Rheumatology

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

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

Background: Itch in systemic sclerosis (SSc) is thought to be most significant in early disease, but no longitudinal studies have examined itch course. We estimated itch presence and severity from SSc disease onset, accounting for participant age and time since onset at each assessment. Methods: People with SSc from the multinational Scleroderma Patient-centred Intervention Network Cohort completed past-week itch severity assessments (0 to 10 numerical rating scale) at enrolment and longitudinally at 3-month intervals. To estimate itch probability (score > 0) and, if present, itch severity, we used two-stage mixed effects models with basis splines to address non-linearity. The primary predictor was age at each assessment, partitioned into age at non-Raynaud phenomenon symptom onset and time since onset. We estimated prevalence and severity for onset ages of 20, 30, 40, 50 and 60 years and, for each onset age, at 2 years, 3 years, 4 years, 5 years, 7 years, and 5-year intervals 10 years to 35 years post-onset. Findings: We included 2173 participants with 19 733 itch assessments (mean [standard deviation] 9.1 [6.9] assessments). 1896 of 2173 (87.3%) participants were women. Mean age at enrolment was 54.7 (SD 12.7) years. 873 (40.2%) participants had diffuse cutaneous SSc. Predicted itch probability was between 35.0% (95% CI 31.8% to 38.5%) and 36.8% (95% CI 33.3% to 40.4%) at all onset age and disease duration combinations. Mean itch severity, when present, was moderate, between 4.1 (95% CI 4.1 to 4.1) and 4.4 (95% CI 4.3 to 4.4), for all age and duration combinations. Interpretation: Itch prevalence and mean severity were stable across onset ages and over time within onset ages. Findings suggest that itch is common in SSc and not as closely related to disease duration as previously thought. Research is needed to elucidate itch pathophysiology and identify effective management strategies.

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

BackgroundGastroesophageal reflux disease (GERD) is highly prevalent in systemic sclerosis (SSc) and frequently persists despite proton pump inhibitor (PPI) therapy. However, the mechanisms underlying PPI-refractory GERD in SSc remain incompletely understood. MethodsWe conducted a singlel7lcentre, retrospective study of adults with SSc who underwent ambulatory pH-multichannel intraluminal impedance (pH/MII) monitoring while receiving twicel7ldaily PPI therapy (2021-2025). Esophageal motility (highl7lresolution manometry, HREM) and gastric emptying scintigraphy were integrated to examine associations between gastro-esophageal dysmotility and reflux phenotypes. ResultsThirty patients were included, of whom 67% had PPI-refractory reflux symptoms and 33% were undergoing pre-lung transplantation evaluation. Refractory GERD was present in 29/30 patients (97%) based on Lyon 2.0 classification, with conclusive evidence in 53% and borderline evidence in 43%. Esophageal dysmotility was identified in 80%, most commonly absent contractility (67%), and was associated with impaired reflux clearance, reflected by longer acid clearance times (2.20 [1.15-3.75] vs 1.15 [0.43-1.90] min) and prolonged reflux episode duration (16.60 [4.38-40.63] vs 1.95 [0.53-20.43] min). Gastric dysmotility was identified in 60.7% and was associated with an increased reflux episode burden (51.00 [30.00-81.50] vs 25.00 [21.00-54.00] episodes/24h). ConclusionsPPIl7lrefractory GERD is nearly universal in this SSc cohort and reflects heterogeneous, quantifiable abnormalities across the foregut, including impaired esophageal clearance and increased reflux burden related to gastric retention. These findings support integrated physiologic evaluation to define reflux mechanisms, inform risk stratification (including lung transplantation), and guide targeted, mechanism-based therapies beyond acid suppression.

BackgroundThyroid Eye Disease (TED) is an autoimmune orbital disorder driven by pathogenic T-cell subsets, including T-helper 1 (Th1) and follicular helper T (Tfh) cells, which sustain orbital inflammation and thyroid-stimulating immunoglobulin (TSI) production. Selenium supplementation has demonstrated clinical benefit in mild TED, yet its immunological mechanisms remain poorly defined. MethodsA murine TED model was established in female BALB/c mice via TSHR plasmid immunisation. Animals maintained on a low-selenium diet (0.07 ppm) received sodium selenite supplementation at 0.2 mg/kg/day. Orbital pathology was assessed by immunohistochemistry, H&E and Massons Trichrome staining. T-cell subset abundance was quantified by flow cytometry, and serum T4, TRAb, and IL-21 levels were measured by ELISA. In vitro dose-response experiments examined the effects of selenium on Tfh cell viability, IL-21 production, apoptosis, and ferroptosis. ResultsSelenium supplementation reduced CD3 T-cell orbital infiltration, collagen fibrosis, and serum T4 and TRAb levels in TSHR-immunised mice. Flow cytometry revealed significant reductions in Tfh and Th1 cell abundance, with Th17 cells unaffected. Serum IL-21 and B-cell abundance were also markedly reduced in vivo. In vitro, selenium exhibited a biphasic, dose-dependent effect on Tfh cells: low concentrations maintained viability and IL-21 production, while higher concentrations induced ferroptosis and apoptosis. ConclusionsSelenium modulates pathogenic T-cell responses in TED, most prominently suppressing the Tfh compartment and attenuating the Tfh-B cell-autoantibody axis via ferroptosis and apoptosis. These findings suggest a mechanistic framework for the clinical benefit of selenium in mild TED and highlight the importance of dose selection within its narrow therapeutic window.

Rheumatoid arthritis is a prototypical autoimmune disease, characterised by prolonged systemic autoimmunity prior to organ-specific tissue inflammation. To achieve the contemporary goal of autoimmune disease prevention, a nuanced understanding of the transition from systemic autoimmunity to tissue-specific inflammation is critical. Here, we sought to identify immune signatures associated with the transition to subclinical joint inflammation detected by multi-joint ultrasound in anti-citrullinated protein antibodies (ACPA+)-positive individuals who imminently progress to RA. To achieve this, we performed single-cell transcriptomic and proteomic profiling on prospectively collected blood samples from high-risk ACPA+ imminent progressors, who were further stratified by the presence or absence of ultrasound (US)-detectable subclinical synovitis and compared them with ACPA+ non-progressors. We found type-1 interferon (IFN-I) activation in circulating CD14+ classical monocyte and GZMK+ CD8+ T cells preceding subclinical joint inflammation in ultrasound-negative (USneg) future progressors. In contrast, US-positive (USpos) future progressors exhibited a phenotypic shift in CD14+ classical monocytes towards IL1B+ expression and clonal expansion of GZMB+ cytotoxic CD8+ T cells at the onset of subclinical synovitis. Plasma proteomics also revealed a shift from Toll-like receptor-associated innate pathways in USneg future progressors toward effector and tissue-remodeling signatures in USpos future progressors. These findings suggest IFN-I-driven immune priming in specific immune subsets precedes the onset of subclinical joint inflammation, whereas tissue-directed inflammatory and cytotoxic programmes emerge at the onset of joint inflammation when clinical RA is imminent.

Background: Digital health platforms can improve clinical efficiency and patient outcomes, but adoption in routine care remains limited due to workflow and integration challenges. Rheumatoid arthritis (RA) management relies on consistent capture of patient-reported and clinical data, which is often time-intensive and inconsistently documented. Objective: To assess the impact of the cliexa-RA digital platform on patient experience, physician workflow, and cost-related outcomes using the Quadruple Aim framework. Methods: A six-month pilot study was conducted at the Colorado Arthritis Center involving 300 RA patients. Patients completed a 16-question intake (RAPID3-based), followed by clinician-entered joint assessments. The platform generated five disease activity scores (DAS28-ESR, DAS28-CRP, SDAI, CDAI, RAPID3) and produced EMR-compatible outputs. Time metrics, patient satisfaction, and workflow efficiency were evaluated. Results: Mean patient intake time was 2.4 minutes, a 52% reduction compared to paper-based processes. Clinician time for calculation and documentation decreased by 77%, with near real-time EMR integration. Overall patient satisfaction was high (3.55/4), with 85% recommending the platform. Physicians reported improved documentation efficiency and workflow integration. Administrative cost reductions were observed through decreased reporting burden and improved compliance with quality reporting requirements. Conclusions: The cliexa-RA platform significantly improved efficiency and user experience in RA management. These findings support the role of integrated digital tools in reducing administrative burden and enabling scalable, data-driven care, with potential downstream benefits for cost and population health.

IntroductionSystemic Lupus Erythematosus (SLE) is a chronic autoimmune disease characterized by loss of immune tolerance, autoantibody production, and multi-organ damage. Current therapies, including glucocorticoids and CAR-T/CAR-NK cell therapies, are limited by adverse effects, high cost, and safety concerns. ObjectivesTo develop engineered NK-92 cell-derived extracellular vesicles displaying CD19 single-chain variable fragment (V-CD19-Exo) and evaluate their therapeutic efficacy in an MRL/lpr mouse model of SLE. MethodsThe CD19scFv-LAMP-2B fusion construct was stably expressed in NK-92 cells via lentiviral transduction. Extracellular vesicles were isolated by differential centrifugation and characterized by NTA, TEM, and Western Blot. In vivo efficacy was assessed in MRL/lpr mice through B cell depletion analysis, renal function monitoring, cytokine profiling, autoantibody detection, and survival observation. ResultsV-CD19-Exo significantly reduced splenic CD19{square}CD20{square} B cells from 10.53% to 1.51% (p < 0.0001). Treatment attenuated proteinuria, ameliorated lupus nephritis pathology, reversed splenomegaly, and downregulated serum IgE, IL-17A, IFN-{gamma}, anti-dsDNA, and ANA levels. Notably, V-CD19-Exo improved survival to approximately 80% compared to 25% in untreated controls. ConclusionEngineered NK-92 cell-derived extracellular vesicles represent a novel, safe, and effective cell-free therapeutic strategy for SLE, offering advantages over conventional cell therapies including lower immunogenicity, scalable production, and no requirement for lymphodepletion.

ImportanceAge-related eye diseases, such as cataract, glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR), are leading causes of irreversible vision loss globally. Chronic inflammation is a shared pathogenic pathway, but the role of systemic inflammatory drivers like clonal hematopoiesis of indeterminate potential (CHIP) is unknown. ObjectiveTo investigate the association of CHIP, including its major genetic subtypes and clone sizes, with the risk of four major age-related eye diseases. Design, Setting, and ParticipantsThis was a prospective cohort study conducted using data from the UK Biobank, a large-scale, population-based cohort. A total of 436,469 participants free of the four eye diseases at baseline were included in the analysis. Data were collected from 2006 to 2010, with follow-up extending to March 2022. ExposuresCHIP status was ascertained from whole-exome sequencing data, defined by the presence of a somatic driver mutation with a variant allele fraction of 2% or greater. Main Outcomes and MeasuresThe primary outcomes were incident cases of cataract, glaucoma, AMD, and DR, identified through linked electronic health records. Associations were assessed using multivariable Cox proportional hazards regression models. ResultsOf 436,469 participants (mean [SD] age, 56.4 [8.1] years; 54.5% women), 14,110 (3.2%) had CHIP. Over a median follow-up of 13.1 years, CHIP was significantly associated with an increased risk of incident cataract (Hazard Ratio [HR], 1.08; 95% CI, 1.03-1.14), AMD (HR, 1.12; 95% CI, 1.04-1.21), and DR (HR, 1.41; 95% CI, 1.20-1.64). No significant association was found with glaucoma (HR, 1.08; 95% CI, 0.99-1.17). The risk for AMD was primarily associated with smaller clones (VAF <10%), while the risk for DR was highest with non-DNMT3A mutations. Systemic inflammation, particularly neutrophil count, partially mediated the associations. Conclusions and RelevanceIn this study, CHIP was independently associated with a higher risk of developing cataract, AMD, and DR, but not glaucoma. These findings establish a link between hematopoietic somatic mutations and the pathogenesis of several major age-related eye diseases, suggesting that CHIP-driven inflammation is a potential target for risk stratification and prevention. Key PointsO_ST_ABSQuestionC_ST_ABSIs clonal hematopoiesis of indeterminate potential (CHIP) associated with the risk of major age-related eye diseases? FindingsIn this cohort study of 436,469 participants, CHIP was associated with an increased risk of incident cataract (HR, 1.08; 95% CI, 1.03-1.14), age-related macular degeneration (HR, 1.12; 95% CI, 1.04-1.21), and diabetic retinopathy (HR, 1.41; 95% CI, 1.20-1.64), but not glaucoma. MeaningThese findings identify CHIP as an independent, non-ocular risk factor for cataract, AMD, and diabetic retinopathy, suggesting that systemic inflammation driven by CHIP contributes to the pathogenesis of these conditions and may represent a novel target for preventive strategies.

Background: Idiopathic pulmonary fibrosis (IPF) is a rare disease with a poor prognosis. Disease risk involves rare and common genetic variants. However, an inverse association have been described between them. Accordingly, IPF patients with a higher polygenic risk score (PRS) for IPF are less likely to carry rare deleterious variants and vice versa. Here, we evaluate weather PRS of IPF could serve as an additional criterion to patient prioritisation for rare variant discovery. Methods: We identified carriers based on the presence of rare qualifying variants (QVs) in genes linked to monogenic forms of pulmonary fibrosis in 888 IPF patients from the Pulmonary Fibrosis Foundation Patient Registry (PFF-PR). Genome-wide association study (GWAS) summary statistics from independent cohorts were used to construct a whole-genome PRS (WG-PRS) using a clumping and thresholding method (C+T) and a Bayesian method (SBayesRC). PRS were also derived from 19 known common sentinel IPF variants (Sentinel-PRS). Logistic regression models were used to evaluate associations between PRS and carrier status. Discriminatory performance was evaluated using area under the curve (AUC) analysis, and comparisons were made with DeLong test. Validation was performed in 472 IPF individuals from the UK PROFILE cohort. Results: IPF-PRS were strongly associated with the QVs carrier status: Odds Ratio [OR] 0.65 (95% Confidence Interval [CI] 0.53-0.79) for WG-PRSC+T, OR 0.71 (95% CI 0.59-0.86) for WG-PRSSBayesRC, and OR 0.77 (95% CI 0.63-0.94) for Sentinel-PRS. Adding WG-PRS to the patient personal clinical history improved the prediction of QVs carriers: AUC=0.62 for the clinical model, AUC=0.68 for WG-PRSC+T (DeLong test, p=9.54x10-4) and AUC=0.66 for WG-PRSSBayesRC (DeLong test, p=0.02). Adding of IPF-PRS to clinical variables correctly reclassified 22.8% of carriers when using WG-PRSC+T, 20.8% when using Sentinel-PRS, and 16.7% for WG-PRSSBayesRC. WG-PRSSBayesRC and the Sentinel-PRS also demonstrated improved prediction of QVs carriers in telomere-related genes in PROFILE. Conclusions: Incorporating IPF-PRS into a model based on the patient clinical history improves the identification of QVs carriers. Although the overall discriminatory power was moderate, these findings raise de the possibility of using WG-PRS as useful criterion for rare variant discovery in patients with IPF and enhance decision-making.

Objective To describe trends in dispensing of monoclonal antibodies (mAbs) for autoimmune conditions during and around pregnancy. Design Descriptive study. Setting Lombardy, Italy between 2012 and 2024. Population All women of reproductive age (14-49 years) resident in Lombardy. Methods We described trends in mAb dispensations among women of reproductive age and the prevalence of mAb dispensing before, during and after pregnancy. We explored maternal factors associated with discontinuation. Main outcome measures Change in prescribing of mAbs over time in all women of reproductive age, and before, during and after pregnancy in those who became pregnant. Prevalence of discontinuation and switching mAbs around pregnancy. Results We included 3,049,175 women of reproductive age and 859,699 pregnancies. Prevalence of mAb dispensing during pregnancy increased over 60-fold over the study period, from 0.0041% (95%CI:0.00084, 0.012) in 2012 to 0.27% (95%CI:0.23, 0.32) in 2024. Pregnancy affected mAb dispensing, with mean prevalence decreasing from 0.080% (95%CI:0.074, 0.087) before pregnancy to 0.051% (95%CI:0.046, 0.057) by the third trimester. Over half (53.3%) of pre-existing users discontinued before or during pregnancy; discontinuation decreased over time, and varied substantially between mAbs. Switching mAbs during pregnancy was rare (3.3%). We found limited evidence that sociodemographic factors were associated with discontinuation, but that some health factors may be, such as use of assisted reproductive technology (OR=1.92, 95%CI:0.98-3.77). Conclusions Italian population-wide data from 2012-2024 show an increase in mAbs dispensed during pregnancy, and fewer instances of discontinuing these drugs over time. This may reflect recent changes in prescribing guidelines for mAbs in pregnancy.

Background: SARS-CoV-2 infection is an established prothrombotic trigger, yet the population-level temporal relationship between circulating viral activity and pulmonary embolism (PE) remains poorly characterized. We aimed to evaluate the short-term association between respiratory viral activity and PE hospitalizations, accounting for specific temporal lags. Methods: We conducted a population-level time-series analysis of incident PE hospitalizations in Ontario, Canada, from 2011 to 2024. Using distributed lag non-linear models, we assessed the association between standardized weekly activity levels of SARS-CoV-2, influenza A/B, and respiratory syncytial virus (RSV) and PE risk over a 5-week lag period. Relative risks (RR) per standard deviation (SD) increase in viral activity were estimated via negative binomial regression using cross-basis terms to account for both exposure-response and lag-response non-linearities. Models were adjusted for Fourier seasonal terms and secular trends. Findings: Among 70,670 incident PE cases identified between 2011 and 2024, SARS-CoV-2 activity demonstrated a significant temporal association with PE. A cumulative RR increase of 20% per SD in SARS-CoV-2 activity was observed over the five weeks following exposure (RR 1.20; 95% CI 1.05-1.37). The risk followed a distinct delay trajectory: weekly cumulative RRs peaked at week 3 (RR 1.21; 95% CI 1.01-1.45). For the 2020-2024 period, influenza A also showed an association peaking at week 3 without statistical significance (RR 1.17; 95% CI 0.95-1.45). Interpretation: Increased population-level SARS-CoV-2 activity is associated with a heightened risk of PE, peaking at approximately the third week. This delayed peak suggests a protracted thrombo-inflammatory window, likely driven by sustained endothelial injury. These findings highlight the vascular burden of COVID-19 and suggest that infection prevention measures, including vaccination, may provide significant downstream protection against thromboembolic disease.

Abstract Background Spontaneous coronary artery dissection (SCAD) is a well-recognised cause of acute coronary syndrome particularly among women without conventional cardiovascular risk factors. Increasing evidence indicates a genetic contribution; however, the underlying genetic architecture of SCAD remains insufficiently understood. Objective The aim of this study was to assess the prevalence of rare variants in previously reported SCAD associated genes and to explore the potential presence of novel genetic alterations in well-characterised Swedish patients with SCAD. Methods The study comprised 201 patients enrolled in SweSCAD, a national project examining the clinical characteristics, aetiology, and outcomes of SCAD. All individuals had a confirmed diagnosis based on invasive coronary angiography. Comprehensive exome sequencing was performed to identify rare variants contributing to disease susceptibility. Results Genetic variants that have been associated with SCAD according to current clinical genetics practice for variant reporting were identified in approximately 4 % of patients. In addition, rare potentially relevant variants were detected in almost 60 % of patients in genes associated with vascular integrity and vascular remodelling. Conclusion This study supports SCAD as a genetically complex arteriopathy, driven by rare high?impact variants together with broader polygenic susceptibility. Variants in collagen, vascular extracellular matrix, and oestrogen?responsive pathways provide biologically plausible links to female?predominant disease. Although the diagnostic yield of clearly actionable variants is modest, these findings support broader genomic evaluation beyond overt syndromic presentations and highlight the need for larger integrative genomic and functional studies to refine risk stratification and management.

BackgroundThis study aims to examine the independent relationships between individual components of metabolic syndrome (MetS) and two key clinical outcomes in patients with Crohns disease (CD): disease activity, as quantified by the Crohns Disease Activity Index (CDAI), and the occurrence of complications. MethodsThis retrospective cross-sectional study included 376 adults with newly diagnosed Crohns disease. Multiple linear regression was used to examine associations between metabolic parameters and CDAI scores, while multivariate logistic regression assessed links to complications. Analyses were also based on clinical CDAI cut-offs. Predictive nomograms were developed and internally validated via bootstrap resampling. ResultsMultiple linear regression indicated that higher CDAI scores were independently associated with lower BMI (B = -5.866, P < 0.001), lower HDL-C levels (B = -81.770, P < 0.001), higher triglycerides (B = 15.618, P = 0.001), and lower ESR (B = -0.375, P = 0.03). Multivariate logistic regression established low HDL-C (OR = 0.042, P < 0.001), low BMI (OR = 0.915, P = 0.034), and high triglycerides (OR = 1.792, P = 0.007) as significant independent risk factors for complications. The developed nomograms demonstrated strong predictive performance, with an adjusted R2 of 0.207 for the CDAI model and an AUC of 0.765 for the complication model. For both predictive tasks, the model incorporating separate TG and HDL-C measurements significantly outperformed the TG/HDL-C ratio model. ConclusionMetabolic disturbances demonstrate a significant association with increased disease severity and a higher risk of complication development in Crohns disease. Core tipO_LIDual-outcome study reveals HDL-C and TG differentially link to CD inflammation and complications, pointing to distinct mechanisms. C_LIO_LILow HDL-C is the strongest independent predictor for CD complications, underscoring its protective role beyond cholesterol transport. C_LIO_LIIndividual TG and HDL-C metrics outperform their ratio in prediction, challenging its use and suggesting independent pathways in CD. C_LIO_LILow BMI independently associates with both adverse outcomes, refining the "obesity paradox" and highlighting malnutritions key role. C_LIO_LIA practical, validated nomogram (AUC=0.765) integrates HDL-C, TG, and BMI to stratify complication risk, aiding clinical decision-making. C_LI

Background: Diagnosing the over 700 known rare bone diseases (RBDs) is inherently challenging and often requires extensive time and multiple clinical visits. Effective treatment, particularly for RBDs with approved therapies, depends on early and precise identification of the specific RBD type. Image recognition artificial intelligence (AI) has the potential to significantly enhance diagnostic processes and improve patient outcomes. Many of these disorders cause characteristic skeletal changes, especially in the hands, and are associated with growth abnormalities. Consequently, affected children routinely undergo hand radiographs for bone age assessment, making these images a widely available yet underutilized diagnostic resource. Materials and Methods: We retrospectively compiled 5,623 multi-institutional hand radiographs from 2,471 patients with 45 different RBDs and 1,382 unaffected controls. We trained two deep learning models: a binary classifier to differentiate between RBD and non-RBD hand radiographs, and a multi-class classifier covering ten RBDs (or RBD groups), using 5-fold cross-validation. Preprocessing included masking, normalization, and data augmentation. Additionally, we applied occlusion sensitivity mapping to visualize class-specific features and evaluated the learned representations through cosine-based retrieval and UMAP projections of the feature space. Results: The affected versus unaffected classifier achieved a balanced accuracy of 85.5% on the test dataset. The ten-class classifier reached a balanced (top-1) accuracy of 76.6%, with top-3 accuracy exceeding 90%. Disorders with highly distinctive phenotypes, such as achondroplasia, achieved accuracies above 95%, whereas phenotypically overlapping disorders, such as ACAN- and SHOX-related short stature, were more frequently confused. Feature space analysis showed that validation samples clustered closely with their respective training distributions, supporting the consistency and generalizability of the learned embeddings. Conclusion: This manuscript presents a proof of principle for the development of Bone2Gene, a next-generation phenotyping (NGP) tool for the detection and differential diagnosis of RBDs, currently based on hand radiographs. Ongoing efforts focus on expanding the dataset to include additional RBDs or RBD groups in the current multi-class classifier for differential diagnosis and to further evaluate its generalizability. The Bone2Gene study is open to collaboration.

Background: Facioscapulohumeral muscular dystrophy (FSHD) is a common hereditary neuromuscular disorder. The Russian FSHD Patient Registry was established in 2019 following the development of a PCR-based method for genetic confirmation of the diagnosis. Results: The registry included 470 participants (51% male). Genetic confirmation was obtained for 76% (n=356), the remainder were included based on clinical and anamnestic data. Clinical assessment forms and patient-reported questionnaires were analyzed for 310 and 142 patients, respectively. D4Z4 repeat unit (RU) distribution showed patterns consistent with European cohorts, with a predominance of patients with 3 RUs. A moderate inverse correlation was found between RUs number and clinical severity scales. Periscapular weakness was the most common onset manifestation (46.8%), followed by facial weakness (31.6%) which was often unnoticed by patients. The mean age in the Russian cohort was 37.8 years (range 0-97), indicating a younger cohort compared to international data. A delta-adjusted cluster analysis (n=215) identified three distinct trajectories: a classic phenotype with onset before age 14 and early involvement of various muscle groups (n=177), and two clusters characterized by either facial or periscapular onset with slow progression. Conclusion: The Russian FSHD registry provides a comprehensive characterization of a large national cohort, revealing a predominance of patients with 3 D4Z4 repeats and a younger demographic profile compared to international data. Cluster analysis identified three heterogeneous disease trajectories, offering a framework for improved patient stratification.

Background: Insulin resistance (IR) and obesity are key drivers of atrial fibrillation (AF). However, the comparative predictive value of the Triglyceride-Glucose (TyG) index versus composite indices combining IR and anthropometric measures such as TyG-BMI, TyG-Waist Circumference (TyG-WC), and Waist-to-Height Ratio (WHtR) remains undefined. We aimed to evaluate these associations and the modifying effect of genetic susceptibility. Methods: We analyzed 293,318 UK Biobank participants free of AF at baseline. Hazard ratios (HRs) were estimated using Cox proportional hazards models, and non-linearity was assessed using restricted cubic splines. Incremental predictive value was evaluated via Net Reclassification Improvement (NRI). Interactions with AF Polygenic Risk Scores (PRS) were examined. Results: During follow-up, 22,707 incident AF cases occurred. While the TyG index was associated with AF in unadjusted models, this association was nullified after full adjustment. In contrast, composite indices (TyG-BMI, TyG-WC) and WHtR showed robust, positive associations (WHtR HR per SD: 1.30, 95% CI 1.28-1.32). Spline analysis identified non-linear threshold effects (e.g., WHtR inflection at 0.556). Adding WHtR or TyG-BMI to baseline models significantly improved risk reclassification (NRI ~10.3-11.8%, P<0.001), whereas TyG alone did not (P=0.73). Elevated metabolic risk increased AF incidence across all genetic categories, with significant interactions suggesting greater relative impact in low-genetic risk groups. Conclusions: Composite indices integrating central obesity and insulin resistance are superior to the TyG index alone in predicting incident AF. The identification of specific risk thresholds and genetic interactions highlights "metabolic health" as a crucial, modifiable target for AF prevention.

Background: Renal impairment is associated with increased risk of Parkinson's disease (PD) in general populations; however, the renal-PD link within cardiovascular disease (CVD) patients remains unclear through the high comorbidity of renal dysfunction and elevated PD risk among this special population. Objectives: To assess renal function's association, longitudinal trajectories and predictive value for PD specifically within a cardiovascular disease cohort. Methods: Among 29,266 UK Biobank CVD patients, we assessed baseline renal function via creatinine-based (eGFRcr) and cystatin C-based (eGFRcys) estimated glomerular filtration. Multivariable Cox regression analyzed associations with incident PD and all-cause mortality, with wide sensitivity analyses addressing reverse causation/confounding. Nested case-control analysis characterized pre-PD eGFR trajectories over 14 years. We finally evaluated whether renal function improved the PREDICT-PD's predictive ability. Results: Over a median 13.1-year follow-up, 489 incident PD cases and 5,919 deaths occurred. Lower eGFR levels exhibited dose-dependent associations with increased PD risk (eGFRcr: HR=0.87 [0.80~0.95]; eGFRcys: HR=0.90 [0.82~0.99]) and all-cause mortality (eGFRcr: HR=0.77 [0.75~0.79]; eGFRcys: HR=0.64 [0.63~0.66]). Pre-PD eGFR trajectories diverged significantly from controls starting over 14 years before diagnosis. eGFR-defined chronic kidney disease (<60 ml/min/1.73m2) conferred 38~60% higher PD risk and 159~234% elevated mortality risk, and could significantly enhance PREDICT-PD's discrimination, with a 1.18~1.34% increase in prediction accuracy. Conclusions: Impaired renal function is an independent PD and all-cause mortality risk factor of CVD patients, preceded by a slow, progressive eGFR decline starting >14 years before diagnosis. Incorporating renal function substantially improves PD risk prediction in this population.

Over half of patients with rheumatoid arthritis (RA) report clinically meaningful pain, despite treatment with disease-modifying antirheumatic drugs (DMARDs). While joint inflammation is a known cause of pain in patients with rheumatic diseases, emerging data indicate that many patients also suffer from centralized or nociplastic pain. There is a critical unmet need to characterize the altered cellular state that distinguishes patients with centralized pain. In the IMPACT study, 39 RA patients with minimal joint inflammation but varying levels of pain underwent quantitative sensory testing (QST) to assess nociplastic pain, completed patient-reported outcome (PRO) surveys, and provided blood samples for immune profiling. Supervised and unsupervised analysis of the multi-parameter spectral flow cytometry data identified immune cell populations correlated with nociplastic pain and patient-reported pain intensity. Moreover, analyses of single-cell RNA-seq from a subset of 22 patients revealed differences in cell type proportions and differential expression between the high and low pain groups. These studies provide novel insights into the role of circulating immune cells in altered central nervous system (CNS) pain regulation in adults with RA.