The Lancet Rheumatology

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.

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: 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.

Patients with myasthenia gravis (MG) may produce autoantibodies neutralizing type I interferons (AAN-I-IFN), which have been shown to underlie severe viral diseases, including critical COVID-19 pneumonia, in patients without MG. We studied an international cohort of 85 unvaccinated SARS-CoV-2-infected MG patients with no antiviral treatment. Hypoxemic pneumonia occurred in 48 of these patients, including 22 (45.8%) with AAN-I-IFN, which neutralized both IFN-2 and IFN-{omega} in 14 (29.2%) patients. Six (16.2%) of the remaining 37 patients had AAN-I-IFN, which neutralized both IFN-2 and IFN-{omega} in three patients. The risk of hypoxemic pneumonia was greater in MG patients with AAN-I-IFN neutralizing 10 ng/mL of both IFN-2 and IFN-{omega} (odds ratio and 95% confidence interval (OR [95% CI]): 12.7 [2.1-78.9], p=0. 0010) or IFN-2 at any dose (4.7 [1.5-15.0], p=0.0054) than in those without such autoantibodies. The risk of AAN-I-IFN production was much higher in MG patients than in the general population (28.9 [10.8-77.7], p=4.9x10-27). Fourteen patients had thymoma, which increased the risk of AAN-I-IFN (64% versus 27%, (OR [95% CI]: 5.6 [1.6-19.4], p=0.0050) and hypoxemic pneumonia (9.2 [1.9-44.2]; p=0.0019). Thymoma is, thus, associated with a higher risk of producing AAN-I-IFN, and these autoantibodies are associated with a higher risk of developing life-threatening COVID-19 pneumonia in patients with MG.

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.

Red blood cell (RBC) alloimmunization is a clinically significant complication in transfused patients whose immunological determinants remain incompletely understood. Type I interferon (IFN-I) signaling drives RBC alloimmunization in murine models, and systemic lupus erythematosus (SLE) is characterized by constitutive IFN-I hyperactivation alongside elevated alloimmunization rates. We analyzed three publicly available SLE RNA-seq cohorts (GSE72509, GSE112087, GSE122459; whole blood and PBMC; total n = 150 SLE) in a pre-specified discovery-replication-validation design. A 14-gene IFN-I signature score was computed per sample; differential expression, gene set enrichment analysis, and Spearman correlation were performed independently per cohort. IFN-I scores were significantly elevated in SLE versus healthy controls in all three cohorts (p < 0.01 each). IFN-high SLE patients showed 665 differentially expressed genes, with enrichment of alloimmunization-associated and plasmablast differentiation gene sets confirmed by GSEA. The alloimmunization signature score correlated significantly with IFN-I score across all three independent cohorts ({rho} = +0.77, +0.51, +0.60; all FDR q < 0.05); Tfh differentiation showed no association in any cohort. To our knowledge, this represents the first human transcriptomic evidence that IFN-I pathway activity in SLE is coupled to alloimmunization-associated immune programs in vivo. These findings identify IFN-I score as a candidate biomarker of alloimmunization susceptibility in SLE and provide translational rationale for prospective studies incorporating transfusion outcome data.

Rheumatoid arthritis (RA) is a heritable and common autoimmune condition. To date, most genetic associations were derived from individuals with either European or East Asian ancestries. Here, we applied a multimodal automated phenotyping strategy to define RA and performed a genome-wide association study (GWAS) of RA in the Million Veteran Program (MVP), including underrepresented African American (AFR) and Admixed American (AMR) populations. Meta-analyses with previous RA cohorts identified 152 autosomal genome-wide significant loci, of which 31 were novel. Inclusion of multi-ancestry data dramatically improved fine-mapping resolution. Functional characterization of these loci using single-cell transcriptomic and chromatin data suggested new RA genes such as CHD7 and CD247. We identified underappreciated functional roles of fine-grained immune cell states other than T cells, such as B cell and myeloid cell states. We observed that multi-ancestry polygenic risk scores using our data demonstrated better predictive ability, especially for AFR and AMR populations.

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.

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.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID are complex chronic conditions that often follow infectious triggers with overlapping clinical features but poorly defined pathophysiological relationships. This study aimed to identify disease-specific immune signatures through multiparameter immunophenotyping of monocytes, dendritic cells, and T-cell subsets. A total of 207 participants were included (ME/CFS: n = 103; long COVID: n = 63; healthy controls: n = 41). Peripheral blood mononuclear cells were analyzed using multiparameter flow cytometry. Statistical analyses included non-parametric testing, age-adjusted ANCOVA, correlation network analysis, and principal component analysis (PCA). Long COVID was characterized by increased M2-like monocyte polarization, elevated CD80 expression across monocyte subsets, expansion of dendritic cells, and reduced expression of activation markers, indicating persistent immune activation with features of immune exhaustion. In contrast, ME/CFS exhibited reduced costimulatory molecule expression, impaired CCR7-mediated immune cell trafficking, and less coordinated activation patterns, consistent with a state of immune suppression. Correlation network analysis revealed more extensive and integrated immune interactions in long COVID, while PCA identified distinct immunophenotypic components and enabled moderate discrimination between the two conditions. These findings demonstrate that ME/CFS and long COVID are characterized by distinct immune profiles, supporting the concept of divergent immunopathological mechanisms. The identified signatures may contribute to biomarker development and guide targeted therapeutic approaches.

ELF4 is an ETS family transcription factor involved in immune regulation, and germline loss-of-function mutations in ELF4 have been known as deficiency in ELF4, X-linked (DEX). To date, ELF4-related disease has been exclusively associated with germline mutations. Here, we report a pediatric patient with recurrent mucocutaneous inflammation and periodic fever caused by a somatic truncating mutation in ELF4. By directly comparing ELF4-mutant and wild-type immune cells within the same individual using full-length single-cell RNA sequencing, we identified mutation-associated transcriptional alterations across multiple immune cell types. Pathway analyses revealed cell type-specific immune alterations, characterized by reduced antiviral and interferon-related signaling in NK cells and enhanced inflammatory pathways related to Th17 differentiation and inflammatory bowel disease in CD16 monocytes. This study expands the disease spectrum of ELF4 deficiency by identifying somatic truncation of ELF4 as a genetic mechanism underlying autoinflammatory diseases and biased immune programs.

Multisystem inflammatory syndrome in children (MIS-C) is a pediatric hyperinflammatory disease manifesting 4-6 weeks after SARS-CoV-2 infection. While the immunological hallmarks of MIS-C have been defined, few details regarding the underlying disease pathology have been resolved. To address this, we used a multiomics approach to profile the plasma and peripheral immune cells of 13 acute MIS-C patients, 18 recovered MIS-C follow-ups resampled over multiple time points (1-18 months), and 15 healthy pediatric controls. Despite rapid clinical disease resolution, circulating pro-inflammatory (IL-8, IL-6, IL-1, IL-1{beta}, TNF-{beta}) and TH2-type cytokines (IL-4, IL-5, IL-13) remained elevated up to three months post-MIS-C onset, revealing a subclinical inflammatory state that endures in recovered children. Surprisingly, the majority of patient-expanded TCRs recognizing SARS-CoV-2 epitopes were cross-reactive (75%, 12/16 SARS-CoV-2 TCRs) for autoantigens related to prostaglandin biology and insulin metabolism, suggesting a breakdown of self-tolerance via SARS-CoV-2 molecular mimicry. Indeed, autoantibody screening confirmed that 13 gene targets with self-antigen peptides also exhibited elevated autoantibodies in MIS-C patients. Further, autoreactive TCR expansions lasted over time and correlated with cytokines involved in allergic inflammation. Together, our findings point to a mechanism of sustained autoimmunity wherein promiscuous TCRs recognize both viral and self-antigens that are activated during primary SARS-CoV-2 infection in children who develop MIS-C. Upon onset, these circulating cross-reactive T cells drive clinically apparent sterile autoinflammation that persists subclinically into convalescence.

Multiple sclerosis (MS) is a debilitating disease affecting more than 1 million Americans, and today is assessed primarily through magnetic resonance imaging (MRI) and observational clinical symptoms. Given the autoimmune nature of MS, we hypothesized that high-dimensional gene expression data from peripheral blood mononuclear cells (PBMCs), when analyzed with the assistance of AI, may collectively serve as valuable biomarkers for the real-time risk and progression of MS. Here, we present PBMC RNA sequencing (RNAseq) results from N=997 samples, including 540 MS, 221 neuromyelitis optica (NMO), and 149 healthy controls. We constructed and optimized ensemble models for three clinical outcomes: (1) discrimination of early MS (EDSS [&le;] 2.0) from healthy individuals with 74% AUC at 100% coverage, (2) differential diagnosis of MS from NMO with 91% AUC at 80% coverage, and (3) subtyping RRMS from progressive MS with 79% AUC at 80% coverage. To our knowledge, no prior molecular test has been reported for any of these three MS clinical tasks, and these results may have immediate impact on clinical management of MS patients. Two innovations that improved the stratification accuracy of our models: selection of gene sets based on expression variance in disease states, and use of non-linear rank sort and conviction weighting in the ensemble score calculation.

Genome-wide association studies of idiopathic pulmonary fibrosis (IPF) have identified 35 common genetic risk loci associated with IPF susceptibility. In this study, we evaluated the effects of the reported variants in clinically curated non-European individuals. Despite limited sample sizes, we observed partial replication, limited transferability of some variants and evidence of ancestry-specific effects. The MUC5B promoter variant rs35705950 emerged as the dominant and most consistent signal across ancestries. Our findings highlight the need for larger, well-characterised studies in understudied populations to support robust discovery and translation.

Background: Extreme-phenotype comparisons allowed the discovery of novel asthma genetic risk loci. However, this approach remains unexplored in epigenome-wide association studies (EWAS). We aimed to identify bulk and cell-specific methylation markers of asthma with severe exacerbations across diverse ancestry groups. Methods: We conducted a meta-EWAS of 739,543 CpGs in whole blood among 1,192 African American and Latino pediatric populations, comparing non-asthmatics and asthma exacerbators. Genome-wide CpGs were followed up for replication in a meta-analysis across 1,516 ethnically diverse participants and in a cross-tissue evaluation of 393 nasal samples. We conducted differentially methylated region (DMRs), cell-type-deconvoluted, and quantitative trait loci analyses (whole-genome sequencing n=1,668; RNA-seq n=1,209). We examined enrichment in traits, pathways, and druggable genes, and analyzed DNAm predictors of plasma proteins and aging. Results: DNAm at 505 CpGs and 119 DMRs in whole blood were associated with asthma exacerbations (p<9x10-8, {lambda}=1.05). We replicated 25 CpGs in blood cells, cross-validated 7 in nasal samples, and detected 42 cell-specific DNAm markers mainly driven by T cells. DNAm at 134 CpGs was associated with gene expression in whole blood, including 118 associations with T-cell receptor genes, and 446 CpGs were regulated by [&ge;]1 genetic variant. We found enrichment for previous associations with environmental exposures, immune disorders, immune and inflammatory pathways, and druggable genes by developmental drugs. 21 methylation-predicted plasma proteins, involved in host defense, and one lung aging clock were associated with asthma exacerbations. Conclusions: The first meta-EWAS of extreme asthma phenotypes identified hundreds of novel DNAm markers, suggesting novel methylation biomarkers and candidate drugs for asthma and supporting the role of T cells.

Neonatal sepsis caused by Klebsiella pneumoniae is a major cause of under-five mortality in sub-Saharan Africa, and the rapid increase of infections caused by bacteria resistant to most or all available antimicrobials severely limits treatment options. An effective, maternally-administered vaccine could make a substantial reduction in neonatal sepsis and associated negative outcomes, as well as reduce the overall need for antimicrobials, a key driver of antimicrobial resistance. This study explored the potential for a maternally administered protein-based vaccine to provide neonatal protection via antibodies transferred transplacentally and through breastfeeding. A case-control study of mother and baby dyads was designed with 20 neonates developing K. pneumoniae sepsis and 80 uninfected control neonates to analyse breastmilk IgA, cord blood IgG and maternal serum IgA and IgG antibodies on a protein microarray with 161 selected K. pneumoniae proteins representing 152 unique genes. This analysis identified a set of proteins eliciting antibody responses, some associated with lack of K. pneumoniae sepsis, that indicate the presence of potentially protective antibodies. This is an essential first step in exploring surface protein accessibility, despite the large capsule. We highlight fimbrial structures, conjugative pili, and small lipoproteins associated with large outer membrane complexes as potential protein vaccine targets.

Genome-guided dietary advice is a goal of precision nutrition. However, the contribution of gene-diet interactions (GxDs) to disease risk remains unclear, hindering the identification of diet-outcome pairs more likely amenable to genetic-based recommendations. We thus implemented a two-step approach: first, we comprehensively assessed the contributions of genome-wide GxDs to cardiometabolic outcomes across a broad array of dietary exposures in UK Biobank participants (N = 141,144 to 325,989). Second, we selected the 20 significant diet-outcome pairs from the 713 pairs tested (p < 7.0 x 10-5) and derived GxD polygenic scores. In an independent sample, all scores were nominally associated with their corresponding outcomes, with 12 of 20 polygenic scores Bonferroni significant (p < 0.0025). Further analyses revealed GxD polygenic scores were associated with clinical outcomes such as incident gout, suggesting translational potential. Altogether, these results showcase the promise of GxD scores to inform precision nutrition.

Purpose: Aicardi-Goutieres syndrome (AGS) is a type I interferonopathy presently associated with nine genes. PTPN1 is a negative regulator of the interferon pathway previously associated with chronic inflammation and recently type 1 IFN autoinflammation. Methods: Genomic data from undiagnosed individuals with suspected AGS were interrogated for PTPN1 variants, and predicted loss-of-function (pLOF) and damaging missense variants in PTPN1 were sought in two additional academic databases as well as the All of Us database. Results: We identified 13 cases with ultra-rare heterozygous pLOF or highly damaging missense variants in PTPN1. Nine cases were identified in a cohort of 53 individuals (~ 17%) with clinical, imaging and persistent biochemical features of AGS. Median age of onset is 1.75 years (IQR 0.67), significantly later (p< 0.0001) than other AGS genotypes. Four additional cases were identified in academic datasets with variable clinical features suggestive of autoinflammation. Additionally, 49 individuals with ultra-rare, damaging PTPN1 variants were identified in the All of Us database, none had features suggestive of AGS, but autoimmunity was highly prevalent (~21.6%). Conclusion: Our data implicate PTPN1 as a cause of later-onset presentations of AGS within a broader spectrum of autoinflammatory phenotypes. Segregation and biobank data demonstrate reduced penetrance, with carriers being enriched for autoimmune disorders.

BackgroundWe explored the efficacy of AS01E-adjuvanted respiratory syncytial virus prefusion F protein-based vaccine (adjuvanted RSVPreF3) in subpopulations of participants with underlying medical conditions in the multi-country, phase 3 AReSVi-006 trial (conducted May/2021-May/2024). MethodsMedically stable [&ge;]60-year-olds were 1:1-randomised to receive one adjuvanted RSVPreF3 or placebo dose pre-RSV season 1. In exploratory post-hoc analyses in subgroups of participants with underlying conditions (including COPD, asthma, diabetes, obesity [BMI[&ge;]30 kg/m2]), we evaluated efficacy of one vaccine dose against RSV-related lower respiratory tract disease (RSV-LRTD), acute respiratory illness (RSV-ARI), and RSV-ARI-related complications (e.g., pneumonia, COPD/asthma exacerbation, cardiovascular events). We also evaluated (post-hoc) RSV-ARI-related systemic corticosteroid and antibiotics use in participants with COPD or asthma. ResultsThe efficacy analyses comprised 12,468 vaccine and 12,498 placebo recipients. Efficacy against RSV-LRTD over three RSV seasons was similar among participants with COPD (75.1%, 95% CI: 40.2-91.4), asthma (65.8%, 31.0-84.7), diabetes (69.8%, 37.5-87.1), and obesity (74.1%, 56.4-85.5) as in the overall study population (62.9%, 97.5% CI: 46.7-74.8). Efficacy was also observed against RSV-ARI in these subgroups. Efficacy against RSV-ARI-related complications was 74.4% (95% CI: 11.2-95.2) in participants with COPD and 60.8% (-9.9-88.7) in those with asthma. Among participants with COPD, 15.4% (1.9-45.4) of RSV-ARI episodes in vaccine vs 22.4% (12.5-35.3) in placebo recipients were treated with systemic corticosteroids, and 46.2% (19.2-74.9) vs 56.9% (43.2-69.8) with antibiotics. ConclusionsPost-hoc analyses of the AReSVi-006 trial suggest that adjuvanted RSVPreF3 may help prevent RSV-ARI, RSV-LRTD, and RSV-related complications in medically stable older adults with underlying medical conditions like COPD and asthma. Trial registrationClinicalTrials.gov: NCT04886596 SummaryPost-hoc analyses of the AReSVi-006 trial suggest that 1 dose of adjuvanted RSVPreF3 may help prevent RSV-related illness and complications over 3 consecutive RSV seasons in subgroups of [&ge;]60-year-olds with chronic medical conditions, e.g., COPD and asthma.

Background: COVID vaccination with periodically updated compositions remains important as SARS-CoV-2 continues to circulate, cause disease, and evolve. Available COVID-19 vaccines in the 2024-2025 season differed by platform, including mRNA-1273, an mRNA-based vaccine, and NVX-CoV2705, a recombinant protein-based vaccine and antigen composition (KP.2-targeted and JN.1-targeted, respectively). There is limited head-to-head real-world evidence comparing the effectiveness of these different approaches to prevention of severe outcomes with COVID-19. We compared mRNA-1273 with protein-based NVX-CoV2705 in insured US adults vaccinated during the 2024-2025 season. Methods: We conducted a retrospective matched cohort study in a large US claims database. Adults aged 18 years or older who received mRNA-1273 or NVX-CoV2705 between Aug 31, 2024 and Feb 28, 2025 were eligible. Recipients were exactly matched 2:1 on key demographic and clinical factors and then weighted with stabilized inverse probability of treatment weights. Outcomes were medically-attended COVID-19 and hospitalization with COVID-19 from day 7 after vaccination through up to 180 days of follow-up. We calculated comparative vaccine effectiveness (cVE) as 100 x (1-- hazard ratio). Results: Of 858,138 eligible mRNA-1273 recipients and 34,667 eligible NVX-CoV2705 recipients, 69,140 and 34,570, respectively, entered the matched cohort. Median (Q1, Q3) follow-up was 180 (163, 180) days for mRNA-1273 and 180 (162,180) for NVX-CoV2705. Medically attended COVID-19 occurred in 706 (1.02%) mRNA-1273 recipients and 512 (1.48%) NVX-CoV2705 recipients; adjusted cVE (95% CI) was 31.7% (23.4%, 39.1%). Hospitalization with COVID-19 occurred in 61 (0.09%) and 49 (0.14%) recipients, respectively; adjusted cVE (95% CI) was 40.7% (13.5%, 59.4%). In the 47,754 mRNA-1273 recipients matched to 23,877 NVX-CoV2705 recipients aged [&ge;]65, adjusted cVE (95% CI) was 25.7% (15.4%, 34.8%) against medically-attended COVID-19 and 41.7% (14.3%, 60.4%) against hospitalization with COVID-19. Conclusions: In this insured US adult population, mRNA-1273 demonstrated greater effectiveness against medically attended COVID-19 and hospitalization with COVID-19 than the protein-based NVX-CoV2705. These findings highlight the potential public-health importance of considering vaccine platform and variant selection when planning for upcoming seasons.