Arthritis & Rheumatology

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.

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.

BackgroundOsteoarthritis (OA) is a leading cause of disability worldwide, yet no licensed therapies can prevent or slow its progression. We aimed to identify potential targets for disease-modifying OA drugs (DMOADs) by integrating genetic and differential protein expression (DPE) evidence. MethodsWe evaluated genetically predicted perturbations of plasma protein levels using cis-protein quantitative trait loci (cis-pQTLs) across three large European cohorts (UK Biobank Pharma Proteomics Project, deCODE, and Fenland) and outcome data from the Genetics of Osteoarthritis Consortium, covering 11 OA phenotypes. DPE analyses were performed in 44,789 UKB participants, comparing 2,920 protein measurements between OA cases and controls, supported by sensitivity analyses. Proteins identified through genetic and/or DPE approaches were further assessed in downstream analyses. FindingsIn total, 305 proteins showed evidence of association with OA through genetically predicted perturbations, with 81 supported by colocalisation across datasets. DPE analyses identified 605 proteins associated with at least one OA phenotype, of which 450 (74{middle dot}4%) remained robust after sensitivity testing. Several novel targets were identified, including PPP1R9B, PCSK7, and ITIH4. Integration of both approaches prioritised 5 proteins, 4 of which demonstrated druggable potential, including 3 high-confidence candidates DLK1, TNFRSF9, and OGN. Downstream analyses highlighted key biological pathways and candidate compounds with potential for repurposing. InterpretationThis large-scale study combines genetic and DPE evidence to prioritise candidate DMOAD targets. Findings reinforce established biology while revealing novel proteins and pathways, providing a foundation for therapeutic development in OA. FundingWL is supported by the Guangzhou Elite Project (project no. JY202314). SSZ is supported by The University of Manchester Deans Prize, Arthritis UK Career Development Fellowship (grant no. 23258). This work is supported by the NIHR Manchester Biomedical Research Centre (NIHR203308). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSCirculating proteins have been linked to osteoarthritis (OA) in observational studies, supporting their potential as biomarkers and drug targets. However, differential protein expression analyses are vulnerable to confounding and reverse causation. Mendelian randomisation (MR) studies using proteomic GWAS instruments have suggested causal roles for several circulating proteins in OA-related traits and highlighted druggable candidates. However, many analyses relied on earlier OA GWAS data (e.g., Genetics of Osteoarthritis Consortium 1{middle dot}0) and smaller proteomic GWAS datasets, and typically did not integrate MR findings with large-scale differential protein expression. As a result, it remains unclear how well genetically predicted protein effects align with observed protein expression in OA, and how robust prioritised targets are when replicated across proteomic data from multiple cohorts. Added value of this studyThis study integrates large-scale proteomic MR and differential protein expression (DPE) analyses across multiple OA phenotypes using the largest datasets to date. By combining genetic evidence with observed protein dysregulation in population-based cohorts, we strengthen causal inference and improve robustness of target prioritisation. This approach allows us to distinguish proteins that are likely to play a causal role in OA from those that reflect downstream disease processes, and to highlight targets with greater translational relevance than identified by either method alone. Implications of all the available evidenceTaken together, our findings support a causal role for a subset of circulating proteins in OA and demonstrates the value of integrating genetic and observational proteomic data for target prioritisation. Proteins supported by both MR and DPE are more likely to represent biologically relevant drivers of disease and actionable therapeutic targets. This integrated framework reduces false positives arising from confounding or reverse causation and provides a more reliable basis for drug development, biomarker discovery, and patient stratification in OA.

Autoantibody internalization has been implicated in autoimmune disease pathogenesis, yet its mechanisms, and generality across different diseases, cell types, and affected tissues remain poorly defined. Using bulk RNA sequencing, we identified reproducible, autoantibody-specific transcriptomic signatures consistent with autoantigen dysfunction in muscle biopsies from patients with anti-Mi2 dermatomyositis and anti-PM/Scl scleromyositis across independent cohorts. Electroporation of purified patient IgG into primary cultures of healthy cells was sufficient to induce the corresponding transcriptomic programs in vitro. Direct immunofluorescence demonstrated immunoglobulin internalization into subcellular compartments matching the localization of the autoantigen in different affected tissues. Spatial transcriptomic analyses revealed that antibody-secreting cells translocated cytoplasmic material (i.e., immunoglobulin RNA) into adjacent affected cells expressing autoantibody-specific transcripts. The disease-specific transcripts were present not only in muscle fibers, but also in other cells, including macrophages, endothelial cells, and fibroblasts. Autoantibody-induced transcriptomic programs were associated with cell damage and autoantibody-specific reactive inflammatory programs, including activation of type I interferon and TGF-{beta}1 signaling in anti-Mi2 dermatomyositis and activation of type II interferon in anti-PM/Scl scleromyositis. Antibody internalization was also observed in different tissues from patients with other autoimmune diseases, including anti-U1RNP mixed connective tissue disease, anti-Ku overlap syndrome, and anti-Scl70 systemic sclerosis. Together, these findings establish autoantibody internalization as a shared pathogenic mechanism across diverse autoimmune diseases, providing a unifying framework for conditions driven by autoantibodies against intracellular antigens.

ObjectivesTo investigate genetic architecture and identify novel risk loci shared between juvenile idiopathic arthritis (JIA) and other human leukocyte antigen (HLA)-associated autoimmune diseases (AIDs) by leveraging genome-wide association studies (GWAS) data. MethodsWe analyzed GWAS summary statistics from over two million participants (123,997 cases and 1,843,249 controls) of European ancestry across multiple AIDs including JIA, autoimmune thyroid disease (AITD), celiac disease, inflammatory bowel disease (IBD), multiple sclerosis (MS), psoriasis (Ps), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and type 1 diabetes (T1D). The conjunctional false discovery rate (conjFDR) method was employed to identify shared genetic loci, followed by functional annotation and pathway analysis. ResultsWe identified 46 novel loci shared between JIA and various AIDs: 17 with AITD, 16 with RA, 13 with IBD, five each with MS and Ps, four with SLE, and seven with T1D. Notable shared risk genes included BACH2, UBASH3A, IRF4, IL12A-AS1, ETS1, PSMD14, FOXK1, NEK6, SP140, TNIP1, VAV3, CYP20A1, DNMT3A, LAX1, CASC15, ZC3H12C, KALRN, TBC1D1, PIK3CB, ANXA6, and HIF1A. Functional annotation revealed 170 nonsynonymous exonic variants and 478 potentially deleterious variants (CADD score > 12.37). Gene Ontology analysis consistently highlighted enrichment of T cell-related processes and immune system regulation pathways. ConclusionThis study expands the understanding of genetic architecture in JIA by identifying novel risk loci shared with other AIDs. The extensive genetic overlap and shared biological pathways, particularly in T cell-mediated immunity, suggest common pathogenic mechanisms and potential therapeutic targets across multiple autoimmune conditions.

ObjectivesCardiovascular risk excess in rheumatoid arthritis (RA) cannot be explained by traditional risk factors alone. Recent experimental data have identified ALDH4A1 as a mitochondrial self-antigen implicated in atherosclerosis, yet its clinical significance in human autoimmunity remains unexplored. We aimed to characterize ALDH4A1 and anti-ALDH4A1 antibody levels in early RA, and evaluate their associations with atherosclerosis burden and lipoprotein traits. MethodsALDH4A1 and anti-ALDH4A1 antibodies (IgM, IgG, IgA, and IgG subclasses) were measured in early RA (n=82), clinically suspect arthralgia (n=14), healthy controls (n=70), and a validation cohort of established RA. A prospective cohort (n=13) explored therapeutic modulation under TNF blockade. Associations with atherosclerosis burden, lipid/lipoprotein profiles, oxylipin signatures, proteomics, and cell-free DNA were assessed. ResultsALDH4A1 serum levels were associated with apoptotic-related proteomic pathways, cell-free DNA and lipidomic signatures in early RA. Reduced anti-ALDH4A1 antibodies were found, although divergent patters were noted across isotypes. These differences were confirmed in a validation cohort. IgG (predominantly IgG3) anti-ALDH4A1 correlated with favourable lipoprotein traits and cardiometabolic risk factors. Increased ALDH4A1 and reduced IgM/IgG anti-ALDH4A1 antibodies independently predicted atherosclerosis and improved risk stratification beyond mSCORE, most notably for IgG. ALDH4A1 tracked with TNF dynamics under TNF blockade, whereas increases in IgG antibodies occurred in responders and paralleled changes in lipoprotein features. ConclusionsThe ALDH4A1/anti-ALDH4A1 axis emerges as a novel player bridging lipid disturbances and atherosclerosis along the RA spectrum, hence highlighting the involvement of mitochondrial targets. These components hold promise as functional players, clinical tools and therapeutic targets.

ObjectivesBehcets disease (BD) is a multisystem inflammatory disorder with diverse phenotypes and incompletely defined immune mechanisms. This study aimed to map immune dysregulation in BD at high resolution, comparing active versus remission states and identifying pathways linked to clinical phenotypes. MethodsWe performed single-cell RNA sequencing on 247,028 peripheral blood mononuclear cells (PBMCs) from 34 BD patients and 12 healthy controls. Transcriptomic profiling, differential gene expression, pathway enrichment analyses, and phenotype-stratified comparisons were used to delineate immune cell alterations associated with disease activity and clinical subtypes. ResultsAll three monocyte subsets were markedly expanded in BD and demonstrated dominant IFN-{gamma}-associated activation, robust heat-shock responses, and enhanced antigen-presentation programs. In active disease, monocytes exhibited pronounced type II interferon signatures, which reversed in remission alongside restoration of regulatory and metabolic pathways. Remission was instead characterized by increased expression of type I interferon-regulated genes, suggesting a potentially protective IFN-I-mediated effect, and by activation of SERPIN-associated programs linked to tissue stabilization. Clinical phenotype stratification revealed distinct monocyte signatures, with vascular BD enriched for heat-shock and stress-response pathways, and ocular BD defined by TNF/NF-{kappa}B-driven inflammation. Patients without organ involvement demonstrated an increased type I interferon gene signature, further supporting a potential protective role for type I interferon responses in BD. ConclusionsThis study provides a high-resolution immune atlas of BD, identifying monocyte-driven dysregulation as a central feature. Our findings map the immune heterogeneity of BD, identify activity- and phenotype-linked monocyte states, and suggest immune pathways suitable for targeted intervention.

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

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.

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.

Individuals who have serum elevations of anti-cyclic citrullinated protein (anti-CCP) antibodies are at risk for developing rheumatoid arthritis (RA), yet immunologic factors that lead to a transition from pre- to clinical RA remain unclear. Here, we used materials from anti-CCP antibody-positive individuals enrolled in a clinical trial that evaluated the efficacy of hydroxychloroquine to prevent clinical RA, and performed multi-modal single-cell profiling (transcriptome, surface proteins, T/B-cell receptor sequencing, and chromatin accessibility) on samples obtained at baseline and at RA onset in those who developed clinical RA (Converters) or follow-up point in matched Nonconverters. At both baseline and follow-up, Converters had expansions of peripheral helper T (Tph) cells and CD8+ T cells expressing GZMK and GZMB, along with elevated potentially autoreactive T-cell receptors in CD4+ T cells compared to Nonconverters. Induction of age-associated B cell signatures was observed in B cells of Converters prior to RA onset. Epigenetic profiling further identified chromatin accessibility changes in Converters over time, particularly within myeloid and NK cells. Lastly, predictive modeling using baseline immune features, including Tph cells, GZMK+XCL1+ CD8+, and GZMB+CD57+ CD8+ T cells, together with clinical features such as anti-CCP3 levels, RF-positivity, and HLA shared epitope status, stratified RA risk and predicted time to onset. These findings define immune endotypes in pre-RA that could serve as targets for future preventive interventions and be used to stratify the risk of developing clinical RA in anti-CCP antibody-positive individuals.

Genome-wide association studies have identified genetic polymorphisms at 11p15 associated with Systemic Lupus Erythematosus (lupus). Statistical fine mapping prioritizes a highly prevalent coding haplotype within the IRF7 gene. Analysis of ancient DNA confirms that this haplotype has persisted at high frequencies in the global population for millennia. The IRF7 risk haplotype is sufficient to increase nuclear localization of IRF7 and transcriptional activity downstream of pattern recognition receptor pathways. This risk haplotype increases IRF7 DNA binding strength and alters IRF7 DNA sequence specificity, resulting in genotype-dependent increases in IFN- production in numerous biological systems, including monocytes and airway epithelial cells. CRISPR engineering of a homologous risk variant in mouse Irf7 results in both enhanced innate control of virus infection and increased autoantibody titers in a model of autoimmunity. Altogether, we establish a persistent and prominent genetic IRF7 haplotype that amplifies IRF7 activity in a manner that has immunological risks and benefits. HIGHLIGHTS[bullet] Genetic analysis using modern and evolutionary datasets identifies a persistent and highly prevalent lupus-associated coding haplotype in IRF7 at 11p15 [bullet]The IRF7 lupus risk haplotype increases IFN- production by monocytes and airway epithelial cells [bullet]The IRF7 lupus risk haplotype increases IRF7 DNA binding strength and alters DNA sequence specificity [bullet]A homologous lupus risk variant in mouse Irf7 enhances control of vesicular stomatitis virus and exacerbates autoantibody production

Gout is driven by an interleukin-1{beta}-mediated intense innate immune reaction to monosodium urate (MSU) crystals (MSUc). In cell culture models of inflammatory gout there is a synergistic effect of phagocytosis of MSUc and TLR2 and TLR4 activation by agonists such as free fatty acid and lipopolysaccharide (LPS) in NLRP3-inflammasome activation and IL-1{beta} secretion. A substantial number of gout patients do not report a dietary trigger, and observational studies associate airborne particulate matter with incident gout and flares. Airborne particulate matter contains LPS and airborne-derived particulate matter stimulates IL-1{beta} secretion in cell culture. We hypothesized that air-borne particulate matter could co-stimulate, with MSUc, IL-1{beta} secretion and inflammation. We tested the hypothesis using MSUc with extracted airborne PM4 in human cells (the THP-1 monocyte cell line, primary human monocytes and PBMCs) or carbon black particles with ozone (CB+O3) in a murine foot-pad injection model of gout. There was strong NLRP3-inflammasome-dependent co-stimulation of IL-1{beta} secretion in THP-1 cells with PM4+MSUc and a moderate additive effect in primary human PBMCs. However, there was no added effect on IL-1{beta} secretion of PM4 in isolated primary human monocytes. Inhalation of CB+O3 persistently exacerbated MSUc-induced murine paw inflammation, with an increase of alveolar/lavage macrophages that contained CB+O3 particles and increased lavage expression of IL-1{beta}. In conclusion, airborne-derived PM4 particulate matter enhanced MSUc-induced IL-1{beta} secretion in THP-1 cells and PBMCs. Combined with exacerbation of MSUc-induced inflammation by fine particulate matter in in vivo experiments, these data provide evidence that exposure to fine particulate matter may play a role in the etiology of gout.

Anti-{beta}2-glycoprotein I (anti-{beta}2GPI) antibodies are central to the pathogenesis of antiphospholipid syndrome (APS), an autoimmune disease characterized by a strong predisposition to venous thromboembolism (VTE). In this study, we conducted a multi-ancestry genome-wide association study (GWAS) of quantitative total anti-{beta}2GPI levels in 5,969 participants enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) and identified a genome-wide significant association at the APOH locus. Paradoxically, genetically determined increases in anti-{beta}2GPI levels at this locus were associated with lower VTE risk. Fine-mapping and functional genomics prioritized the missense variant rs1801690 (W335S) in {beta}2GPI (apolipoprotein H, [APOH]) as the most likely causal variant. This variant has an allele frequency of 5-6% in European and East Asian ancestries but only 1% in African ancestries. Integrating prior experimental studies, molecular dynamics simulations and structure-based epitope prediction, we propose a dual-effect mechanism whereby W335S reduces thrombotic risk by disrupting phospholipid binding in Domain V, yet increases autoantibody production through conformational changes that enhance epitope exposure in Domains I and II. These findings mechanistically uncouple autoantibody formation from thrombotic risk in carriers of the W335S variant, and suggest that APOH genotype may represent a clinically relevant genetic biomarker with potential utility for thrombotic risk stratification in anti-{beta}2GPI-positive individuals.

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.

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.

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.

BackgroundKnee osteoarthritis (OA) is a prevalent painful degenerative disease without effective disease-modifying drugs. The rising prevalence of comorbid obesity and knee OA underscores the urgent need for effective management to delay or prevent disease progression. In a recently completed randomized, placebo-controlled trial in adults with comorbid obesity (BMI >30 kg/m{superscript 2}) and unilateral or bilateral knee OA (Kellgren-Lawrence grade II-III), we were the first to demonstrate that a 6-month prebiotic intervention (16 g/day oligofructose-enriched inulin) significantly improved physical function and metabolic health. MethodsTo elucidate the underlying mechanisms, we incorporated metagenomics, metabolomics, and machine-learning-based multi-omics integration in 30 participants who completed baseline and at least one follow-up assessment and sample collection at months 3 and 6. ResultsPrebiotic supplementation reshaped gut microbial composition and function, increasing diet-derived carbohydrate availability, mitigating excessive host-glycan degradation and mucosal barrier disruption, reducing systemic inflammation and metabolic dysregulation, and ultimately improved physical performance and metabolic health. In a diet-induced obese rat model, prebiotic treatment reduced tibial cartilage degeneration and synovial membrane thickening, providing protection against OA onset and progression through a shared inflammatory pathway. ConclusionsOur findings provide mechanistic evidence supporting the therapeutic potential of prebiotic supplementation as a conservative management in humans and as a preventive approach for obesity-related knee OA in a preclinical rat model, mediated through the gut-joint axis. Trial registrationClinicaltrials.govNCT04172688

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.