RMD Open

BackgroundRheumatoid arthritis (RA) is a chronic inflammatory disease characterized by metabolic dysregulation, including altered lipid metabolism. While polyunsaturated fatty acids have been studied, the plasma levels, endogenous synthesis, and relevance of monounsaturated fatty acids (MUFAs) in RA remain unclear. This study examined plasma MUFA levels in RA and their associations with disease activity, adiposity, and intake. MethodsIn this cross-sectional study, 59 individuals with rheumatoid arthritis (RA) and 33 non-RA controls frequency-matched on age, sex, and BMI were recruited between 2017 and 2022. Clinical assessments included disease activity (DAS28), body composition, and metabolic parameters. Dietary intake was assessed using a 4-day food journal, and plasma fatty acids were quantified by gas chromatography in 82 participants with available samples. The stearoyl-CoA desaturase-1 (SCD-1) index was used as a proxy for endogenous MUFA synthesis. Associations between MUFAs and clinical variables were evaluated using univariate and multivariable regression (p<0.05). ResultsRA participants had higher waist-to-hip ratio, fat mass, fasting triglycerides, and lower physical activity than controls. Plasma palmitoleic and oleic acids and the SCD-1 index were higher in RA, whereas linoleic and arachidonic acids were lower. Saturated and omega-3 fatty acids were similar. Higher oleic and gondoic acids were independently associated with greater disease activity; oleic acid was linked to central adiposity, and palmitoleic acid was higher in women, suggesting sex- and adiposity-specific regulation. ConclusionsHigher plasma MUFAs in RA are associated with disease activity, adiposity, and sex, highlighting altered MUFA metabolism as a feature of RA and a potential target for metabolic intervention. Key MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSRheumatoid arthritis (RA) involves systemic inflammation and altered lipid metabolism. While polyunsaturated fatty acids have been studied extensively, the plasma levels, endogenous synthesis, and clinical relevance of monounsaturated fatty acids (MUFAs) in RA remain unclear. What this study addsPatients with RA have higher plasma MUFAs, including oleic and palmitoleic acids, and an elevated SCD-1 index, a marker of endogenous MUFA synthesis. Higher MUFAs are associated with disease activity, central adiposity, and sex-specific patterns, independent of dietary intake. How this study might affect research, practice or policyPlasma MUFAs could serve as potential biomarkers of RA disease activity and metabolic dysregulation. These findings suggest that altered MUFA metabolism contributes to inflammatory pathways, highlighting a potential target for future research, nutritional interventions, or therapeutic strategies.

Objectives: Juvenile systemic lupus erythematosus (JSLE) and juvenile dermatomyositis (JDM) are systemic autoimmune rheumatic diseases (RMDs) with childhood-onset associated with increased risk of damage accumulation and cardiovascular disease (CVD) over the life course. Methods: Damage associated with JSLE and JDM has been assessed using validated outcome measures in a longitudinal single-centre cohort study with long-term follow-up, involving data collected both retrospectively and prospectively. Descriptive statistics, sensitivity and regression analyses have been used to evaluate predictors of damage and CVD-risk. Results: We assessed comparatively a JSLE cohort (n=76), with a mean age of 24.3 +/- 4.2 years and a JDM cohort (n=79) with a mean 20.1 +/-5.0 years (p<0.001), with matched duration of follow-up (10.0 +/- 4.2 vs. 11.0 +/- 5.1, respectively, p=0.68). Traditional CVD-risk factors, including hypertension (p=0.02), dyslipidaemia (p=0.0005), and higher total cholesterol (p=0.01) and LDL-cholesterol (p=0.02) levels at the last assessment were higher in JSLE vs. JDM. Over the disease course, 39 (51.3%) AYA with JSLE vs. 47 (59.4%) AYA with JDM accumulated damage (p=0.307), which was independently predicted by the body mass index in both cohorts (p=0.038 and p=0.026, respectively). The PDAY score was the only tool able to stratify AYA based on CVD-risk (median = 5 (4-13) points in JSLE vs. 0 (0-3) points in JDM, p=0.0001), as all the adult CVD-risk scores were very low in both cohorts. Conclusions: This is the first comparative evaluation of JSLE vs. JDM in adulthood, which highlighted increased damage burden and CVD-risk in JSLE that warrants further investigation.

ObjectiveIdentifying risk factors enables stratification of patients susceptibility to inflammatory arthritis immune-related adverse events (IA-irAE). This retrospective study examines whether preexisting osteoarthritis (OA) increases the likelihood of de novo IA in patients treated with immune checkpoint inhibitors (ICIs). MethodsThe prevalence of OA among ICI-treated patients who developed IA-irAE, those who developed other types of irAEs but not IA (non-IA irAE), and those who did not develop any irAEs (non-irAE) were compared. Electronic medical records were reviewed to extract demographic, clinical and laboratory data. Group comparisons and logistic regression analyses were performed. Results181 de novo IA-irAE patients, 140 non-IA irAE patients and 170 non-irAE patients were included. The prevalence of OA was significantly higher in the IA-irAE group (69%) than the non-IA irAE group (48%) and the non-irAE group (48%) (both p < 0.001). The IA-irAE group demonstrated a higher frequency of multisite OA, with predominant hand involvement (62%) than the non-IA irAE with OA group (13%) and the non-irAE with OA group (13%) (both p < 0.001). A family history of autoimmune disease (AID) (OR 2.03, 95% CI 1.02-4.05), preexisting OA (OR 2.88, 95% CI 1.85-4.52) and melanoma (OR 2.63, 95% CI 1.56-4.47) were identified as risk factors for the development of IA-irAE. ConclusionsOA was more prevalent among ICI-treated patients developing IA-irAE than those who did not. Hand OA was the most common OA pattern in IA-irAE patients. Preexisting OA, melanoma and a family history of AID were risk factors for IA-irAE.

ObjectivesPatients with osteoarthritis (OA) affecting multiple joints have poorer health outcomes than those without, yet most research examines isolated joints, leaving a gap in multi-joint disease. This study aimed to describe radiographically defined hip (rHOA) and knee OA (rKOA) within UK Biobank (UKB), exploring interrelationships across joints, and associations with joint pain, obesity, race and deprivation. MethodsAutomated machine learning was applied to left and right hip and knee dual-energy X-ray absorptiometry scans. Radiographic OA (rOA) was defined as custom grades [&ge;]2. Joint pain was assessed through self-reported questionnaires. Descriptive statistics summarised the population characteristics. Logistic regression models examined bilateral and cross-joint associations, as well as associations with joint pain. Adjustments were made for age, sex, race, height, weight and deprivation. Other models examined the associations between body size and OA. ResultsAmong 59,475 individuals (mean age 65 years; 52.8% female), rHOA prevalence was 4,098 (6.9%)) and 4,841 (8.1%) for the right and left joints, respectively. The corresponding estimates for rKOA were 3,750 (6.3%) and 4,220 (7.1%). Overall, increasing grades of rOA and number of joints affected were more strongly associated with joint pain. Regarding joint-interrelationships, bilateral associations were stronger at the knee, whereas cross-joint associations (hip-knee) were weaker. Associations with BMI and height differed between the hip and knee. ConclusionsRadiographic hip and knee OA exhibit distinct patterns of interrelationship, associations with symptoms and risk factors, suggesting heterogeneity in disease process and the need for joint-specific treatment. Key MessagesO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LIOsteoarthritis (OA) commonly affects the hip and knee and is associated with pain and disability, with recognised risk factors such as age, obesity and deprivation. C_LIO_LIIncreasing interest in multi-joint OA challenges the traditional concept of lower-limb OA as a monoarthritis, but most research examines joints in isolation. C_LIO_LIGenetic evidence suggests that hip and knee OA may differ in underlying mechanisms, yet population-scale comparisons are limited. C_LI What this study adds?O_LIAmong 59,574 individuals, this study identifies that radiographic OA captures structurally and clinically relevant disease with increasing severity and greater number of joints affected, positively associated with chronic joint pain. C_LIO_LIRadiographic hip and knee OA demonstrated strong bilateral but weaker cross-joint associations, indicating preferential within-joint symmetry. C_LIO_LIRisk factors differed by anatomical site with BMI and weight strongly associated with knee OA and weakly associated with hip OA. Height showed the opposite associations. C_LI How this study might affect research, practice or policy?O_LIThese findings support that hip and knee OA may partially represent different disease processes rather than a single condition. C_LIO_LIClinical practice should consider cumulative joint involvement and joint-specific risk factors. C_LIO_LIFuture research should consider the development of more targeted treatment to prevent multi-joint progression. C_LI

BackgroundExcessive accumulation of fibrillar collagen causes pathological scarring and fibrosis. A promising anti-fibrotic strategy targets the extracellular assembly of collagen fibrils rather than intracellular synthesis pathways. We previously developed a chimeric monoclonal antibody targeting the C-terminal telopeptide of the 2(I) chain of human collagen I that effectively disrupts fibrillogenesis. This study details the engineering of a humanized antibody variant optimized for therapeutic application, augmented with a collagen-binding peptide (CBP) to enhance targeted retention in fibrotic tissues. MethodsA humanized ACA was engineered by in silico homology modeling, complementarity-determining region grafting, and sequence optimization to eliminate chemical liabilities. Variants were expressed in mammalian cells and evaluated for binding kinetics and specificity. To improve spatial localization, the CBP was fused to the antibody. The lead variant was assessed for in vitro cytotoxicity, matrix retention, and in vivo efficacy using a rabbit model of post-traumatic knee arthrofibrosis. ResultsThe humanized ACA variants maintained high specificity and affinity for the 2Ct target domain. Fusing the CBP to the C-terminus of the light chain (C-cbpACA) successfully enhanced matrix retention without compromising target engagement or causing cellular toxicity. In the rabbit arthrofibrosis model, intra-articular C-cbpACA delivery significantly reduced flexion contracture and decreased total collagen deposition in the joint capsule compared to untreated controls. ConclusionWe successfully engineered a clinically viable, humanized, and matrix-targeted anti-fibrotic antibody that specifically inhibited extracellular collagen assembly and exhibited enhanced localization within fibrotic tissues. This construct represents a promising therapeutic strategy for mitigating pathological scarring and improving post-traumatic functional outcomes.

ObjectivesRheumatoid arthritis (RA) exhibits clinical and biological heterogeneity, with synovial tissue stratified into histological pathotypes: lympho-myeloid, diffuse-myeloid, and pauci-immune fibroid. Although GWAS have uncovered RA risk loci, how genetic risk relates to synovial immunopathology remains unclear. To better understand how genetic predisposition may shape divergent early disease mechanisms, we characterised the expression patterns of GWAS-identified RA susceptibility genes and related rheumatic diseases across the synovial pathotypes. MethodsRNA-sequencing data from synovium of 87 treatment-naive, early RA patients from the Pathobiology of Early Arthritis Cohort. Differential gene expression between pathotypes and pathway enrichment analyses were performed using susceptibility genes for RA, osteoarthritis (OA), ankylosing spondylitis, psoriatic arthritis and systemic lupus erythematosus. ResultsRA susceptibility gene expression in synovial tissue separated patients by pathotype and correlated with markers of disease activity. RA susceptibility genes were significantly enriched among genes upregulated in lympho-myeloid synovium and linked to lymphocyte activation and differentiation pathways. In contrast, OA susceptibility genes were upregulated in diffuse-myeloid and fibroid synovium. Both patterns were most pronounced in ACPA-positive and directionally consistent in ACPA-negative patients. ConclusionRA genetic susceptibility is not evenly distributed across synovial pathotypes but is strongly biased toward the lympho-myeloid pathotype, indicating that current GWAS signals preferentially capture immune-driven disease mechanisms. Enrichment of OA susceptibility genes in diffuse-myeloid and fibroid pathotypes, even among ACPA-positive patients, suggests shared biological features between auto-immune and non-inflammatory degenerative joint diseases in certain RA subtypes. Synovial pathotype stratification is therefore essential for interpreting genetic risk and understanding disease heterogeneity. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABS- Rheumatoid arthritis (RA) is clinically and biologically heterogeneous, and its affected synovial tissue can be stratified into distinct immunohistological pathotypes. - GWAS have identified numerous genetic risk loci for RA and related rheumatic and inflammatory diseases. - It remains poorly understood how RA genetic risk relates to synovial tissue heterogeneity. What this study adds- GWAS-identified RA susceptibility genes show strong, pathotype-specific expression in synovial tissue, with marked enrichment in the lympho-myeloid pathotype. - OA susceptibility genes are primarily upregulated in diffuse-myeloid and pauci-immune fibroid RA synovium, indicating shared fibroblast- and remodelling-related pathways. - These gene expression patterns are most pronounced in ACPA-positive RA but remain directionally consistent in ACPA-negative RA. How this study might affect research, practice or policy- Synovial pathotype stratification should be incorporated into genetic studies of RA. - Pathotype-aware genetic studies may improve patient stratification and guide development of more targeted therapeutic strategies.

BackgroundJuvenile idiopathic arthritis (JIA) shows recognised sex differences, but their impact on treatment and early outcomes remains uncertain. This study assesses sex-specific patterns in onset, phenotype, treatment timing, and short- and medium-term outcomes in JIA. MethodsData were drawn from the Childhood Arthritis Prospective Study (CAPS), a UK multicentre inception cohort of 1,789 children presenting with a new episode of arthritis. Demographics, subtype distribution, clinical features, and 6- and 12-month outcomes were stratified by sex. Cox, Kaplan-Meier, and linear regression models assessed associations between sex and treatment initiation and 12-month outcomes. ResultsThe cohort was predominantly female (64.3%), with a median age at symptom onset of 6.8 years. Girls were younger than boys at onset (6.1 vs 7.8 years, p<0.0001) and diagnosis (7.0 vs 9.1 years, p<0.0001) and demonstrated a distinct bimodal age distribution. Diagnostic delay was short and comparable (median 4.4 months, p=0.8932). At diagnosis, girls had slightly higher active joint counts (p=0.0080, while inflammatory markers were similar except in psoriatic JIA, where females had higher ESR and CRP. After adjustment, sex was not associated with time to methotrexate (HR 0.89, 95% CI 0.74-1.06) or biologic initiation (HR 0.91, 95% CI 0.72-1.16). Outcomes at 6- and 12-month were largely comparable, with only ESR showing a modest male-favoured improvement at 12 months (p=0.0480). ConclusionsSex shaped age at onset and subtype distribution but did not independently influence treatment timing or early outcomes, underscoring the value of sex-aware analyses while confirming broadly comparable short-term trajectories in JIA. Evidence before this studyRecent evidence on sex effects in JIA is genuinely mixed: several cohorts have reported that girls, despite more severe onset, show greater resolution of objective inflammation, while a newer, large network analysis found females had poorer outcomes across composite disease activity and pain, pointing to potential inequities or phenotype-driven differences. In parallel, boys, especially in enthesitis-related arthritis (ERA), often exhibit more persistent activity and risk of damage. Overall, the picture is controversial: sex appears to shape biology, trajectory, and patient-reported burden in different ways across subtypes and settings, reinforcing the need for sex-stratified analyses, careful adjustment for confounders, and precision approaches that integrate biomarkers, subtype, and social context in JIA care. Added value of this studyThe study establishes that, although sex is closely linked to JIA subtype distribution and baseline clinical features, it does not independently determine the timing of methotrexate or biologic initiation within a UK inception cohort. By analysing one of Europes largest prospective multicentre datasets, it provides strong evidence that treatment decisions appear to be guided by disease characteristics rather than demographic bias. Within the context of the UK National Health Service (NHS), where universal access to paediatric rheumatology care is a core principle, this study provides important epidemiological evidence on sex and equity in JIA. Although clear sex differences were observed in age at onset, subtype distribution, and certain diagnostic features, these did not translate into disparities in treatment timing or medium-term disease burden. The absence of sex-based differences in 6 and 12-month outcomes, despite variation in baseline presentation, suggests that the NHS model of coordinated, guideline-driven care may help buffer against inequities that might otherwise emerge in systems with variable access. These findings reinforce the value of population-based cohorts in evaluating equity within healthcare delivery and highlight that, in this setting, sex does not appear to drive differential treatment or short-term clinical trajectories. Implications of all the available evidence.This study underscores sex as an important biological variable in JIA. Although treatment initiation was equitable and disease-driven, baseline phenotype differences and isolated effects on 12-month outcomes highlight how sex interacts with JIA subtype and initial disease burden. Prior work shows that females often present earlier with higher inflammatory burden, while males are more frequently affected by ERA, a subtype linked to treatment resistance and poorer long-term outcomes. Yet published findings remain inconsistent, with some cohorts reporting better resolution of inflammation in females and others suggesting poorer outcomes. Our findings suggest that coordinated and guideline-driven care may minimise sex-related disparities in JIA, even when underlying biological or phenotypic differences exist. The comparable medium-term trajectories observed across sexes support equitable paediatric rheumatology care in the UK and highlight the need to continue monitoring for structural or access-related inequities beyond clinical measures.

BackgroundInterleukin-6 (IL-6) is a cytokine that plays a key role in systemic hyperinflammation and may mediate the relationship between acute COVID-19 and severe long-term outcomes such as Long COVID or death. IL-6 modulating drugs may reduce patients risk of severe post-COVID-19 outcomes. MethodsWe conducted an emulated target trial in a retrospective cohort of patients with moderate-to-severe rheumatoid arthritis who were prescribed IL-6 receptor antagonists (sarilumab or tocilizumab, pooled treatment) or other biologic agents (anakinra or baricitinib, pooled comparator) in 2022. We compared the 12-month cumulative incidence of mortality and Long COVID (diagnosed and probable) between groups using Super Learner and targeted maximum likelihood estimation, adjusting for covariates of interest. ResultsIn our cohort of 3,553 patients, we found that prescription of IL-6 receptor antagonists was associated with a lower 12-month cumulative mortality (adjusted relative risk (aRR) 0.40, 95% CI 0.27, 0.59), diagnosed Long COVID aRR 0.42, 95% CI 0.23, 0.78), and probable Long COVID (aRR 0.71, 95% CI 0.61, 0.83), compared to prescription of other biologic agents, among rheumatoid arthritis patients. ConclusionsIL-6 receptor antagonists may prevent the incidence of severe post-COVID-19 outcomes, such as Long COVID or mortality. This supports the hypothesis that IL-6 may be a mechanistic biomarker of COVID-19 sequelae and that acute COVID-19 severity may mediate this relationship.

ObjectiveQuantitative computed tomography (QCT) can automatically quantify parenchymal abnormalities on chest CT imaging using deep learning. We leveraged QCT to detect pulmonary abnormalities in patients with early rheumatoid arthritis (RA) compared to healthy controls. MethodsWe analyzed high-resolution CT chest imaging from participants with early RA in the prospective, multicenter, SAIL-RA study and healthy non-smoking controls from the COPDGene study. A deep learning classifier quantified the percentage of normal lung, interstitial abnormalities, and emphysema for each participant. We compared the percentage of QCT features between early RA participants and healthy comparators and examined associations using multivariable linear regression. ResultsWe analyzed 200 participants with early RA (median RA duration 8.3 months, mean age 55.7 years, 74.5% female) and 104 healthy controls (mean age 62.0 years, 68.3% female). The median percentage of interstitial abnormalities on QCT was 3.7% (IQR 2.1, 6.1%) for early RA and 1.6% (IQR 0.8, 2.4%) for healthy controls (p<0.0001). Early RA was associated with 9.3% less normal lung on QCT than healthy controls, adjusted for age and sex (p<0.0001). Among RA participants, QCT interstitial abnormalities were associated with older age (multivariable {beta}=0.1 per year, 95%CI 0.07-0.2, p<0.0001) and higher DAS28-ESR (multivariable {beta}=0.6 per unit, 95%CI 0.01-1.3, p=0.046). ConclusionParticipants with early RA had less normal lung and more interstitial abnormalities on a deep learning-derived QCT measure than healthy controls. These results suggest that loss of normal lung is already present in early RA and emphasizes the urgent need for strategies to preserve lung health in RA.

OBJECTIVESOsteoarthritis is a heterogeneous disease, with diverse structural patterns likely reflecting distinct genetic drivers. Robust, data-driven methods to identify and characterise such phenotypes are lacking. This study leveraged the UK Biobank to define machine learning-derived structural osteoarthritis phenotypes and evaluate their clinical and genetic profiles. METHODSMachine learning models were applied to knee and hip DXA scans to derive osteophyte area, minimum joint space width, and B-scores (a combined shape vector predictive of osteoarthritis). Imaging and demographic features were clustered using k-means to classify individuals with at least one osteoarthritis feature. Phenotypes were compared with healthy controls for associations with joint pain and total joint replacement (TJR). Genetic correlations, osteoarthritis risk loci, and polygenic risk scores were analysed to define shared and distinct genetic mechanisms between phenotypes. RESULTSAmong 59,539 participants (mean age 65 years; 53% female), nine reproducible phenotypes were identified, spanning joint-specific and multi-joint patterns. Hypertrophic and end-stage knee phenotypes showed the highest odds of pain (OR 7.8 [95% CI 7.1,8.7], 13.4 [9.5,19.0]) and TJR (66.0 [46.6,93.5], 127.6 [72.6,224.1]). A novel increased-cartilage phenotype was associated with greater odds of hip (3.5 [2.4,5.2]) and knee replacement (4.1 [2.6,6.6]). Distinct genetic architectures were observed; increased- and atrophic-cartilage phenotypes were inversely genetically correlated (rg -0.46 [-0.9,-0.2]) with opposing effects at DOT1L and COL27A1. CONCLUSIONSMachine learning revealed nine reproducible osteoarthritis structural phenotypes with divergent clinical and genetic signatures. These findings demonstrate that simple imaging and demographic data can stratify patients into biologically distinct phenotypes likely to require tailored treatments. Key messagesWhat is already known on this topic? O_LIDifferent osteoarthritis phenotypes have been proposed, which could guide patient stratification for drug trials and pharmacotherapy. However, these proposals have mainly been based on analysis of small numbers of patients that are focused on the knee joint alone. C_LIO_LITo our knowledge, no systematic, hypothesis-free approach has been applied to classify different osteoarthritis phenotypes using structural features derived from large numbers of individuals. C_LI What this study adds? O_LIThis study identifies and characterises nine reproducible structural phenotypes of osteoarthritis across both the hip and knee using high-resolution DXA imaging in UK Biobank. C_LIO_LIIt demonstrates that these phenotypes have distinct clinical profiles, with widely varying risks of joint pain and subsequent joint replacement. C_LIO_LIIt provides robust evidence that the phenotypes differ in their genetic architecture, supporting the existence of genetically determined endotypes within osteoarthritis. C_LI How this study might affect research, practice or policy? O_LIThe findings advance understanding of the structural heterogeneity of osteoarthritis and highlight that distinct phenotypes represent different biological pathways guiding research into future disease modifying therapeutics. C_LIO_LIThe automated, scalable methods used here could support patient stratification in clinical trials, enabling targeted evaluation of treatments in phenotypes most likely to benefit, an essential step towards a precision medicine approach in osteoarthritis. C_LI

BackgroundBiologics and Janus kinase (JAK) inhibitors carry specific risks for Ankylosing Spondylitis patients at risk of tuberculosis infection or those with contraindications such as a history of cancer, there is an urgent need to explore safe and effective alternative treatment options. AimsTo evaluate the efficacy and safety of Iguratimod combined with Yunke injection in the treatment of ankylosing spondylitis at risk of tuberculosis infection or those with a history of cancer. Study DesignRetrospective cohort study. MethodsA retrospective study was conducted on 48 patients with ankylosing spondylitis who had received treatment over the past 3 years and had a history of tuberculosis infection or malignancy. Their treatment regimens and therapeutic outcomes were analyzed, with particular attention to the progression of tuberculosis and malignancy. ResultsThere was 30 patients receiving Iguratimod combined with Yunke injection treatment, and non-steroidal anti-inflammatory drugs (NSAIDs) were added when pain was severe,referred to as the observation group; 18 patients took Iguratimod and NSAIDs, referred to as the contral group. After treatment of 24 months, both groups showed significant improvements in Ankylosing Spondylitis Disease Activity Score (ASDAS), Bath Ankylosing Spondylitis Functional Index (BASFI), modified Stoke Ankylosing Spondylitis Spine Score (mSASSS), Erythrocyte Sedimentation Rate (ESR), and C-Reactive Protein (CRP), and overall levels could achieve low disease activity. However, the improvement of observation groupin was better than that in the control group, P<0.05. Moreover, the use of NSAIDs in the observation group was significantly less than that in the control group, P<0.001. ConclusionThis study shows that Iguratimod combined with Yunke injection has good efficacy in patients with ankylosing spondylitis who cannot use biologics or JAK inhibitors, not only alleviating pain and morning stiffness but also slowing radiographic progression and reducing the dose of NSAIDs. The combination has a synergistic effect and does not increase adverse reactions. This therapy provides a novel option for patients with specific ankylosing spondylitis.

ObjectivesResearch of refractory disease in juvenile idiopathic arthritis (JIA) is limited, and a potential genetic contribution has yet to be investigated. This study aimed to explore the presence of rare monogenic disease gene coding variants in a refractory JIA population. MethodsCases were included with a record of inefficacy for methotrexate and [&ge;]1 biologic drug or exposure to methotrexate and [&ge;]2 biologic drugs for any reason. Whole exome sequencing data were analysed using VarSeq. rarity and pathogenicity filters were applied. Variants within an OMIM curated paediatric monogenic gene list, arthritis OMIM gene list, primary immunodeficiency gene panel (PanelApp) or gene reported for JIA drug response or toxicity (ClinPGX) were retained. ACMG classification excluded benign or likely benign variants. ResultsIn total, 83 individuals were included. Twelve variants were previously reported in other paediatric onset diseases with similar phenotypes to JIA. Seventeen variants were detected in twelve genes with an arthritis OMIM phenotype. Seventeen variants were detected within fourteen genes that were reported on the primary immunodeficiency panel (PanelApp) and were previously reported in a publication. A total of 39 variants were detected in genes from a JIA drug response or toxicity gene list (ClinPGX). ConclusionsThis study evidences that 66 individuals with refractory JIA carry rare variants associated with paediatric diseases, JIA susceptibility loci or drug response and toxicity. These variants could contribute to refractory disease, mimics of JIA/complicated phenotypes or effect treatment response. Longitudinal data are needed to confirm these findings.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease that causes joint destruction along with extra-articular morbidity and early mortality. Abatacept (CTLA-4 Ig), a blocker of lymphocyte co-stimulation, has become a well-accepted biologic treatment with proven efficacy in established-RA and for preventing disease onset in predisposed individuals. To investigate the immunologic implications of abatacept treatment, we conducted a prospective, open-label trial with multi-omic single-cell analyses of lymphocytes and BCR repertoire profiling at predefined intervals. Treatment-induced low-disease activity correlated with coordinated depletion of circulating peripheral helper cells (Tph), late-activated naive cells (late-aNAV), and of CD27-IgD- (Double negative, DN) Zeb2+CD11c+ T-box transcription factor 21 (Tbet+) DN2 unconventional memory B cells, implicated in the tertiary lymphoid structures responsible for the propagation of pathologic autoimmune responses and joint destruction. Among B-cell subsets, DN2 had the greatest representation of molecular machinery for antigen-uptake, processing, and presentation. Among memory B-cell subsets, DN2 had the lowest representation of somatically generated N-glycosylation sites and somatic hypermutation. Yet abatacept induced DN2 cells to express elevated CXCR4 levels, which normalized upon drug withdrawal, suggesting that abatacept treatment may cause these cells to traffic out of pathologic synovial infiltrates. In conclusion, we have documented that abatacept affects the circulating immune cellular drivers of disease activity, Tph, late-aNAV and DN2. Therapeutic depletion of these pathologic lymphocyte subsets is associated with clinical benefits that can persist after therapy cessation. Hence, levels of these subsets may serve as surrogates for the overall burden of disease and potential response to abatacept therapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=62 SRC="FIGDIR/small/26348386v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@b44131org.highwire.dtl.DTLVardef@241f4eorg.highwire.dtl.DTLVardef@18361f6org.highwire.dtl.DTLVardef@9470b7_HPS_FORMAT_FIGEXP M_FIG C_FIG One Sentence SummaryMulti-omics analyses showed costimulatory blockade depletes trafficking DN2 B cells and Tph cells that correlates with rheumatoid disease response.

ObjectiveTo clinically evaluate a digital biomarker, the Finger Fold Index (FFI), derived from the ratio of joint diameter to finger fold surface area in hand photographs, for assessing joint swelling in inflammatory arthritis. MethodsSmartphone hand photographs from two routine care cohorts of patients with rheumatoid (RA) and psoriatic arthritis (PsA) were analyzed using a machine learning pipeline for automated detection and processing of proximal interphalangeal (PIP) joints. The FFI was clinically evaluated by correlation with joint swelling scores (0-3) and DAS28-CRP. A healthy cohort was used to establish FFI reference ranges, which were then compared to the arthritis cohorts. ResultsA total of 1275 PIP joint images of 124 arthritis patients and 53 healthy individuals were included. FFI values correlated with swelling scores in the arthritis population with r = 0.443 (95% CI 0.384-0.498). A correlation was observed between the mean FFI and DAS28-CRP dichotomized at 3.2 (r = 0.310, 95% CI 0.123-0.475). FFI values exceeding the healthy reference ranges were associated with swelling (Cramers V = 0.400-0.631; p < 0.001). ConclusionFFI values derived from hand photographs showed a significant association with clinical joint swelling and disease activity in RA and PsA patients. Longitudinal studies are needed to assess sensitivity to change and to establish whether this biomarker can be reliably used for remote patient monitoring.

Protein kinase A (PKA) is involved in bone biology and is a key mediator of parathyroid hormone signaling in the osteoblast. However, the consequences of sustained PKA activation in bone are unclear. In this study, we inducibly activated PKA in osteoblasts by deleting its major regulatory subunit, Prkar1a, using a Col11-driven Cre system. Prkar1aob-/-mice demonstrated rapid and profound bone pathologies in their femurs, lumbar and caudal vertebrae with cortical bone breakdown and cortical trabecularization. This phenotype was characterized by increased bone turnover and elevated osteoblastic and osteoclastic activities. Transcriptomic and qPCR analyses showed an impairment of osteoblast differentiation with a defect in ossification, expansion of stromal cells, and numbers of both osteoblastic and osteoclastic precursors. Moreover, there were alterations in gene expression of chemokines and Wnt members with enhanced osteoclastogenesis. Altogether, activation of PKA in osteoblasts by inducible deletion of Prkar1a causes a profound high bone turnover phenotype resembling several human bone diseases.

BackgroundChildren with juvenile idiopathic arthritis (JIA) are reported to exhibit increased rates of symptoms affecting emotional regulation and behavior. However, underlying biological mechanisms remain unclear. Neuroinflammation in the central nervous system (CNS) can be triggered by peripheral immune effects and may contribute to these observations. In this study, we aimed to investigate if neurobiological alterations are present in systemic JIA (sJIA), and if CNS neuroinflammation occurs during arthritis, and to explore the potential mechanisms involved. MethodsPlasma samples from patients with active sJIA (n = 16) and sex- and age-matched healthy controls (HCs, n = 16), together with paired samples from the same sJIA patients during inactive disease (n = 12), were analyzed using Olink proteomics to determine the peripheral neurobiological and inflammation protein profiles. Clinical data was retrieved from the Swedish Pediatric Rheumatology Register and medical charts. CNS Neuroinflammatory responses and underlying mechanisms were further explored through in vivo and in vitro experiments. FindingsActive sJIA patients exhibited altered neurobiological protein profiles compared with HCs. These alterations correlated with higher scores of pain and life impact in patients, suggesting that the altered profiles may reflect neurofunctional changes in the patients. Notably, the neurobiological protein profile remained altered even during the inactive phase of the disease. In chronic arthritic mice, microglial activation and impaired neurogenesis were observed in hippocampus, with no significant cortical changes. RNA-seq analysis implicated mitochondrial dysfunction and oxidative stress in mediating neuroinflammation during chronic arthritis in mice. Heme oxygenase 2 (HMOX2) was identified as a peripheral biomarker indicating hippocampal microglia activation. Combined neurobiological and inflammation profiling in sJIA patients implicated Interleukin-6 (IL-6) and Interleukin-18 (IL-18) as key drivers of hippocampal microglia activation during arthritis. InterpretationChronic arthritis is associated with neuroinflammation and altered neurobiological protein profiles in sJIA. HMOX2 emerges as a promising plasma biomarker of CNS changes. IL-6 and especially IL-18 are indicated as key drivers of neuroinflammatory processes. These findings offer insights for clinical monitoring and targeted therapies. FundingThis study was funded by grants from the Swedish Research Council and The Swedish Rheumatism Association. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSChildren with juvenile idiopathic arthritis (JIA) have increased rates of emotional and behavioral disturbances compared with healthy peers. Systemic inflammation and chronic arthritis are suspected to affect the central nervous system, but biological mechanisms in systemic JIA (sJIA) are poorly understood. Added value of this studyIn this study, we demonstrate patients with sJIA have a distinct plasma neurobiological protein profile compared with healthy controls, which correlate with higher pain and life impact scores. In chronic arthritic mice, hippocampal microglial activation, impaired neurogenesis, and mitochondrial dysfunction with oxidative stress are presented. By combining patient and mouse data, we identify heme oxygenase 2 (HMOX2) as a candidate plasma biomarker of hippocampal neuroinflammation and implicate IL-6, and especially IL-18, as key mediators linking chronic arthritis to neurobiological changes. Implications of all the available evidenceThis study provides molecular evidence that neurobiological alterations in sJIA patients and supports incorporating neurobiological and neuropsychiatric monitoring into the clinical follow-up of children with sJIA. We highlight the mechanistic targets and measurable biomarkers (e.g. HMOX2) for future studies and trials aiming to modulate neuroinflammation in chronic arthritis. This study may inform the development of personalized treatment strategies, including IL-18-directed therapies, for patients at risk of neurological or psychosocial complications.

Aberrant bone remodeling is a hallmark of osteoarthritis, the most common arthritis affecting over 27 million US adults. Subchondral bone sclerosis, one sign of aberrant bone remodeling observable by routine x-rays, occurs as the trabeculae thicken, leading to increased bone volume. Toll-like receptors, pattern-recognition receptors of the innate immune system, have been implicated in OA pathogenesis, with TLR ligands, receptors, and co-receptors shown to mediate the severity and progression of OA. We have previously shown that CD14-deficiency protects mice against post-traumatic OA, and specifically reduces subchondral sclerosis post-injury. We hypothesized that depletion of CD14 protects against TLR4-dependent inhibition of osteoclastogenesis and therefore increases OC density in the SCB after injury, mitigating aberrant bone deposition in a murine model of OA. To determine how cellular changes correlate with bone structure derangements post-DMM, we performed MicroCT, Tartrate-resistant acid phosphatase staining, and alkaline phosphatase staining. To establish mechanistic changes in cellular signaling, we isolated WT and CD14-deficient osteoclast precursors and subjected them to LPS, an osteoarthritis-relevant TLR ligand, during differentiation. CD14-deficient mice, as well as WT mice treated with an anti-CD14 monoclonal antibody, show protection from post-injury increases in both bone volume fraction and bone mineral density. CD14-deficient mice had an increased osteoclast presence in the SCB two weeks post-injury, potentially protecting them from increases in bone volume and density. In vitro, CD14-deficient OCPs differentiated faster than WT OCPs, due to reduced Type I Interferon (IFN-I) signaling. In the presence of an LPS challenge, CD14-deficient OCPs were protected against LPS and TLR4-mediated inhibition, likely due to decreased MyD88-dependent TLR4 signaling. This work opens up new potential pathways to therapeutically target aberrant bone remodeling in the setting of joint injury and PTOA. Lay SummaryOsteoarthritis is one of the leading causes of disability worldwide. One of the hallmarks is subchondral sclerosis, or thickening of the bone in and around the joint. In this work, we used a mouse model of osteoarthritis to show that decreasing inflammatory signaling, through removal of CD14, protects against subchondral sclerosis, due to an increased presence of osteoclasts, cells that combat bone thickening. Osteoclasts without CD14 differentiate faster than osteoclasts with CD14, due to decreased Type I Interferon, an inflammatory cytokine. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/705094v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@176bdd5org.highwire.dtl.DTLVardef@a914bborg.highwire.dtl.DTLVardef@902748org.highwire.dtl.DTLVardef@2f9b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background: immune dysregulation underlies cardiovascular risk excess in systemic autoimmune diseases, such as rheumatoid arthritis (RA) and Sjogren disease (SjD). However, exact mediators are unknown. Regulatory autoantibodies targeting G protein coupled receptors, including CXCR3, have emerged as modulators of immune and vascular homeostasis, but their role in autoimmunity remains ill defined. Our aim was to evaluate antiCXCR3 levels in systemic autoimmunity and their potential value as biomarkers. Methods: antiCXCR3 IgG serum levels were quantified in early RA (n=84), clinically suspect arthralgia (n=12), and controls (n=65). Established RA (n=103) and SjD (n=44) were recruited for validation. Atherosclerosis was assessed by carotid ultrasound. Cytokines were measured by multiplex immunoassays. Cardiometabolic related proteins were evaluated using high-throughput targeted proteomics. Publicly available datasets were used for validation. Results: antiCXCR3 antibodies were significantly reduced in early RA and arthralgia compared with controls, independently of disease activity, autoantibodies, or systemic inflammation. This finding was confirmed in validation cohorts. AntiCXCR3 were negatively associated with good therapeutic outcomes upon csDMARD at 6 and 12 months. Lower anti-CXCR3 levels were independently associated with atherosclerosis occurrence and extent across conditions. Incorporating antiCXCR3 into mSCORE improved risk stratification. AntiCXCR3 were related to proteomic signatures linked to immune activation and to apoptosis, chemotaxis, and cell adhesion in an atherosclerosis dependent manner. Transcriptomic analyses indicated compartment specific CXCR3 dysregulation. Conclusion: reduced antiCXCR3 antibodies represent a shared hallmark bridging systemic autoimmunity and atherosclerosis burden, shaping our understanding on the regulatory role of antibodies at the vascular immune interface. Clinical translation of anti-CXCR3 antibodies hold promise to improve risk stratification.

BackgroundPain is one of the most prevalent and distressing symptoms in juvenile idiopathic arthritis (JIA) and often persists despite treatment. Damage-associated molecular patterns (DAMPs), such as high mobility group box 1 (HMGB1) and S100A8/A9, have been implicated in inflammatory activation and nociceptive sensitization, but their associations with pain are not fully characterized in JIA. MethodsPlasma and paired synovial fluid (SF) samples were obtained from patients with oligoarticular and polyarticular JIA from the Juvenile Arthritis Biobank (JABBA). A discovery cohort (n = 79) was used to investigate associations between biomarkers and pain, and these associations were subsequently examined in a validation cohort (n = 38). Levels of HMGB1, S100A8/A9, IL-6, IL-8, C2C, and TRAP5b were measured using ELISA. Associations between biomarkers and patient-reported pain scores were assessed using multivariable linear regression analyses. ResultsPlasma and SF levels of most biomarkers did not show significant correlations, except for TRAP5b, which demonstrated a moderate correlation. In the discovery cohort, as multivariable linear regression analyses, both CRP and SF HMGB1 ({beta} = 1.14, 95% CI: 0.21-2.08; {beta} = 1.54, 95% CI: 0.06-3.01 respectively in fully adjusted model) were independently associated with higher pain scores. SF S100A8/A9 ({beta} = 1.00, 95% CI: 0.10-1.89) was additionally associated with pain in fully adjusted models. Sensitivity analyses confirmed the robustness of these findings. These associations were further supported in the validation cohort. ConclusionsPain in JIA is associated with both systemic CRP and local alarmin markers, with SF HMGB1 showing a particularly robust association. These findings highlight the importance of local joint HMGB1 in pain mechanisms and suggest a potential role for DAMP-mediated pathways in persistent pain in JIA.

BackgroundDespite advances in therapy, optimal management of juvenile idiopathic arthritis (JIA) remains challenging. The ability to predict disease progression in JIA can improve personalized treatment decisions, but few reliable clinical predictors have been identified. We developed machine learning approaches to predict disease trajectories in children with JIA. MethodsUsing data from the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry (years 2015-2024), we developed machine learning models to predict attainment of inactive disease in children with non-systemic JIA. We applied Dynamic Bayesian Networks (DBN) to model temporal dependencies and causal relationships, and Convolutional Neural Networks (CNN) to capture complex non-linear patterns. Model input included demographic factors, longitudinal clinical factors, and medication use in the preceding 12 months. FindingsA total of 8,093 participants were included. When tested on an independent test cohort, both DBN (AUC:0.76; precision:0.73; recall:0.83; F1-score:0.78; accuracy:0.71) and CNN (AUC:0.76; precision:0.71; recall:0.63; F1-score:0.67; accuracy:0.70) models achieved comparable performance in predicting inactive disease. Disease activity levels in the preceding 12 months, presence of enthesitis and uveitis were the strongest predictors. Causal relationships captured in the DBN model revealed suboptimal care patterns, likely shaped by insurance constraints and a predominantly reactive approach to JIA management. InterpretationOur study demonstrates that machine learning approaches can predict disease trajectories in JIA with good discriminative performance. Unlike prior studies that predict outcomes at single timepoints, our models are the first to predict inactive disease longitudinally. However, suboptimal care patterns in retrospective data limit models capacity to learn treatment-outcome relationships, underscoring critical opportunities to improve JIA care and the need for prospective comparative studies to better inform prediction models. FundingPatient-Centered Outcomes Research Institute (PCORI) Award (ME-2022C2-25573-IC). RESEARCH IN CONTEXT Evidence before this studyNumerous studies have sought to identify clinical predictors of JIA progression and outcomes. However, few reliable predictors have emerged and existing prediction models demonstrate limited performance. As a result, our ability to personalize treatment decisions based on individual risk of severe disease course remains limited. Added value of this studyWe developed novel machine learning models that predict individualized disease trajectories in children with polyarticular and oligoarticular JIA using data from their preceding 12-month clinical course. These models demonstrated strong discriminative performance and outperformed previously published machine learning approaches in JIA. Unlike prior studies limited to single time-point predictions, our models are the first to predict inactive disease longitudinally, enabling a patient-specific projection of disease progression over time. Importantly, our findings also bright to light patterns of suboptimal care, likely driven by insurance constraints and a reactive treatment paradigm, underscoring critical opportunities to improve JIA management. Implications of all the available evidenceOur models have the potential to support clinical decision-making by enabling early identification of children with JIA at risk for unfavorable disease trajectories. In addition, the suboptimal care patterns and systems-level barriers identified through our analyses highlight priority areas for quality improvement initiatives and policy interventions to reduce gaps in JIA care delivery.