Arthritis & Rheumatology

Systemic sclerosis (SSc) is a rare, heterogeneous autoimmune disease characterized by immune dysregulation, vasculopathy and fibrosis. While typically sporadic, SSc can in a minority of cases show familial clustering. Whole exome sequencing (WES), performed on six families with two affected members each, identified a total of 253 genes with rare, disease co-segregating variants predicted to affect protein function. Of these, we prioritized PRKD2, one of only three genes identified in two families. PRKD2 encodes Protein kinase D2: an intracellular serine-threonine kinase that amplifies T cell receptor (TCR) signaling. Both familial SSc-associated PRKD2 missense variants increased kinase activation, exerting overlapping, activating effects on TCR signaling in heterozygous knock-in Jurkat cells. A pan-PRKD inhibitor suppressed T cell activation in peripheral blood mononuclear cells from both familial SSc cases and controls. The enrichment of PRKD2 rare variants in a sporadic SSc cohort provides further support for its relevance to SSc pathogenesis. Together, these findings identify PRKD2 rare variants as potential genetic contributors to SSc, and PRKD2-mediated TCR signaling as a candidate disease-relevant and potentially targetable pathway.

Objective: Tissue-specific biomarkers that are reliable and associated with clinical manifestations of idiopathic inflammatory myopathy (IIM) are lacking. The blood circulation in individuals serves as a central conduit, allowing communication between tissues and facilitating clearance and recycling of tissue-derived proteins. Thus we applied a dual antibody-based proximity extension assay to profile the plasma proteome in subtypes of patients with IIM. Methods: Plasma samples from 201 patients diagnosed with IIM at Karolinska University Hospital were analyzed using Olink. Clinical manifestations, disease activity measurements, and laboratory results were collected. First, we evaluated differential protein abundance across IIM subtypes. Then we calculated tissue scores for each disease subtype using tissue gene expression databases. Finally, interferon (IFN) and complement pathway scores were calculated. Results: Plasma from patients with dermatomyositis was enriched for IFN signaling and skin associated proteins, anti-synthetase syndrome (ASyS) for lung associated proteins, immune-mediated necrotizing myopathy (IMNM) for muscle associated proteins, and inclusion body myositis for T cell response proteins. Patients with IMNM showed the highest tissue score for skeletal muscles, and ASyS for lung tissue score. Skeletal muscle scores correlated strongly with muscle disease activity visual analog scale scores, creatinine kinase levels, and muscle weakness score. Patients with interstitial lung disease along with and those with anti-Jo1 autoantibodies showed differential enrichment of surfactant proteins and IFN pathway activation. Conclusions: Circulatory proteome is a promising tool to capture distinct tissue-specific responses that correlate with disease activity and tissue injury in patients with IIM.

Systemic sclerosis (SSc) is an autoimmune connective tissue disease characterized by symmetric fibrosis of the skin and multiple internal organs. The mechanisms that trigger early fibrotic changes remain unclear. Mast cells are known to infiltrate human SSc lesional skin in early disease stages, yet the role of mast cells in initiating fibrosis and pruritus in SSc remains debated, in part due to unclear pathways of mast cell activation. Here, we show that mast cells, via the receptor Mrgprb2, contribute to fibrosis in the bleomycin (BLM)-induced skin fibrosis mouse model. Mast cells accumulate in the skin of BLM-treated wild-type (WT) but not Mrgprb2-knockout (Mrgprb2-/-) mice. Mrgprb2-/- mice show attenuated disease severity, with reduced collagen deposition and lower expression of matrix metalloproteinases and inflammatory markers associated with fibrosis. BLM treatment also increases pruritus in WT mice in the early stages of the model; an effect reduced in Mrgprb2-/- mice. This is the first report of itch in this model of skin fibrosis, further linking it to clinical SSc, where pruritus is an early and prevalent symptom affecting nearly half of patients. In a parallel human cohort, lesional SSc skin harbors significantly more mast cells than paired non-lesional skin from the same patients, demonstrating that mast cell accumulation is specific to affected tissue. Lesional mast cell counts also track with skin disease severity, correlating with modified Rodnan skin score and patient-reported skin tightness. Together, these findings implicate Mrgprb2-mediated mast cell activity in both fibrosis and pruritus in SSc, highlighting mast cells as a candidate therapeutic target in this understudied disease process.

Objective: The principal diagnostic test for rheumatoid arthritis (RA) relies on the detection of anti-cyclic citrullinated peptide (CCP) antibodies. The CCP test exhibits moderate sensitivity and specificity but does not adequately detect a high proportion of cases or effectively distinguish RA from related conditions such as systemic lupus erythematosus (SLE). To discover improved diagnostic biomarkers for RA, we performed a comprehensive proteomic analysis of antibody-bound antigens present in RA, SLE, and healthy control (HC) sera and identified proteins associated with transforming growth factor-beta-1 (TGF-beta-1) signaling and assessed the sensitivity and specificity of antibodies against these antigens in comparison to CCP. Methods: Total antibodies were immunoprecipitated from pooled sera of HC individuals (n=3) and patients with clinically diagnosed RA (n=3) or SLE (n=3). Antibody-bound antigens were identified using multidimensional protein identification technology (MudPIT) shotgun proteomics. Candidate antigens associated with TGF-beta-1 signaling were selected for evaluation, and corresponding serum autoantibodies were assessed for their ability to classify RA using a POC lateral-flow immunochromatographic format. Results: Proteins present in antibody immunoprecipitations included TGF-beta-1-induced protein (TGFBI), thrombospondin 1 (TSP1), serum amyloid A1 (SAA), and fibronectin (FN). POC assays using these candidates, as well as TGF-beta-1 itself, as capture antigens were used to detect corresponding serum autoantibodies in 107 subjects with clinically diagnosed RA, 42 subjects with other rheumatic diseases (non-RA), and 121 HC subjects. Receiver operating characteristic curves were constructed using RA and HC groups to assess diagnostic performance, and optimal cutpoints identified using the Youden Index (maximizing the sum of sensitivity and specificity). CCP test results were determined using previously established thresholds. Using an analysis et of 169 subjects in the HC and RA groups who had values for TGFBI, SAA, and CCP, TGFBI autoantibodies achieved a sensitivity of 82%, specificity of 98.8%, positive likelihood ratio (PLR) of 65.6, and NLR of 0.2. SAA autoantibodies achieved a sensitivity of 92.1%, specificity of 85%, PLR of 6.1, and NLR of 0.1. Both outperformed CCP (sensitivity of 68.5%, specificity of 95%, PLR of 13.7, and NLR of 0.3). Using an analysis set of 120 subjects in the RA and non-RA groups who had values for TGFBI, SAA, and CCP, TGFBI and SAA autoantibodies exhibited sensitivities and specificities of 82 and 92.1% and 74.2 and 45.2%, respectively, compared to 68.5 and 74.2% for CCP. Autoantibodies to TGF-beta-1, TSP1, and FN exhibited only modest diagnostic performance. Conclusion: RA sera contain autoantibodies targeting multiple proteins associated with the TGF-beta-1 signaling pathway that is implicated in inflammatory processes in RA. Among the candidates tested, TGFBI and SAA autoantibodies exhibited the highest diagnostic performance in a POC lateral-flow format, supporting their potential utility as biomarkers for RA diagnosis. These findings also support further investigation of the TGF-beta-1 signaling pathway as a potential therapeutic target in RA.

Abstract Cardiovascular disease (CVD) is a major cause of morbidity and premature mortality in people with rheumatoid arthritis (RA). Whether multidimensional cardiometabolic, inflammatory, renal, behavioral, and psychosocial factors define distinct cardiovascular risk phenotypes in RA remains unclear. This study aimed to identify data-driven phenotypes and evaluate their associations with prevalent CVD. We analyzed 3,252 adults aged over 20 years with self-reported RA from the 2005-2018 National Health and Nutrition Examination Survey (NHANES). Unsupervised partitioning around medoids (PAM) clustering using Gower distance identified distinct data-driven cardiovascular-risk profiles. Cluster validity was assessed using silhouette analysis and internal train test validation. Survey-weighted binary logistic regression evaluated associations between phenotype membership and prevalent CVD. Six clinically interpretable data-driven phenotypes were identified with varying CVD prevalence: Severe Metabolic Diabetic (40.3%), Aging Diabetic Hypertensive (34.9%), Non-Diabetic Intermediate (20.2%), Mild Metabolic (14.8%), Cardiometabolic (10.4%), and Smoking-Predominant (19.4%). Compared with the Cardiometabolic phenotype, the Severe Metabolic Diabetic phenotype exhibited the highest odds of prevalent CVD (aOR 4.11, 95%CI:2.56-6.59), followed by the Aging Diabetic-Hypertensive phenotype (aOR 3.38, 95%CI:2.22-5.15). Higher odds of prevalent CVD were also observed in the Smoking-Predominant (aOR 1.99, 95% CI: 1.26-3.13) and Non-Diabetic Intermediate (aOR 1.77, 95% CI: 1.10-2.84) phenotypes. The six-cluster solution demonstrated moderate separation and strong internal correspondence across training and testing sets, while the phenotype-informed model showed moderate discrimination for prevalent CVD (AUC = 0.72). Among adults with rheumatoid arthritis (RA), distinct data-driven phenotypes were identified based on combined patterns of metabolic, inflammatory, renal, behavioral, and psychosocial factors, with differing burdens of prevalent cardiovascular disease (CVD). Phenotype-based approaches may provide a comprehensive framework for characterizing multidimensional cardiovascular risk in RA.

Giant cell arteritis (GCA) is an immune-mediated vasculitis that can cause serious morbidity including sight loss, stroke and aortic aneurysm. There is an unmet need for blood-based biomarkers and novel therapeutics. We measured plasma protein levels using the SomaScan v4.1 platform, comprising 7,273 protein measurements (SOMAmers) reflecting 6,596 unique protein targets. We profiled the proteome in 113 patients who presented acutely with possible GCA. 56 had biopsy-proven GCA and 57 did not have GCA (non-GCA). We found 144 SOMAmers increased and 151 reduced in GCA. Dysregulated biological pathways included IL6-JAK-STAT3 signalling, chemokines for both myeloid (e.g. CXCL2, CXCL3, CCL18, CCL23) and lymphoid cells (e.g. CXCL9, CXCL13), and the complement system (e.g. C9, CFHR5, C5a, Factor B). Enzyme-Linked Immunosorbent Assays (ELISAs) confirmed elevated plasma levels of C5a, the terminal complement complex, Factor B and CFHR5 in GCA. We developed a 26-protein signature that distinguished GCA from non-GCA (area-under-the curve, AUC, 0.93) and validated the diagnostic signature in external datasets. Our data implicate terminal complement pathway activation in GCA, raising the possibility of complement-directed therapies. We show proof-of-principle that a multiplex protein biomarker could be used as a diagnostic adjunct in suspected GCA.

Fc{gamma}RIIa, encoded by FCGR2A, is a widely expressed Fc receptor implicated in autoimmunity and infectious disease susceptibility. To fine-map the rheumatoid arthritis (RA) association at the complex FCGR locus, we combined gene-specific resequencing, genetic association studies in UK and Spanish European cohorts, functional genomics, structural biology, biophysical analyses, and cellular assays. We identified a common European FCGR2A haplotype (2A.3), defined by Q27W, H131H, and the RA-associated SNP rs12746613, which showed the strongest association with RA. Multi-omics analyses demonstrated that 2A.3 is associated with reduced expression of the soluble FCGR2A splice variant and lower circulating soluble Fc{gamma}RIIa levels. Functional studies revealed altered IgG interactions and delayed Fc{gamma}RIIa signal transduction associated with Q27W, while structural analyses found no evidence for stable ectodomain dimerisation. Together, these findings identify 2A.3 as an important functional contributor to RA susceptibility and provide mechanistic insight into how FCGR2A variation may influence immune regulation and disease risk in Europeans.

Objective: To assess the accuracy of codes and algorithms used to identify selected connective tissue diseases (CTDs) in electronic health records (EHRs) and administrative databases. Methods: We searched MEDLINE, Embase, and CENTRAL databases for studies that validated case definitions in EHRs against a reference standard, including rheumatologist-confirmed diagnosis or clinical classification criteria. Title/abstract screening, full-text review, data extraction, and quality appraisal were independently performed in duplicate. Findings were synthesised narratively and through a bivariate random-effects meta-analysis of sensitivity and specificity. Results: A total of 38 studies were included. Systemic lupus erythematosus (SLE) was the most frequently studied disease, followed by systemic sclerosis (SSc). Across diseases, progressively restrictive algorithms generally improved positive predictive value (PPV), although the optimal strategy varied by disease. In SLE, multiple diagnostic codes provided the most favorable overall performance, whereas adding clinical data provided limited incremental benefit. In SSc, disease-specific clinical features, particularly Raynaud's phenomenon, improved case identification, while specialist or inpatient-based algorithms performed better for polymyositis/dermatomyositis, although evidence was limited. For SLE, meta-analysis yielded pooled sensitivity of 0.90 (95% Cis 0.70-0.97), specificity of 0.83 (95% CIs 0.54-0.95), and PPV of 0.75 (95% CIs 0.59-0.86). Evidence for Sjogren's Disease was limited to one study, and no studies evaluated MCTD/UCTD. Conclusions: Optimal EHR case-identification strategies vary by disease and should be tailored to disease-specific clinical and diagnostic characteristics rather than algorithm complexity alone. Future research should develop and externally validate robust, standardised algorithms in representative populations, using rigorous validation methods, and assess the added value of longitudinal EHR data, biomarkers, and computational phenotyping approaches.

Background: Smartphone enabled remote patient monitoring has the potential to complement conventional follow-up in inflammatory arthritis. We previously presented the finger fold index (FFI) derived from hand photographs as ratio of automated detected proximal interphalangeal (PIP) joint diameter and surface of dorsal finger folds as a digital biomarker for clinical joint swelling and disease activity in rheumatoid arthritis (RA) and psoriatic arthritis (PsA). Objective: To evaluate the feasibility, image quality, patient engagement, and clinical utility of both HCP- and patient-collected hand photographs integrated into a national rheumatology registry, and to assess the performance of the FFI as an image-derived digital biomarker for clinical joint swelling of the proximal interphalangeal joints in a real-world arthritis cohort. Methods: In this longitudinal multicenter study, a photo function with written instructions were integrated into the Swiss Clinical Quality Management in Rheumatic Diseases (SCQM) registry and their mySCQM mobile application, respectively. Patients with RA or PsA contributed longitudinal smartphone photographs together with patient-reported outcomes (PROs) via the mySCQM mobile application while health care professionals (HCPs) acquired images during routine visits. After manual quality assessment, images were processed using an automated computer vision pipeline to derive the FFI, a digital biomarker based on dorsal finger-fold morphology. Image quality was evaluated for both HCP- and participant-collected photographs, and patient engagement was assessed. Associations between FFI, clinical proximal interphalangeal (PIP) joint swelling, RADAI-5, DAS28-CRP and longitudinal changes were assessed. A generalized linear mixed model was used to estimate the association between FFI and joint swelling while accounting for repeated measures and within-subject correlations. Results: Between 2023 and 2025, 374 RA and PsA patients were included. HCPs captured 977 hand images while 174 patients collected 1228 hand images via the mySCQM app. Patients demonstrated sustained engagement after instruction, contributing a mean of seven images during data collection. Following quality control, 1729 hand images comprising 4048 PIP joints were included for analysis. Image quality was comparable between patient-acquired and HCP-acquired photographs; 78.3% of the patient-acquired vs. 73.5% of the HCP-acquired hand images were suitable to run the ML-model. 23.1% of the cropped joints had to be removed after the running of the FFI algorithm due to false diameter or finger fold detection e.g. due to wrong hand positioning. In images taken by HCPs, mean FFI and DAS28-CRP were weakly but significantly correlated (Spearmans {rho} = 0.164; 95% CI [0.004 to 0.317]; p = 0.039). Conversely, RADAI-5 scores did not correlate with the mean FFI in RA patients (r = 0.007, p = 0.932, 95% CI [-0.169-0.183]). At follow-up visits, clinical swelling resolved in 40 joints, of which in 68.0% the direction of the delta FFI was concordant with the clinical change. In contrast, 13 joints developed incident clinical swelling, of which 87.5% had a direction of the delta FFI that was concordant with the clinical change. However, the GLMM showed no significant associations between swelling and joint location or time-varying FFI, and no evidence of interaction between FFI and PIP joint. Conclusion: Integration of patient self-imaging into a remote monitoring application for inflammatory arthritis is feasible and achieves image quality comparable to clinician acquired photographs. The FFI derived from collected images shows association with clinical joint swelling and disease activity scores, but not PROs. In a substantial proportion of images, the FFI algorithm could not be applied because of insufficient image quality. More standardized image acquisition and further refinement of the FFI algorithm are warranted.

Macrophages in the synovial lining are critical for the maintenance of healthy tissue while also contributing to the pathogenesis of rheumatoid arthritis (RA). However, the field currently lacks a unifying characterization of synovial macrophage heterogeneity across steady-state and inflammation. Here, we defined 4 transcriptionally distinct populations of synovial macrophages CX3CR1+MHCII- (lining); CX3CR1-MHCII- (interstitial/sublining); CX3CR1-MHCII+ (monocyte-derived); and CX3CR1+MHCII+ (infiltrating). The MHCII-populations are long-lived and derived from embryonic precursors regardless of localization while the MHCII+ populations differentiate from bone marrow (BM) progenitors dependent on CCR2. We identified conserved activation pathways between acute and chronic mouse models of inflammatory arthritis as well as novel arthritis-associated subpopulations. During peak inflammation, the influx of BM-derived cells was associated with upregulation of monocyte-related genes with concurrent down-regulation of tissue-resident genes. Our results provide a unifying schema for describing synovial macrophages across conditions and pave the way for future studies in modulating transcriptional activity in rheumatoid arthritis.

Osteoarthritis (OA) and systemic sclerosis (SSc) are diseases with distinct etiologies but similar disease phenotypes, most prominently fibrosis, a process governed by the pathological activation of fibroblasts. Mechanisms underpinning fibrosis in these diseases are widely studied, though have yet to be directly compared. We employed single-cell RNA-seq and high-resolution spatial transcriptomics to describe the functional plasticity and the range of fibroblast activation states in both diseases. We identified disease-enriched fibroblast subsets conserved in both diseases, including fibrogenic myofibroblast-like cells, chemokine- and cytokine-expressing inflammatory fibroblasts, and lining-like fibroblasts. These subsets exhibited convergent fibrotic programs also observed in idiopathic pulmonary fibrosis, as well as overlapping osteochondral transcriptional programs. Xenium 5K spatial transcriptomics revealed that conserved, disease-associated fibroblasts reside in highly similar anatomic niches in OA synovium and SSc skin. These consisted of a fibrotic ECM-rich niche harboring myofibroblast-like cells and an inflammatory niche containing inflammatory fibroblasts adjacent to infiltrating immune cells. Disease-associated transcriptional remodeling converged on shared functional pathways and common putative upstream molecular regulators. These findings identify conserved cellular states, spatial niches, and regulatory programs across OA and SSc, suggesting that fibrotic disease is underpinned by shared pathogenic stromal states and candidate targets for therapeutic strategies are applicable across both diseases.

Osteoarthritis (OA) is the most common chronic joint disease and a leading cause of disability worldwide, yet no disease-modifying therapies are available. Although OA has traditionally been viewed as a cartilage-centered degenerative disease, growing evidence suggests that synovial inflammation is a critical driver of disease progression. However, the upstream mechanisms and actionable targets that govern this inflammatory response remain poorly defined. Connexin 43 (Cx43), a key regulator of musculoskeletal homeostasis that forms both gap junctions and hemichannels (HCs), is upregulated in osteoarthritic cartilage and synovium, but the specific contribution of Cx43 channels remains unclear. Here, we show that selective inhibition of Cx43 HCs attenuates OA progression in a murine post-traumatic OA model. Using adeno-associated virus (AAV)-mediated gene deletion, we found that Cx43 knockdown in joint tissues reduced cartilage erosion, synovial hyperplasia, subchondral bone sclerosis, and OA-associated pain. To dissect HC-specific functions, we developed a monoclonal antibody, Cx43(M1), that blocks Cx43 HCs without affecting junctional communication. Cx43(M1) preserved cartilage integrity, suppressed synovial inflammation, and alleviated pain behaviors, even when treatment was initiated after established cartilage damage. Mechanistically, the antibody preferentially localized to synovial macrophages, where it inhibited HC activity, reduced ATP and PGE2 release, and suppressed pro-inflammatory gene expression. Macrophage-specific Cx43 deletion recapitulated these protective effects, and Cx43 HC blockade in primary human OA synovial macrophages similarly inhibited inflammatory and catabolic responses. These findings identify synovial macrophage Cx43 HCs as upstream drivers of OA and support a paradigm shift from a predominantly chondrocyte-centered view toward synovial macrophage directed intervention.

Background: Lumbar disc herniation, with or without concomitant disc degeneration, is a major cause of lumbar radiculopathy and low back pain, which also a key public musculoskeletal disorder without an exact pathophysiology. Studies have suggested that inflammatory cells and biochemical markers of inflammation also play an important role in lumbar radiculopathy in addition to nerve compression. The aim of the present study was to assess the association of selected circulatory inflammatory markers (CRP, hs-CRP and E-selectin) in patients with lumbar disc herniation without radiological degeneration (LDH) and lumbar disc herniation with radiological degeneration (LDHD). Materials & methods: This case-control study included 208 participants, comprising 104 patients with lumbar disc pathology and 104 controls. Patients were further stratified into LDH (n=67) and LDHD (n=37). Serum CRP, hs-CRP and E-selectin concentrations were measured. Results: Among the patients, 35.6 % presented with LDHD while 64.4 % had only LDH. Significantly increased median hs-CRP (p<0.001) and CRP (p<0.001) were observed in patients groups compared to controls, while CRP showing a consistent independent association across the combined disease (OR=1.68, 95% CI=1.33-2.14, p<0.001), LDHD (OR=1.62, 95% CI=1.16-2.20, p=0.005) and LDH (OR=1.69, 95% CI=1.30-2.20, p<0.001) multivariable models. No significant difference was observed in serum E-selectin between the study groups. Multivariable models incorporating inflammatory and clinical variables demonstrated substantially greater discriminatory performance than individual biomarkers alone. Conclusion: Elevated circulating CRP and hs-CRP concentrations were associated with lumbar disc pathology, with CRP showing a consistent independent association across the combined disease, LDH and LDHD multivariable models, whereas E-selectin showed no significant association. Multivariable models incorporating inflammatory and clinical variables demonstrated greater discriminatory performance than individual biomarkers. These findings support a potential systemic inflammatory component in lumbar disc pathology, although the cross-sectional nature of the measurements does not establish causality or a local inflammatory response within the disc.

Objective: Autoantibodies are central for pathology of rheumatoid arthritis (RA) and diabetes mellitus (DM) carrying high predictive and diagnostic value. Here, we explore the frequency and functional potential of DM-related antibodies (DMab) in RA. Methods: DMab targeting glutamic acid decarboxylase (GAD65ab), tyrosine phosphatase-like islet antigen 2 (IA2ab) and zinc transporter 8 (ZnT8ab) were measured in 326 DM-free RA patients (260 females, 66 males), using specific ELISAs. The DMab profile was analysed in relation to 30 clinical and serological variables. ZnT8+ cells were detailed by a public single-cell transcriptome in RA synovial tissue. Results: DMab production was more frequent in females, dominated by ZnT8ab (86%), followed by GAD65ab (26.4%) and IA2ab (7.0%). DMab-positive patients, and specifically ZnT8ab-positive women, had higher levels of insulin and HOMA-IR index and lower serum IL-6, IFN{gamma}, and IL-9. Multivariable logistic regression estimating ZnT8ab, IA2ab, GAD65ab production revealed that BDNF, insulin and DAS28 were positive predictors of ZnT8ab. Increasing ZnT8ab levels were inversely related to RAab in the mixed interaction model. CD14+ cell transcriptome identified association between an activated secretory cell type and increasing ZnT8ab levels. Additionally, ZnT8ab levels were in direct proportion with ZnT8 production in RA CD4+ T cells. Single-cell transcriptome of RA synovial tissue revealed ZnT8+ cells among the lubricin producing lining layer fibroblasts programmed for invasive behaviour. Conclusion: This study reveals frequent production of ZnT8ab in non-diabetic RA patients and identifies their antigenic target expressed in lining synovial fibroblasts of RA joints.

Multiple sclerosis (MS) is approximately three times more common in females than in males, but sex-linked epigenetic mechanisms remain incompletely understood. We tested whether X-chromosome DNA methylation differs in females with MS and whether associated sites preferentially map to genes normally subject to X-chromosome inactivation (XCI). An X-chromosome-focused epigenome-wide association study was performed in whole blood from three datasets comprising 496 females with MS and 509 female controls, with independent evaluation in isolated CD4+ T cells (80 cases, 76 controls). At FDR < 0.01, 3 182 X-chromosome CpGs were hypomethylated in MS (mean {Delta}{beta} = -0.035). Hypomethylated CpGs were strongly enriched in non-escape genes normally subject to XCI relative to escape genes (OR 6.77; p = 1.55x10-57) and mapped to immune and chromatin-related processes. Exploratory cis-mQTL analysis identified strong local genetic effects at a small subset of loci, including WAS, IRAK1 and TLR7. In CD4+ T cells, 2 080 of the 3,182 whole-blood hypomethylated CpGs (65.4%) were also significantly hypomethylated. These findings identify a reproducible X-chromosome hypomethylation signature in female MS and support direct investigation of inactive-X regulation, XCI escape and X-linked immune gene dosage.

Objectives Juvenile idiopathic arthritis (JIA) is a collection of childhood onset rheumatic conditions that more frequently occur in females in most subtypes. Sex influences disease biology, treatment trajectories, and patient outcomes, however, no study to date has investigated the interaction of sex with autosomal genetic risk to JIA. Methods Genotype data from 3748 JIA cases (2551 female, 1197 male) and 9196 controls (5136 female, 4060 male) were analysed using a sex-stratified genome-wide association analysis. Systemic JIA was excluded. HLA imputation and fine-mapping were performed using SNP2HLA. Sex-specific effects were assessed using an omnibus sex-interaction test for multi-allelic amino acid positions. A subtype specific analysis was repeated in rheumatoid factor (RF) negative polyarthritis and oligoarthritis (1862 female, 718 male). Results A sex-combined analysis identified genome-wide significant (P<5x10-8) loci across the HLA region and nine loci outside the HLA region, including a novel association at rs231977 (NUPR1). Markers within the HLA region were significantly sex-dimorphic (P<5x10-8) and nine loci outside of the HLA region were suggestive for sex dimorphism (P<5x10-6), including SPRY2. HLA fine-mapping identified lysine at position 70 of HLA-B conferring greater male JIA risk, and tyrosine at position 10 of HLA-DRB1 conferring greater female JIA risk. Subtype specific analysis strengthened the association of tyrosine at position 10 of DRB1 in females. Conclusions This study provides the first evidence that autosomal genetic risk factors contribute to JIA risk in a sex-dimorphic manner, mirroring known clinical observations, and highlighting the importance of incorporating sex-stratified methods in future JIA studies.

Background Disease flares in dermatomyositis (DM) are unpredictable and often detected weeks to months after their onset. Interferon (IFN)-related gene signatures are implicated in DM, but their value for longitudinal flare prediction remains unclear. We hypothesized that longitudinal transcriptomic profiling using minimally invasive blood microsampling would detect IFN gene signatures preceding and during DM disease flares. Methods In this feasibility study, patients were included if they had inactive or minimally active disease and at least one of the following criteria: recent diagnosis within 2 years, a documented flare in the prior year, or ongoing tapering of immunosuppressive therapy. Patients self-assessed their disease activity weekly for 6 months using the International Myositis Assessment and Clinical Study group (IMACS) patient global assessment (PtGA; numerical rating scale, range 0-10). Disease flares, defined as a PtGA increase >2 for 2 consecutive weeks, triggered an in-person visit for confirmation by a physician. During the follow-up period, patients also self-collected weekly blood microsamples (125uL) that were shipped by courier to the study center. From those weekly blood microsamples, RNA sequencing was performed on 54 samples collected across 9 timepoints using an Illumina platform. Bioinformatic analyses included alignment, quality assessment, and gene-level quantification to evaluate differential gene expression and RNA processing changes during DM flares. Results Six DM patients were included in this study (2 anti-MDA5, 2 anti-Mi2, 1 anti-NXP2, 1 no myositis-specific antibodies). All were female with ages at study entry ranging from 46 to 72 years. Three of the six patients experienced a flare during their 6-month follow-up. The mean (SD) RNA integrity score for the weekly blood microsamples collected was 7,61 (0,64). IFN scores were significantly higher in flare-associated samples than in no flare samples (linear mixed-effects model with individual patient as a random intercept, P = 5.13 x 10E-4). Gene set enrichment analysis of hallmark gene sets identified enrichment of IFN-related gene sets in pre-flare and flare samples with IFN Alpha Response and IFN Gamma Response showing the highest positive normalized enrichment scores. Conclusion This study demonstrates the technical feasibility of combining home-based longitudinal blood microsampling with transcriptomic profiling in dermatomyositis. IFN gene score were higher in flare-associated than in no-flare samples, supporting further investigation of IFN-related signatures as candidate biomarkers for longitudinal disease monitoring.

Background: Chronic lowgrade inflammation in long standing rheumatoid arthritis (RA) contributes not only to joint damage but also to metabolic dysregulation, endothelial dysfunction, and elevated cardiovascular (CV) risk. Although combination disease modifying anti rheumatic drugs (DMARDs) remain the mainstay of therapy, their long term efficacy in controlling systemic inflammation and preventing metabolic complications appears limited. Phytochemicals such as resveratrol, a polyphenolic compound widely used in traditional and complementary medicine, possess anti inflammatory and immunomodulatory properties. Objectives: To investigate whether resveratrol can complement the immunomodulatory effects of combination DMARDs in long duration RA patients by modulating inflammatory cytokines and the JNK-IRS-Akt insulin signaling axis. Methods: This study enrolled early and late rheumatoid arthritis patients to assess disease activity, vascular markers, and ex vivo PBMC responses. PBMCs were isolated for cytotoxicity testing and resveratrol treatment, followed by ELISA and Western blot analysis. Statistical comparisons evaluated immunomodulatory effects and alterations in inflammatory signaling. Results: Longitudinal follow up of RA patients showed significant first year improvement in disease activity and atherosclerotic markers, correlated with MTX dose. An early versus late RA comparison revealed elevated cytokines and enhanced JNK mediated stress signaling in longstanding disease. Resveratrol maintained PBMC viability, reduced LPS induced TNF&alpha and adipokine levels, and downregulated pJNK and GSK&beta, indicating targeted anti inflammatory modulation independent of Akt activation. Conclusion: Chronic RA showed persistent inflammatory and metabolic dysregulation driven by JNK-NF&kappaB activation. Resveratrol reduced cytokines, corrected adipokine imbalance, and selectively inhibited JNK, suggesting adjunct therapeutic value alongside DMARDs for improving immunometabolic disturbances in long-standing RA.

Background. Small fibre pathology has been proposed as a peripheral substrate for a subset of patients with fibromyalgia. A 2019 meta-analysis of 8 studies (222 patients) reported a pooled prevalence of 49% with moderate heterogeneity, and concluded that this supported a distinct fibromyalgia phenotype. The evidence base has since expanded substantially. Methods. We systematically searched PubMed for original human studies reporting the proportion of adults with fibromyalgia showing abnormal small fibre findings on an objective structural or functional test (skin biopsy with intraepidermal nerve fibre density, corneal confocal microscopy, sudomotor testing, microneurography, or laser-evoked potentials). Proportions were pooled with a random-effects model on the logit scale (REML). We pre-specified subgroup analyses by diagnostic method and assessment site, meta-regression on publication year and sample size, leave-one-out sensitivity analysis, and risk-of-bias appraisal with the JBI prevalence checklist. Where cohorts overlapped, the most complete report was retained. Search and initial screening were AI-assisted; eligibility, extraction and appraisal were performed independently by two reviewers with consensus. Results. Of 83 records, 34 studies met eligibility and 21 (1,268 patients) provided extractable proportions. Applying a uniform rule of abnormality at any assessed site, the pooled prevalence was 46.5% (95% CI 34.3-59.1), with I2=92.7% and a 95% prediction interval of 8.6% to 89.0%. Individual estimates ranged from 0% to 85.2%. Contrary to our pre-specified hypothesis, diagnostic method did not explain heterogeneity (QM p=0.89, R2=0). Assessment site was the dominant moderator: using each study's site-specific data, distal-leg assessment yielded 30.5% (22.4-40.1; 15 studies) and proximal-thigh assessment 73.9% (53.5-87.4; 4 studies). Three studies assessed both sites in the same patients and all three found more abnormality proximally (31.6% vs 46.2%; 12.3% vs 85.2%; 9.7% vs 83.9%). Publication year (p=0.50) and sample size (p=0.24) were not associated with prevalence. Leave-one-out estimates remained between 44.4% and 49.6%. Conclusions. More than tripling the evidence base did not stabilise the pooled prevalence estimate and more than doubled heterogeneity (I2 68% to 93%). The prediction interval now spans almost the entire possible range, and the method difference reported in 2019 is no longer detectable. Studies do not share a common definition of abnormality, and several do not report one at all. A pooled prevalence figure for small fibre pathology in fibromyalgia is therefore not currently interpretable; a standardised case definition is a prerequisite for meaningful synthesis. The anatomical site of assessment, not the technique, emerges as the dominant source of variation and should be treated as a primary moderator in future work.

While progress has been made in identifying the true risk-driving single nucleotide polymorphisms (SNPS) on juvenile idiopathic arthritis (JIA) risk haplotypes, the affected cells and target genes largely remain unknown. We used data from a previously published massively parallel reporter assay (MPRA) to query human data in the Database of Immune Cell eQTLs (DICE) and the Gene-Tissue Expression (GTEx) database to identify affected cells and target genes of MPRA-identified SNPs in immune cells and relevant tissues. SNPs identified on MPRA were associated with gene expression levels in a broad range of immune cells in the DICE database, including CD4+ and CD8+ T lymphocytes, monocytes, NK cells, and B cells. MPRA-identified SNPs showed strong associations with gene expression in GTEx whole blood, spleen, and/or EBV-stimulated lymphocytes. Our data show the efficacy of combining MPRA and using human cells/tissue expression data to elucidate complex mechanisms driving genetic risk for JIA.