affects joints at the cell level, the team studied tissue samples from 19 children when they were diagnosed with arthritis, before they began treatment. Researchers took tiny samples of tissue from the inflamed joint lining, fluid from the joint, and blood to compare the cells found in each place. Using advanced tools that analyse individual cells, for the first time the team made a detailed map of the many cell types present in inflamed joints of children. They found that the joint tissue had a unique mix of cells not seen in the blood or joint fluid. The joint tissue also had structural cells (called fibroblasts) and blood vessels, as well as key immune cells. These were far more common in the inflamed tissue but absent in healthy joint samples. Some of these cells play a leading part in driving inflammation and the researchers found that they were linked to genes associated with worse arthritis symptoms.

Younger children had more of a specialised immune cell known as plasma cells, while older children showed a different mix of immune cells—suggesting that treatment strategies might need to be carefully designed according to the child’s age at diagnosis. To better understand how all these different cells interact within inflamed joints, the researchers used cutting-edge ‘spatial mapping’ methods – these allow them to see exactly where different cell types are located and how they talk to each other. They discovered that the joint is organized into several distinct “neighbourhoods”, each with a unique combination of cells and signalling activity. Higher numbers of certain neighbourhoods was linked to more severe inflammation.

Interestingly, for the first time, the researchers identified that some disease-driving cells were shared with adult-onset arthritis but also found key differences in children’s joints compared to adults—such as blood vessel patterns and immune responses. These findings show that childhood arthritis is not simply a smaller version of adult arthritis – it is its own distinct disease. Therefore, age-specific research is essential to develop more individual treatments for children with arthritis.

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Melissa Tordoff , Samantha L Smith, Saskia Lawson-Tovey; UK JIA Biologics Register, CAPS, CHARMS, CLUSTER, JIAGC; Andrew D Dick , Michael W Beresford , Athimalaipet V Ramanan, Kimme L Hyrich, Andrew P Morris, Stephen Eyre, Lucy R Wedderburn, John Bowes; CLUSTER consortium

Aims of research

To find changes in people’s DNA that lead to an increased risk of developing an inflammatory eye condition called uveitis. These changes in the DNA were then combined with clinical information to create a statistical test to help classify people with increased risk.

Background of research

Children and young people with juvenile idiopathic arthritis (JIA) are at a higher risk of developing uveitis. It is important to identify those at higher risk early. Several clinical factors, such as sex and the age at which JIA begins, have been associated with an increased risk of uveitis. Additionally, certain genetic variants in a specific part of the genome known as the human leukocyte antigen (HLA) region are also linked to this increased risk. However, until now, these factors have not been combined into a single test to identify those at high risk.

Design/methods – how this research was carried out?

We compared genetic variants between 579 JIA patients with uveitis and 2,479 patients without uveitis. We identified three genetic variants associated with an increased risk of developing uveitis. When these genetic factors were combined with clinical information, the ability to identify individuals at higher risk improved.

Conclusions

This research could lead to the development of a screening tool for uveitis in children and young people with JIA, potentially enabling earlier identification and intervention

Click the link below for the full paper:

Integration of genetic and clinical risk factors improves the risk classification of uveitis in patients with juvenile idiopathic arthritis – PubMed (nih.gov)

Freya Luling Feilding, Laura Crosby, Emily Earle, Richard Beesley, Kerry Leslie, Eilean MacDonald, Catherine Wright, Debbie Wilson, Anna Sherriffs, Teresa Duerr, Athimalaipet V Ramanan; CLUSTER Consortium

In juvenile idiopathic arthritis we have seen remarkable progress in the number of available licensed biological and small molecule treatments in the past two decades, leading to improved outcomes for patients. Designing clinical trials for these therapeutics is fraught with ethical, legislative, and practical challenges. However, many aspects of current clinical trial design in juvenile idiopathic arthritis do not meet the needs of patients and clinicians. Commonly used withdrawal trial designs raise substantial ethical concerns for patients and families who believe that they do not enable evidence-based and patient-centred decisions around medication choices. In this Viewpoint, we present the personal views of a patient and parent network that is of the opinion that current trial design in juvenile idiopathic arthritis is failing children and young people with juvenile idiopathic arthritis and set out the need for change informed by lived experience.

How can trial designs better serve the needs of children and young people with juvenile idiopathic arthritis? – PubMed (nih.gov)

Stephanie J.W. Shoop-Worrall, Saskia Lawson-Tovey, Lucy R. Wedderburn, Kimme L. Hyrich, Nophar Geifman, CLUSTER Consortium

DOI: https://doi.org/10.1016/j.ebiom.2023.104946

Summary:

Methotrexate is given to most children and young people with JIA. JIA is so varied that Methotrexate could help some areas of disease, and not others. But at the moment, we only look to see if someone has ‘responded’ or not. This study looked at four groups totalling nearly 2000 children and young people with JIA to understand how their disease changes after taking Methotrexate.

Stephanie J.W.Shoop-Worrall, Vanessa G Macintyre, Coziana Ciurtin, Gavin Cleary, Flora McErlane, Lucy R Wedderburn, Kimme L Hyrich, CLUSTER Consortium

DOI: https://doi.org/10.1002/acr.25296

Summary:

For the last 30 years, JIA has been classified or grouped into 7 subtypes to help guide research and also the way JIA may be treated. However, as we learn more about JIA, there are discussions as to whether this grouping needs to be updated. Recently, a research group called PRINTO, proposed a new way of grouping JIA. It is a work in progress but the early ideas of this group have been published. We wanted to know how these new proposed groups might compare to way the way we are currently sub-grouping different types of JIA.

The research included  data from 1223 children with JIA who had taken part in the Childhood Arthritis Prospective Study (CAPS), which ran between 2001 and 2019.   We found that currently, the majority (70%) of children with JIA would not yet have an assigned subtype using the new way of grouping, but we know further work is ongoing to understand the best way to group these children. For the new proposed categories which have been defined so far, we found very good overlap with an existing subgroup called enthesitis-related arthritis. Twenty percent of children received a new subgroup label called early-onset ANA positive JIA. We also saw an increase in the number of children who were now grouped under a heading called RF-positive JIA, which was less restrictive than previous groupings.

The new classification is still being developed and we do not yet know if and when it will be adopted into either research or clinical practice, and clearly there is much work still needed, but it is important to continue to use our understanding of what scientists have learned about this rare condition to ensure that research is delivered in the best way possible.

Richard Beesley, Freya Luling Feilding, CLUSTER Consortium Champions, Elizabeth C Rosser, Stephanie J W Shoop-Worrall, Alyssia McNeece, Zoe Wanstall, Kimme Hyrich, Lucy R Wedderburn, CLUSTER Consortium 

DOI: https://doi.org/10.1093/rheumatology/kead482

Summary:

The importance of Patient and Public Involvement and Engagement (PPIE) in the early phases of research design is significant and increasingly recognised throughout the research community. Here we describe the approach taken within the CLUSTER Consortium, setting out a stepwise process to support involvement at the earliest possible stage of project design, whilst acknowledging the real-world context of time pressures. This clearly defined strategic policy has ensured incorporation of PPIE into the early phases of research planning in CLUSTER and high-quality patient involvement has been demonstrated throughout the project. Ultimately this approach will strengthen research outcomes, maximising benefit for patients with JIA and JIA-Uveitis.

Saskia Lawson-Tovey, Samantha Louise Smith, Nophar Geifman, Stephanie Shoop-Worrall, Sandra Ng, Michael R. Barnes, Lucy R. Wedderburn, Kimme L. Hyrich &  CLUSTER consortium

DOI: 10.1186/s12969-023-00839-2

Abstract:

Background: CLUSTER is a UK consortium focussed on precision medicine research in JIA/JIA-Uveitis. As part of this programme, a large-scale JIA data resource was created by harmonizing and pooling existing real-world studies. Here we present challenges and progress towards creation of this unique large JIA dataset.

Methods: Four real-world studies contributed data; two clinical datasets of JIA patients starting first-line methotrexate (MTX) or tumour necrosis factor inhibitors (TNFi) were created. Variables were selected based on a previously developed core dataset, and encrypted NHS numbers were used to identify children contributing similar data across multiple studies.

Results: Of 7013 records (from 5435 individuals), 2882 (1304 individuals) represented the same child across studies. The final datasets contain 2899 (MTX) and 2401 (TNFi) unique patients; 1018 are in both datasets. Missingness ranged from 10 to 60% and was not improved through harmonisation.

Conclusions: Combining data across studies has achieved dataset sizes rarely seen in JIA, invaluable to progressing research. Losing variable specificity and missingness, and their impact on future analyses requires further consideration.

Lianne Kearsley-Fleet, Eileen Baildam, Michael W Beresford, Sharon Douglas, Helen E Foster, Taunton R Southwood, Kimme L Hyrich, Coziana Ciurtin

DOI: https://doi.org/10.1093/rheumatology/keac463

Abstract:

Sumner, E. J., Almeida, B., Palman, J., Bale, P., Heard, C., Holzinger, D., Roth, J., Foell, D., Robinson, E., Ursu, S., Wallace, C., Gilmour, K., Wedderburn, L. R., & Ralph, E. (2022).

DOI: https://doi.org/10.1007/s10067-022-06165-4

Abstract:

The objective of this study was to determine the effectiveness of MRP8/14 as a predictor of disease flare in patients with juvenile idiopathic arthritis (JIA) following the withdrawal of methotrexate (MTX) in a routine clinical setting. All MRP8/14 tests performed at a single centre in a 27-month period were considered for analysis. Patients were assessed against criteria for inactive disease and subsequent disease flare. Decisions on whether or not to stop treatment were recorded. MRP8/14 results were assessed in conjunction with clinical information. Clinicians were also surveyed to investigate if MRP8/14 influenced their decision to discontinue MTX where this was available at that time point. One hundred four cases met the inclusion criteria during the study period. Although there was no significant difference in flares between patients with an elevated or low MRP8/14 value, in those who stopped MTX (n = 22), no patients with a low MRP8/14 (≤ 4000 ng/ml) result flared (follow-up time 12 months). Clinicians reported that for patients with clinically inactive disease and an elevated MRP8/14 result (> 4000 ng/ml), none would advise withdrawal of MTX. Low MRP8/14 was interpreted favourably when considering stopping MTX treatment in patients with JIA. Implementation of MRP8/14 testing has changed clinical practice at this centre. However, the observation that some patients in our cohort who had an elevated MRP8/14 value did not flare after stopping MTX for non-disease-related reasons highlights the need for further biomarkers to predict the risk of flare off medication in JIA and aid clinicians in treatment decisions.

Key Points

• First study of serum MRP8/14 measurement in clinical practice to inform treatment decisions in patients with JIA.

• No patients with a low MRP8/14 test result went on to suffer a disease flare in 12 months of follow follow-up.

• Further biomarkers are needed to predict the risk of flare off medication in JIA and treatment decisions.

Lucy R Wedderburn, Athimalaipet V Ramanan, Adam P Croft, Kimme L Hyrich, Andrew D Dick, On behalf of the CLUSTER Consortium

DOI: 10.1136/ard-2022-222553

Abstract:

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.

Shoop-Worrall SJW, Cresswell K, Bolger I, Dillion B, Hyrich K, Geifman N, and Members of the CLUSTER Consortium (2021).

DOI: doi.org/10.1136/annrheumdis-2021-220454

Abstract:

Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support for therapy selection, and automated interpretation of clinical images. Nevertheless, such data-driven approaches could potentially model noise, or miss true clinical phenomena. One proposed solution to ensure clinically meaningful machine learning models is to involve primary stakeholders in their development and interpretation. Including patient and health care professionals’ input and priorities, in combination with statistical fit measures, allows for any resulting models to be well fit, meaningful, and fit for practice in the wider rheumatological community. Here we describe outputs from workshops that involved healthcare professionals, and young people from the Your Rheum Young Person’s Advisory Group, in the development of complex machine learning models. These were developed to better describe trajectory of early juvenile idiopathic arthritis disease, as part of the CLUSTER consortium. We further provide key instructions for reproducibility of this process. Involving people living with, and managing, a disease investigated using machine learning techniques, is feasible, impactful and empowering for all those involved.

Claire T Deakin, Georgina H Cornish, Kevin W Ng, Nikhil Faulkner, William Bolland, Joshua Hope, Annachiara Rosa, Ruth Harvey, Saira Hussain, Christopher Earl, Bethany R Jebson, Meredyth G L L Wilkinson, Lucy R Marshall, Kathryn O’Brien, Elizabeth C Rosser, Anna Radziszewska, Hannah Peckham, Harsita Patel, Judith Heaney, Hannah Rickman, Stavroula Paraskevopoulou, Catherine F Houlihan, Moira J Spyer, Steve J Gamblin , John McCauley, Eleni Nastouli, Michael Levin, Peter Cherepanov, Coziana Ciurtin, Lucy R Wedderburn, George Kassiotis

Deakin et al. examined the antibody response to the common-cold coronavirus HCoV-OC43 and cross-reactive response to SARS-CoV-2 in pre-COVID-19 pandemic sera from JIA, JDM, and JSLE patients.

They found that these prevalent inflammatory rheumatic diseases or their immunosuppressive treatment did not adversely affect the response to a common-cold coronavirus.

Access the full paper: https://pubmed.ncbi.nlm.nih.gov/34414384/

Nigrovic, P.A., Colbert, R.A., Holers, V.M., Ozen, S., Ruperto, N., Thompson, S. D., Wedderburn L.R., Yeung, R. S. M., Martini, A.  (2021)

Biological classification of childhood arthritis: roadmap to a molecular nomenclature

https://www.nature.com/articles/s41584-021-00590-6

Abstract:

Chronic inflammatory arthritis in childhood is heterogeneous in presentation and course. Most forms exhibit clinical and genetic similarity to arthritis of adult onset, although at least one phenotype might be restricted to children. Nevertheless, paediatric and adult rheumatologists have historically addressed disease classification separately, yielding a juvenile idiopathic arthritis (JIA) nomenclature that exhibits no terminological overlap with adult-onset arthritis. Accumulating clinical, genetic and mechanistic data reveal the critical limitations of this strategy, necessitating a new approach to defining biological categories within JIA. In this Review, we provide an overview of the current evidence for biological subgroups of arthritis in children, delineate forms that seem contiguous with adult-onset arthritis, and consider integrative genetic and bioinformatic strategies to identify discrete entities within inflammatory arthritis across all ages.

Fisher, C., Cirurtin, C., Leandro, M., Sen, D., Wedderburn L.R, (2021).

Similarities and Differences Between Juvenile and Adult Spondyloarthropathies

https://www.frontiersin.org/articles/10.3389/fmed.2021.681621/full 

Summary:

Spondyloarthritis (SpA) encompasses a broad spectrum of conditions occurring from childhood to middle age. Key features of SpA include axial and peripheral arthritis, enthesitis, extra-articular manifestations, and a strong association with HLA-B27. These features are common across the ages but there are important differences between juvenile and adult onset disease. Juvenile SpA predominantly affects the peripheral joints and the incidence of axial arthritis increases with age. Enthesitis is important in early disease. This review article highlights the similarities and differences between juvenile and adult SpA including classification, pathogenesis, clinical features, imaging, therapeutic strategies, and disease outcomes. In addition, the impact of the biological transition from childhood to adulthood is explored including the importance of musculoskeletal and immunological maturation. We discuss how the changes associated with adolescence may be important in explaining age-related differences in the clinical phenotype between juvenile and adult SpA and their implications for the treatment of juvenile SpA.

Infographic trajectories CAPS SSW

Shoop-Worrall SJ, Hyrich KL, Wedderburn LR, Thomson W, Geifman N, on behalf of CAPS the CLUSTER Consortium (2020).

DOI: 10.1016/S2665-9913(20)30269-1

Added value of this study:

Our work reports global longitudinal patterns of disease in children and young people with JIA, extending knowledge of the heterogeneity in disease course beyond the existing International League of Associations for Rheumatology paradigm. Additionally, studies have repeatedly shown that patient-reported outcomes do not correlate well with physician-reported outcomes. Our study shows that there are multiple clusters among children and young people with JIA who have different patterns in these outcomes over time, and that these patterns sometimes diverge. In doing so, we provide a foundation for reassessment of how JIA disease measures are used to capture disease course and clinical outcomes.

Shoop-Worrall SJ, Hyrich KL, Verstappen SM, Sergeant JC, Baildam E, Chieng A, Davidson J, Foster H, Ioannou Y, McErlane F, Wedderburn LR, Thomson W, McDonagh JE.

Comparing Proxy, Adolescent and Adult Assessments of Functional Ability in Adolescents with Juvenile Idiopathic Arthritis.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154708/ 

Shoop-Worrall SJ, Wu Q, Davies R, Hyrich KL, Wedderburn LR.

Predicting disease outcomes in juvenile idiopathic arthritis: challenges, evidence, and new directions.

https://www.sciencedirect.com/science/article/pii/S2352464219301889?via%3Dihub

Summary:

The aims of treating juvenile idiopathic arthritis are to elicit treatment response toward remission, while preventing future flares. Understanding patient and disease characteristics that predispose young people with this condition to these outcomes would allow the forecasting of disease process and the tailoring of therapies. The strongest predictor of remission is disease category, particularly oligoarthritis, although a few additional clinical predictors of treatment response have been identified. Novel evidence using biomarkers, such as S100 proteins and novel single nucleotide polymorphism data, could add value to clinical models. The future aim of personalised medicine in the treatment of juvenile idiopathic arthritis will be aided with international collaborations, allowing for the analysis of larger datasets with novel biomarker data. Combined clinical and biomarker panels will probably be required for predicting outcomes in such a complex disease.