RMD Open

ObjectivesTo assess whether baseline ESR-CRP difference (D score) is associated with discontinuation due to loss of efficacy during Janus kinase inhibitor therapy after biologic failure in rheumatoid arthritis. MethodsSingle-centre retrospective cohort of 24 patients with rheumatoid arthritis who initiated a Janus kinase inhibitor after inadequate response to at least one biologic DMARD. D score was ESR (mm/h) minus CRP (mg/L). The primary outcome was discontinuation due to loss of efficacy; other discontinuations were censored. Kaplan-Meier curves and Cox models were used. ResultsSeven patients discontinued due to loss of efficacy. After dichotomisation at the median D score (20.3; n = 12 per group), 1-year LOE-free persistence was 90.9% in the high D group and 43.2% in the low D group (log-rank p = 0.004). The hazard ratio per 10-unit increase was 0.47 (95% CI 0.29 to 0.76; p = 0.002) and 0.41 after age adjustment (0.22 to 0.74; p = 0.003). ConclusionsBaseline D score was associated with lower risk of discontinuation due to loss of efficacy. Larger studies are needed. Key messagesO_LILoss-of-efficacy discontinuation tended to cluster in patients with low ESR and low CRP at baseline. C_LIO_LIHigher baseline D score was associated with fewer loss-of-efficacy discontinuations during JAK inhibitor therapy. C_LIO_LID score from ESR and CRP may complement post-biologic treatment decisions, pending external validation. C_LI

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.

Predictors of Health-Related Quality of Life in Indonesian Women with Systemic Lupus Erythematosus: A Cross-Sectional Within-Cohort Analysis ObjectiveThis study aims to determine the effects of sleep quality along with age, marital status, socioeconomic status, depression, anxiety, disease activity, pain scale, and dose of corticosteroids on quality of life in women with SLE. MethodsVariables were assessed in 75 women with SLE using the Pittsburgh Sleep Quality Index (PSQI), Lupus Quality of Life (Lupus QoL), Depression, Anxiety, and Stress Scale-21 (DASS-21), and Mexican SLE Disease Activity Index (MEX-SLEDAI). Bivariate and multivariate analyses were performed to determine contributors to quality of life. ResultsOf 75 subjects, 35 (46.7%) patients had poor sleep quality. The mean QoL score for patients is 84.27. Poor sleepers had impaired QoL in physical health (p = 0.003), emotional health (p = 0.007), pain (p = 0.003), and planning (p = 0.006), with fatigue (p < 0.0001) as the most significantly impaired. Younger age (Mean {+/-} SD = 81.1 {+/-} 12.67; p = 0.014) and anxiety or depression (Mean {+/-} SD = 56.66 {+/-} 8.17; p = 0.006) were significantly associated with lower quality-of-life scores. The linear regression results showed an R-squared of 0.361, with anxiety ({beta} = 21.402), sleep quality ({beta} = 8.392), and age ({beta} = 5.526) as the most significant variables. Marital status, socioeconomic status, disease activity, pain scale, and corticosteroid dose did not correlate with QoL. ConclusionPoor sleep quality, anxiety, and younger age were significant independent predictors of lower QoL in women with SLE, explaining 36.1% of the variance. These findings suggest that psychosocial and sleep interventions are crucial for improving well-being in this population, potentially more so than focusing solely on disease activity. Summary Box: Key MessagesO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LISystemic Lupus Erythematosus (SLE) significantly diminishes health-related quality of life (HRQoL), particularly in Asian populations where severe organ involvement is more prevalent. C_LIO_LISleep disturbances affect a large majority of SLE patients globally (approximately 62%) and are closely linked to psychological distress and fatigue. C_LIO_LITraditional management focuses heavily on controlling systemic disease activity and organ damage, yet these clinical markers often correlate poorly with patient-reported well-being3. C_LI What does this study add?O_LIIn this cohort of Indonesian women with SLE, nearly half (46.7%) reported poor sleep quality. C_LIO_LIMultivariate analysis identified anxiety/depression ({beta} = -21.402), poor sleep quality ({beta} = - 8.392), and younger age ({beta} = 5.526) as the most significant independent predictors of lower HRQoL, collectively explaining 36.1% of the variance. C_LIO_LIFatigue was identified as the HRQoL domain most severely impaired by poor sleep quality. C_LIO_LINotably, in patients with predominantly low disease activity, markers like the MEX-SLEDAI and corticosteroid dose did not significantly impact HRQoL, highlighting a "disconnect" between clinical control and patient-perceived health. C_LI How might this study affect clinical practice?O_LIThe findings advocate for a shift in the SLE management paradigm from purely inflammatory control toward a multidisciplinary approach that includes routine screening for sleep quality and psychological health. C_LIO_LIClinicians should prioritize interventions such as Cognitive-Behavioral Therapy for Insomnia (CBT-I) and anxiety management, especially for younger patients who may experience greater disruption to life milestones. C_LI

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.

Autoimmune inflammatory myopathies (AIM) with prominent B cell aggregates (BCM) on muscle biopsy is an uncommon finding. We aimed to compare the characteristics and clinical course of patients with BCM on muscle biopsy to those without and characterize B cell infiltrates in the muscle of these patients. We performed a retrospective study of subjects with AIM in the Canada Inflammatory Myopathy Study (CIMS) cohort to identify cases with BCM on muscle biopsy, which was defined as [&ge;]30 CD20+ cells/aggregate. AIM cases without BCM that encompassed the broader spectrum of AIM, namely dermatomyositis, overlap myositis and inclusion body myositis were selected as controls. Descriptive statistics were used to compare BCM cases and controls. Cyclic immunofluorescence (Cyc-IF) was performed to characterize inflammatory infiltrates and B cell structures. We included 69 subjects (mean age at diagnosis 51{+/-}16 years, 77% females): 22 BCM, 24 dermatomyositis, 14 overlap myositis, and inclusion body myositis. Most BCM subjects (18/22, 82%) had an associated autoimmune disease: 12 (55%) had systemic sclerosis, 5 (23%) rheumatoid arthritis and one (5%) systemic lupus erythematosus/systemic sclerosis overlap. Extra-muscular features found in BCM patients included arthritis (50%), interstitial lung disease (43%), Raynauds phenomenon (32%), and dermatomyositis rash (27%). Two patients (9%) had facial muscle weakness and one (5%) had positive anti-AChR autoantibodies. In BCM subjects, upper extremities were weaker than lower extremities in 7/21 (33%) of cases. Neck flexor weakness was frequent (17/22, 77%), while neck extensor weakness was uncommon (1/15, 7%). Cyclic immunofluorescence (Cyc-IF) spatial analysis of BCM biopsies displayed many features akin to tertiary lymphoid structures. Findings suggest possible involvement of both the traditional germinal center reaction and the extrafollicular pathway in BCM. In conclusion, in this series of myositis with B cell aggregates reported to date we found clinical similarities (i.e., associated with overlapping autoimmune diseases) and differences (i.e., muscle weakness distribution) with previous reports. The discovery of tertiary lymphoid structures on spatial analysis of muscle biopsies of BCM patients provides novel insight into its pathophysiology and potential therapeutic targets.

ObjectivesWhether febuxostat is associated with an increased cardiovascular risk compared to allopurinol in patients with gout remains controversial, with major randomized trials reporting conflicting results. This study aims to perform a comprehensive meta-analysis using reconstructed individual participant data (IPD) to evaluate the time-varying cardiovascular and mortality risk of febuxostat versus allopurinol in gout. MethodsWe conducted a one-stage individual participant data meta-analysis. PubMed, Embase, and Cochrane Library were searched up to November 2025 for randomized controlled trials and propensity score-matched observational studies reporting Kaplan-Meier curves for cardiovascular risk or all-cause mortality. Individual patient data were reconstructed from published curves. Time-varying hazard ratios (HRs) were estimated using a mixed-effects Cox model with treatment-by-time interaction across pre-specified intervals (0-12, 12-24, 24-48, >48 months). ResultsFour studies (n=19,090) were included. Analysis revealed significant time-varying effects. For cardiovascular risk, HRs were 0.89 (95% CI 0.79 to 0.99) at 0-12 months, 0.58 (0.50 to 0.68) at 12-24 months, 0.86 (0.74 to 0.99) at 24-48 months, and 1.09 (0.81 to 1.46) after >48 months. For all-cause mortality, HRs were 0.70 (0.62 to 0.79), 0.39 (0.33 to 0.45), 0.75 (0.65 to 0.86), and 1.02 (0.77 to 1.34) across the same intervals, respectively. ConclusionThe cardiovascular and mortality risk of febuxostat relative to allopurinol is time-dependent, showing a significant early reduction that attenuates over time. These findings advocate for a time-aware approach to clinical management and monitoring.

BackgroundGout is the among the most prevalent arthritides worldwide and is associated with high morbidity, cardiovascular risk, and substantial healthcare burden. Despite effective urate-lowering therapies (ULT), many patients remain undertreated, particularly those with severe or complex disease. Nurse-led gout management has improved outcomes in primary care, but data in multimorbid tertiary center populations are lacking. ObjectiveTo evaluate the effectiveness of a supervised nurse-led gout clinic in achieving and maintaining serum urate (UA) targets in a tertiary hospital cohort. MethodsIn this observational study at University Hospital Bern (May 2023-Jan 2026), 69 patients with confirmed gout were enrolled. Patients were assigned to UA targets of <300 {micro}mol/L (Group 1: severe gout) or <360 {micro}mol/L (Group 2: non-severe gout). An advanced Practice Nurse (APN) provided education, a rheumatologist provided pharmacological management per 2020 ACR guidelines. UA levels, flare frequency, prophylaxis, and treatment adjustments were monitored, with follow-up at six and twelve months. ResultsGroup 1 required higher allopurinol doses than Group 2 (p<0.01). UA targets were achieved in 82% of Group 1 regimens and 68% of Group 2. Flare rates and prophylaxis use were comparable. At six and twelve months, 62-67% of Group 1 and 83-88% of Group 2 maintained UA targets. Failures were often due to external treatment modifications. No major ULT-related adverse events were observed. ConclusionSupervised nurse-led gout management effectively achieves UA targets in this "difficult-to-manage" cohort. Maintaining UA targets may benefit from shorter follow-up intervals and enhanced education for patients and healthcare providers.

Background and AimFibromyalgia is an idiopathic chronic widespread pain syndrome affecting 2-4% of the general population globally. Besides widespread fibromyalgia pain, morning stiffness, associated neurologic as well as sleep problems are also reported. Disease is more prevalent in females of middle-age group with low socioeconomic status, thus deteriorating overall productivity and psychosocial health. There is no permanent cure of the disease. This study aimed to explore, validate and assess the effect of four weeks of supervised yogic intervention on pain status, quality of life, sleep, cortical excitability, flexibility and range of motion in fibromyalgia patients, as compared to standard therapy. MethodCase-control study, interventional study and assessor-blined randomized controlled trial, conducted in 120 fibromyalgia patients (60 yoga group: 60 waitlisted controls) and 60 age-matched healthy controls. Pain was assessed subjectively, using questionnaires and objectively, using quantitative sensory testing and ELISA. Sleep and quality of life were assessed using common and disease specific decsiptors. Flexibility and range of motion was assessed using sit and reach box, lateral goniometry and modified Schobers test. Transcranial magnetic stimulation on M1 was used to assess corticomotor excitability of participants. Study parameters were assessed at baseline and after four weeks of the intervention. ResultsA significantly poor sleep, flexibility and quality of life was reported in the fibromyalgia patients due to excruciating pain (VAS = 6.92{+/-}0.12); corticomotor function was also abnormal in the patients, which were restored after four weeks of yogic intervention. On subjective and objective assessment of pain, we found significant relief and improvement in pain status in the yoga group as compared to the waitlisted controls. Fibromyalgia impact, sleep, quality of life and flexibility were also found solely better in fibromyalgia patients undergoing yogic interventions. Cortical parameters, specifically RMT, MEPs and MEP recruitment curves showed a significant improvement in yoga group as compared to waitlisted controls. ConclusionFour weeks of regular and supervised yogic intervention may ameliorate pain, improve flexibility and range of motion and changes cortical plasticity in the Indian cohort of fibromyalgia patients, as compared to standard therapy. Yoga-based interventions can also improve overall quality of life and sleep impairmentsby reducing catastrophization and fibromyalgia impact.

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.

IntroductionPain is often persistent in patients with inflammatory arthritis (IA). There is limited research on pain mechanisms in early IA. We used detailed assessments to characterise pain types longitudinally. MethodsThis prospective observational study investigated the relative contribution of peripheral versus centrally mediated pain in newly diagnosed IA patients with pain scores [&ge;]3, followed over two years. Assessments included: disease activity (Disease Activity Score-28, musculoskeletal ultrasound); quality of life (Musculoskeletal Health questionnaire); mental health status (Patient Health Questionnaire Anxiety, Depression Scale) and pain characteristics (Fibromyalgia criteria, painDETECT, Static and Dynamic Quantitative Sensory Testing). Mixed-effects regression models examined longitudinal associations. ResultsAmong 66 participants (all baseline pain NRS [&ge;]3), pain decreased significantly in the first six months, with smaller, non-significant reductions thereafter. At 24 months, 49% still reported pain (NRS [&ge;]3) and 25% showed no pain improvement. Those with pain had higher baseline and longitudinal scores for centrally mediated pain (fibromyalgia severity, painDETECT) and psychological distress, despite similar baseline inflammation and similar reductions over time. Both baseline and longitudinal inflammation was not associated with subsequent pain (b -0.05, 95% CI -0.67 to 0.56), whereas higher centrally mediated pain markers predicted less pain reduction (b 1.41, 95% CI 0.83-1.99, p<0.001). ConclusionIn our early IA cohort, despite reductions in inflammation half of patients reported persistent pain, primarily driven by centrally mediated mechanisms. Early identification and treatment of this group may improve long-term outcomes. Key messages- This is the first longitudinal study assessing relative contributions of inflammation and centrally mediated pain features in early IA. - Despite reductions in inflammation half of patients reported persistent pain, primarily driven by centrally mediated mechanisms. - Early assessment and treatment of non-inflammatory pain mechanisms may improve long-term pain outcomes.

ObjectivesMosaic chromosomal alterations (mCAs) increase with age and are associated with many diseases, including autoimmune diseases. The associations between mCAs and systemic sclerosis (SSc) and its clinical subtypes have not been explored. MethodsWe recruited study subjects from two independent datasets (Set 1: 635 SSc, 4,401 controls; Set 2: 347 SSc, 2,170 controls) and detected mCAs (Loss, LOH, Gain, and mLOX) from their peripheral blood samples. Logistic regression analyses were conducted with covariates in each cohort, and the results were meta-analyzed. We also conducted stratified analyses by age groups, the age at disease onset, clinical phenotypes based on the skin lesions, autoantibody profiles, the presence of complications. ResultsWe observed a trend of increased Loss in SSc, especially in old age (P=0.0063). The association of Loss was strengthened in certain subtypes of SSc, including lcSSc (OR=2.22, P=0.019) and SSc with vascular complications (digital ulcers, pulmonary hypertension, or renal crisis, OR=3.30, P=0.0054). The effect sizes of Loss increased in patients with high cell fractions (CFs). We also observed that mLOX was significantly associated with SSc, lcSSc, and ACA-SSc only for subjects with high CFs. mLOX was significantly associated with lcSSc and ACA-SSc even compared with dcSSc and ATA-SSc, respectively. These associations were consistently observed in each of the two data sets. Finally, we identified majority of the associations of Loss were mainly driven by SSc with late age at onset. ConclusionsLoss and mLOX were significantly and differentially associated with SSc and its subtypes, underscoring potential phenotype-specific contributions of mCAs. WHAT IS ALREADY KNOWN ON THIS TOPICO_LISystemic sclerosis (SSc) is a heterogeneous disease, with its phenotypes and disease outcomes varying among patients. C_LIO_LIAge-related mosaic chromosomal alterations (mCAs) in blood and subsequent clonal haematopoiesis are associated with various adverse health outcomes. C_LIO_LImCAs have also been linked to several immune-mediated diseases, such as LORA, and hence may influence immune cells and their functions. C_LI WHAT THIS STUDY ADDSO_LIAutosomal copy-number loss (Loss) is increased in SSc in aged subjects. C_LIO_LILoss was associated with lcSSc, ACA-SSc. ILD-SSc, and VC-SSc in a dose-dependent manner of cell fraction. C_LIO_LImLOX was associated with SSc and its subtypes only in patients with high cell fraction. C_LIO_LILate-onset SSc and its subtypes show stronger associations with Loss with higher effect sizes compared to non-late onset SSc. C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYO_LIOur study facilitates further research to recapitulate the current findings in independent cohorts as well as in different ancestries. C_LIO_LIIncorporating profiles of Loss and mLOX in blood into conventional clinical information may enable a better stratification of SSc patients and the development of a better management strategy. C_LIO_LIFurther experimental approaches, such as whole genome sequences and single-cell C_LI RNA sequences, that investigate the underlying molecular mechanisms of phenotypic heterogeneity of SSc driven by Loss and mLOX are also warranted.

ObjectiveRegular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis (RA). Scoring systems to quantify such damage, such as the widely used Sharp/van der Heijde (SvdH) score, are limited by the requirement of time and experienced staff as well as intra- and inter-rater variability. To alleviate these problems, autoscoRA, a fully automated scoring system to assign SvdH scores to radiographs of the hands and feet was developed. MethodsUsing the hitherto largest dataset of adult rheumatoid arthritis patients, autoscoRA, a deep learning-based system, was trained to automatically perform joint extraction and scoring of joint space narrowing and bone erosion. ResultsThe dataset included 769 patients (155 of which in the test set) with 3437 visits (707) and 12144 radiographs (2507). The model reached excellent agreement with a human scorer for joint space narrowing, erosion, and combined scores both on the joint level and for summed total SvdH scores (ICC 0.9). On a subset of data scored by a second human reader, the model outperformed the former in terms of agreement with the first human reader. In addition, autoscoRA demonstrated good agreement with a human reader for detecting longitudinal progression of joint damage across different SvdH score cut-offs defining the presence of progression (average agreement of 70 %). ConclusionAutomated systems like autoscoRA could be used to facilitate scoring of radiographic joint damage in clinical trials, registries and observational studies, and, eventually, routine clinical care.

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.

BackgroundHaploinsufficiency of A20 (HA20) is an immune dysregulation disorder caused by loss-of-function TNFAIP3 mutations. This international multicenter study aimed to delineate its clinical spectrum, genetic basis, and natural history. MethodsA cross-sectional, retrospective analysis was conducted in HA20 patients with pathogenic or likely pathogenic TNFAIP3 variants. Clinical, laboratory and treatment data were assessed. Clustering analysis was applied to evaluate clinical features and disease phenotypes. Patients were stratified by age (< 16 years vs [&ge;] 16 years), country of origin (China vs U.S.), and gender. ResultsA total of 185 patients from 41 clinics across 7 countries were included (median onset 3.3 years). Common clinical features were mucocutaneous involvement (80.5%), recurrent fever (63.3%), gastrointestinal symptoms (58.6%), cytopenias (56.6%), arthritis/arthralgia (46.7%), and recurrent infections (35.5%). Compared with adults and patients from the U.S. cohort, intestinal ulcers were significantly more frequent in children and patients from the Chinese cohort (P = 0.002 and P < 0.0001, respectively), whereas uveitis was less common in these groups (P = 0.001 and P < 0.0001, respectively). Hierarchical clustering of clinical disease phenotypes based on Pearson distance identified two major clusters, an autoinflammation-predominant phenotype and an autoimmune-predominant phenotype. The autoinflammation-predominant phenotype was more common in children and patients from the Chinese cohort (P = 0.033 and P = 0.003, respectively). A total of 89 pathogenic TNFAIP3 mutations were identified, including 46 novel variants. Large deletions were associated with neurologic disease and developmental delay (P = 0.0054 and P = 0.0245, respectively); however, there were no clear association between disruptions of specific functional A20 domains and onset age or phenotype. Therapeutically, TNF and IL-1 inhibitors were effective in most patients, with thalidomide and JAK inhibitors used in refractory cases; 51.5% had achieved minimal disease activity at the most recent follow-up. ConclusionsHA20 is a common dominantly inherited immune dysregulation disorder with phenotypic heterogeneity and potential age-dependent evolution. This large international cohort highlights diagnostic and therapeutic strategies to advance evaluation and management of HA20.

BackgroundCardiovascular (CV) disease risk is increased in rheumatoid arthritis (RA) and is the leading cause of mortality. Improved CV risk stratification tools in RA could enhance use of preventative care and improve outcomes. MethodsWe previously studied biomarkers of CV disease - adiponectin, hsCRP, Lp(a), osteoprotegerin (OPG), high-sensitivity cardiac troponin T (hsTnT), serum amyloid A (SAA), YKL-40, soluble TNF receptor1 (sTNFR1) -- that were associated with CV risk. In the current study, these biomarkers were tested in an unrelated external cohort of RA patients followed at a single academic medical center without a history of CV events. CV events were identified through Medicare and Medicaid administrative data or through medical record review of self-reported events. Biomarkers were assessed at cohort entry among a nested cohort of cases and controls, matched 1:1 on sex and age. Analyses were conducted using conditional logistic regression. We examined whether the candidate biomarkers added to clinical CV risk factors improved model prediction, using the area under the curve (AUC) as well as the net reclassification index (NRI). ResultsFrom a cohort of 1,345 eligible patients with RA, we identified 123 patients with confirmed CV events. Cases and matched controls were typical of RA: median age 63 years, 77% women, RA disease duration 11 years, 72% seropositive, 85% used a biologic or conventional disease modifying anti-rheumatic drug, 58% non-steroidal anti-inflammatory drugs, and 30% oral glucocorticoids. From the candidate biomarkers, LASSO regression selected hsTnT and sTNFR1 as associated with CV events. The AUC for models that included only clinical risk factors was 0.758 (95% CI 0.689-0.829); after adding hsTnT and sTNFR1, the AUC increased to 0.802 (95% CI 0.718-0.998). The NRI of the model with biomarkers was 16.3%, with improvement only observed in patients who did not have CV events during follow-up. ConclusionsAdding selected biomarkers to clinical risk factors enhances the discrimination of models predicting CV events among patients with RA. These risk models require prospective testing to see if they have value in clinical practice decision-making regarding preventative care.

Systemic autoimmune rheumatic diseases (SARDs) are a heterogeneous group of autoimmune conditions characterized by immune system dysregulation leading to chronic inflammation and tissue damage. The overlapping clinical manifestations make differential diagnosis challenging, highlighting the need for novel biomarkers to facilitate early diagnosis, stratification, and personalized treatment. Five SARDs including idiopathic inflammatory myopathies (n=210), rheumatoid arthritis (n=84), systemic sclerosis (n=100), Sjogren disease (n=99), and systemic lupus erythematosus (n=99), as well as healthy controls (n=400) and controls with acute infectious diseases (n=218) were selected for plasma protein profiling using Olink Explore 1536. Proteins with known association to SARDs as well as novel associations were identified through differential abundance analysis and machine learning. This explorative cross-sectional study demonstrates the importance of a pan-disease approach to biomarker identification within and between the five SARDs. NPX boxplots from this study are available open-access through the Human Protein Atlas, facilitating further plasma-proteome research on autoimmune diseases.

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.

Autoimmune demyelinating central nervous system (CNS) disorders encompass a wide array of clinical entities ranging from the organ specific Multiple Sclerosis (MS) to systemic autoimmune diseases (SADs) such as Systemic Lupus Erythematosus (SLE) and Sjogrens syndrome (SS). Despite international research efforts, distinction of these entities at clinical, imaging and laboratory level remains challenging, with almost 20% of patients being misdiag-nosed with MS, out of which more than 50% carry the misdiagnosis for at least 3 years, while 5% are misdiagnosed for 20 years or more. This work aims to identify early biomarkers that can discriminate MS from other clinical entities that are MS mimickers. For this reason, we have meticulously curated a unique biobank with serum, DNA, RNA, and cerebrospinal fluid (CSF) samples from 396 treatment-naive patients who presented with a demyelinating episode and for which we have recorded over 300 clinical, serological, and imaging parameters. These patients have undergone follow up at 6 months and 12 months from their first demyelinating episodes and have been categorised as follows: MS, SAD with CNS involvement, and demyelination with autoimmune features (DAF). A hybrid model for semi-supervised tabular classification is proposed that integrates a graph attention network with dynamic graph learning via Random Forest proximity and k-NN graphs with tabular prior-data fitted network for direct classification. The model also performed feature selection, self-supervised contrastive learning, self-training and data augmentation.

ObjectiveSystemic lupus erythematosus (SLE) is characterized by persistent type I interferon (IFN) signaling and adaptive immune dysregulation. We previously identified hypomethylation of HLA-DRB1 and STAT1 in SLE CD8+ T cells, enabling aberrant IFN-driven HLA-DRB1 expression and expansion of a distinct CD8+ T cell subset. This study aimed to comprehensively characterize CD8+ HLA-DRB1+ T cells in lupus. MethodsPeripheral blood CD8+ T cells from SLE patients and healthy controls were analyzed by flow cytometry to assess differentiation and effector functions. Single-cell RNA sequencing and TCR sequencing, with and without IFN- stimulation, were used to assess transcriptional heterogeneity, exhaustion, senescence, and cytotoxicity. ResultsCD8+ HLA-DRB1+ T cells were enriched within effector memory and terminally differentiated CD8+ T cells and were significantly expanded within the effector memory compartment in SLE compared to healthy controls. These cells displayed paradoxical features of cytotoxic activation, proliferative potential, exhaustion, and senescence. Compared to healthy controls, lupus CD8+ HLA-DRB1+ T cells exhibited increased exhaustion, reduced cytotoxicity, and impaired viral defense pathways. IFN- treatment enhanced IFN-{gamma} responses in lupus CD8+ HLA-DRB1+ T cells and exacerbated exhaustion and senescence. Despite upregulation of cytotoxic gene expression, IFN- reduced CD107a surface mobilization, indicating impaired degranulation. Analysis of lupus nephritis datasets revealed that most kidney-infiltrating CD8+ T cells express HLA-DRB1. ConclusionCD8+ HLA-DRB1+ T cells represent a cytotoxic yet dysfunctional effector memory population expanded in SLE. Type I IFN drives this paradoxical state by promoting exhaustion and impaired degranulation, highlighting a potential therapeutic axis in SLE.

ObjectiveTo apply large language models (LLMs) to Reddit posts referencing systemic lupus erythematosus (SLE) to identify patient-expressed unmet medical needs, symptom experiences, and healthcare challenges, demonstrating how AI-enabled social media listening complements traditional patient-experience research. MethodsWe extracted 4,633 posts from ten SLE-related or health-focused Reddit communities using the public Reddit API (October-November 2025). After removing duplicates, promotional content, and posts with insufficient information, 2,603 posts remained. A thematic codebook was developed through manual review of 300 posts and iteratively refined. Two LLMs (Gemini 3.0 and GPT-5.2) were evaluated for automated thematic labeling using percent agreement, Cohens {kappa}, and a human-annotated reference set (n=100). The best-performing model was used to quantify theme prevalence, followed by qualitative review of representative narratives. ResultsGPT-5.2 demonstrated higher performance (F1=0.844) than Gemini 3.0 (F1=0.811), with substantial inter-model agreement across main themes (mean {kappa}=0.71). Posts reflected multidimensional experiences. The most frequent subtheme was Advice Seeking (84.1%), followed by Emotional Coping (55.6%). Common symptom-related themes included Pain (37.2%), Other Symptom Presentations (37.6%), Fatigue (24.7%), and Acute or Worsening Flares (30.2%). Diagnostic uncertainty was prominent, including confusion about laboratory results (24.0%) and emotional impact of uncertainty (33.0%). Qualitative review highlighted emotional distress, reliance on peer communities for interpretation of symptoms and labs, and difficulty managing complex treatment regimens. ConclusionLLM-enabled social media listening offers a scalable method for synthesizing large volumes of unstructured patient narratives, providing timely insights into lived experiences and unmet needs among individuals discussing lupus online. Findings align with established qualitative literature while highlighting persistent gaps in patient education, communication, and care coordination. This analytical framework can be applied across disease areas to support patient-centered care, measurement development, and evidence generation relevant to therapeutic and health-services research. What is already known on this topicO_LIPeople living with systemic lupus erythematosus (SLE) experience substantial unmet needs related to diagnostic uncertainty, symptom burden, emotional distress, medication challenges, and healthcare system barriers. C_LIO_LITraditional qualitative methods (e.g., interviews, focus groups, surveys) capture valuable patient perspectives but are limited by small sample sizes, recall bias, and restricted question frameworks. C_LIO_LISocial media listening has emerged as a promising way to collect real-time patient insights, and recent regulatory guidance acknowledges its value as patient experience data. However, systematic, scalable analysis of large patient-generated datasets has historically been constrained by analytic burden and variability. C_LI What this study addsO_LIThis study is among the first to apply state-of-the-art large language models (LLMs) to a large corpus of SLE-related social media posts, enabling scalable thematic analysis of thousands of patient narratives. C_LIO_LIIt provides a validated methodological framework for using dual-LLM agreement, human-annotated references, and performance benchmarking (precision, recall, F1) to ensure reliability in automated thematic labeling. C_LIO_LIFindings reveal a multidimensional patient burden consistent with prior studies while uncovering persistent gaps in patient education, confusion around laboratory testing, care coordination challenges, and heavy reliance on peer communities for advice. C_LIO_LIThe approach demonstrates that LLM-enabled social media listening can generate timely, granular, patient-prioritized insights at a scale unattainable by traditional methods. C_LI How this study might affect research, practice, or policyO_LIResearch: Establishes a reproducible, scalable framework for integrating LLM-based thematic analysis into patient-focused evidence generation, accelerating insight extraction from large unstructured datasets across disease areas. C_LIO_LIClinical practice: Highlights actionable gaps in patient education, communication, and care coordination, informing interventions to improve clinical encounters, shared decision-making, and symptom management support. C_LIO_LIPolicy and regulatory science: Demonstrates how social media-derived patient experience data, when paired with rigorous quality controls, can complement formal qualitative studies and support patient-focused drug development, measurement development, and health-services planning. C_LI