Background Multisystem inflammatory syndrome in children (MIS-C) is a sequela of SARS-CoV-2 infection; however, longitudinal cardiac outcomes are unclear. Herein, we test the association between MIS-C biomarkers, inpatient echocardiographic features, and outcomes of interest: presence of myocarditis and myocardial delayed enhancement (MDE) on cardiac magnetic resonance (CMR). Furthermore, we describe the evolution of CMR features in MIS-C. Methods Patients diagnosed with MIS-C from 2020-2021 with CMR were included. Admission and serial biomarkers and echocardiographic features were collected. Primary outcomes measured were diagnosis of myocarditis (using modified Lake Louise criteria) and myocardial delayed enhancement (quantified by full width at half maximum method) on CMR. Secondary outcomes included abnormal LVEF on admission echocardiogram and changes in parametric mapping with serial CMR. Results A total of 66 patients were included (median age 9.7 IQR [7.2-14.7] years). Admission BNP (P=0.016), CRP (P=0.027), and ESR (P=0.002) associated with LV dysfunction on inpatient echocardiogram. CMR1 was obtained a median of 38 [26-61] days after hospital presentation. Myocarditis was present in 44% and MDE in 52% on CMR1, with median MDE burden of 10.8 [8.5-16.8]% in those affected. Inpatient echocardiographic features were not associated with presence of myocarditis or MDE. Admission ESR (P=0.031) associated with MDE. Admission platelets associated with myocarditis (P=0.040) and MDE (P=0.004). CMR2 (n=19), occurring a median of 11 [7-14] months after baseline CMR, demonstrated lower global T2 z-scores (P=0.035) without significant change in global T1 z-scores or ECV. Myocarditis (16% [3/19]) and MDE (28% [5/18]) were less frequent on CMR2. Conclusions For MIS-C patients, initial echocardiographic indices do not associate with myocarditis or MDE by CMR one month later; admission ESR and platelet levels may portend myocarditis or MDE on initial CMR. Reduced T2 z-score over serial CMR suggests resolving edema.

Objective Systemic lupus erythematosus (SLE) is an autoimmune disease that affects numerous organs. Neutrophil extracellular traps (NETs) contribute to sterile inflammation and autoantibody generation in SLE. Isolevuglandins (isoLGs) are reactive oxygen species that are formed during NETosis and contribute to chromatin expansion. Scavenging of isoLGs attenuates SLE disease activity and hypertension in murine models of SLE. We hypothesized that isoLGs drive NETosis in SLE. Methods Neutrophils were isolated from patients with SLE (n = 6), treated with the isoLG scavenger ethyl‐2‐hydroxybenzylamine (Et‐2‐HOBA), and evaluated for NETosis by immunofluorescence. Single‐cell sequencing was performed on lymphoid tissue from SLE‐prone B6.SLE123 mice treated with the isoLG scavenger 2‐hydroxybenzylamine (2‐HOBA). Flow cytometry was performed to quantify neutrophils and NETs in B6.SLE123 mice (n = 11–15). Results In neutrophils isolated from patients with SLE, Et‐2‐HOBA prevented NETosis (P < 0.05). In SLE‐prone mice, 2‐HOBA reduced neutrophil counts, inflammatory gene expression, circulating neutrophil counts (P < 0.0001), and aortic NETosis (P < 0.05). Conclusion These findings suggest that isoLGs contribute to systemic autoimmunity and vascular inflammation by driving neutrophil migration and NETosis in SLE.

Background Ascertaining a true cohort of juvenile idiopathic arthritis (JIA) patients using claims and electronic health record (EHR) data is challenging due to clinical complexities. This study aims to develop a computable JIA phenotype using large databases with multi-site validation and replication. Methods This multi-institutional study used reporting resources at three sites identified through the Maternal and Pediatric Precision in Therapeutics Hub. Subjects with ICD-9 and ICD-10-CM codes for JIA and/or psoriatic juvenile arthropathy and age ≤20 at first eligible encounter were included with exclusion of subjects with multiple ICD codes for systemic lupus erythematosus, dermatomyositis, and polymyositis. Each site manually reviewed a subset of charts to validate diagnosis. Summary statistics on variations of encounter counts with a JIA diagnosis are reported. Results There were 8093 subjects identified with potential JIA. Manual review of 253 (3 %) subjects provided a positive predictive value (PPV) of 0.74 in an initial cohort of one code count with exclusion criteria. As the number of JIA code counts required for inclusion increased, the number of subjects with JIA identified decreased, and the PPV increased. When using ≥4 code counts for JIA, age ≤20 years old, and excluding other conditions, the PPV was 0.95, with an estimated 5377 subjects. Conclusion We developed and reproduced a computable and portable phenotype algorithm to identify JIA patients in structured, retrospective data, validated this across multiple institutions, and demonstrated its consistent performance across sites. This approach supports broader adoption in collaborative research networks to enhance the accuracy of JIA studies.

Hypoparathyroidism, sensorineural deafness, and renal dysplasia (HDR) syndrome is caused by pathogenic variants in the GATA3 gene located on chromosome 10p14. Here we present a 10-year-old girl with HDR syndrome who also has oligoarticular juvenile idiopathic arthritis (JIA). The patient presented for genetics evaluation with bilateral sensorineural hearing loss, oligoarticular JIA, and a renal cyst. Trio-based exome sequencing and chromosome microarray analysis revealed a pathogenic heterozygous ~1.45 Mb deletion that included the entire GATA3 gene, consistent with a diagnosis of HDR syndrome. GATA3 is a risk locus associated with autoimmune disease, including rheumatoid arthritis; however, the link between protein-coding variants in GATA3 and autoimmune disease has not been well established. Previously, a single patient with HDR syndrome and psoriatic JIA was identified as having a frameshift variant in the GATA3 gene. These reports highlight the potential for increased susceptibility to early-onset autoimmune arthritis in HDR syndrome, expanding its phenotypic spectrum. Further studies are needed to investigate the role of pathogenic variants in the GATA3 gene in the pathogenesis of JIA and other autoimmune diseases.

BACKGROUND:Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious complication of severe acute respiratory syndrome coronavirus 2 infection. Features of MIS-C overlap with those of Kawasaki disease (KD). OBJECTIVE:The study objective was to develop a prediction model to assist with this diagnostic dilemma. METHODS:Data from a retrospective cohort of children hospitalized with KD before the coronavirus disease 2019 pandemic were compared to a prospective cohort of children hospitalized with MIS-C. A bootstrapped backwards selection process was used to develop a logistic regression model predicting the probability of MIS-C diagnosis. A nomogram was created for application to individual patients. RESULTS:Compared to children with incomplete and complete KD (N = 602), children with MIS-C (N = 105) were older and had longer hospitalizations; more frequent intensive care unit admissions and vasopressor use; lower white blood cell count, lymphocyte count, erythrocyte sedimentation rate, platelet count, sodium, and alanine aminotransferase; and higher hemoglobin and C-reactive protein (CRP) at admission. Left ventricular dysfunction was more frequent in patients with MIS-C, whereas coronary abnormalities were more common in those with KD. The final prediction model included age, sodium, platelet count, alanine aminotransferase, reduction in left ventricular ejection fraction, and CRP. The model exhibited good discrimination with AUC 0.96 (95% confidence interval: [0.94-0.98]) and was well calibrated (optimism-corrected intercept of -0.020 and slope of 0.99). CONCLUSIONS:A diagnostic prediction model utilizing admission information provides excellent discrimination between MIS-C and KD. This model may be useful for diagnosis of MIS-C but requires external validation.

Objective: Pediatric patients have different diseases and outcomes than adults; however, existing phecodes do not capture the distinctive pediatric spectrum of disease. We aim to develop specialized pediatric phecodes (Peds-Phecodes) to enable efficient, large-scale phenotypic analyses of pediatric patients. Materials and Methods: We adopted a hybrid data- and knowledge-driven approach leveraging electronic health records (EHRs) and genetic data from Vanderbilt University Medical Center to modify the most recent version of phecodes to better capture pediatric phenotypes. First, we compared the prevalence of patient diagnoses in pediatric and adult populations to identify disease phenotypes differentially affecting children and adults. We then used clinical domain knowledge to remove phecodes representing phenotypes unlikely to affect pediatric patients and create new phecodes for phenotypes relevant to the pediatric population. We further compared phenome-wide association study (PheWAS) outcomes replicating known pediatric genotype-phenotype associations between Peds-Phecodes and phecodes. Results: The Peds-Phecodes aggregate 15,533 ICD-9-CM codes and 82,949 ICD-10-CM codes into 2,051 distinct phecodes. Peds-Phecodes replicated more known pediatric genotype-phenotype associations than phecodes (248 versus 192 out of 687 SNPs, p<0.001). Discussion: We introduce Peds-Phecodes, a high-throughput EHR phenotyping tool tailored for use in pediatric populations. We successfully validated the Peds-Phecodes using genetic replication studies. Our findings also reveal the potential use of Peds-Phecodes in detecting novel genotype-phenotype associations for pediatric conditions. We expect that Peds-Phecodes will facilitate large-scale phenomic and genomic analyses in pediatric populations. Conclusion: Peds-Phecodes capture higher-quality pediatric phenotypes and deliver superior PheWAS outcomes compared to phecodes.

Abstract Background Multisystem Inflammatory Syndrome in Children (MIS-C) is a rare sequela that typically develops 2–6 weeks after SARS-CoV-2 infection. According to CDC recommendations, children who recover from MIS-C should be vaccinated 90 days after diagnosis, but safety and immunogenicity data are lacking. Our aim was to evaluate the safety and immunogenicity of one dose of the BNT162b2 vaccine in children with a history of MIS-C. Methods We conducted a longitudinal study of children with MIS-C admitted to Monroe Carell Jr. Children's Hospital at Vanderbilt from 7/11/2020 to 3/23/2022. Children were eligible if they met CDC’s MIS-C criteria and had blood collected before and after SARS-CoV-2 vaccination. Clinical data were obtained from medical records and injection site and systemic reactions were recorded for a week following SARS-CoV-2 vaccination via memory aids. IgG against SARS-CoV-2 nucleocapsid (N), spike receptor-binding domain (RBD), and spike extracellular domain (ECD) was detected using an enzyme-linked immunosorbent assay. The first anti-RBD and anti-ECD levels prevaccination and postvaccination were compared using the paired-samples t-test. Results Seven children were included, of whom five were male and five were non-Hispanic White. The first blood sample was collected 3–44 days following admission. The median age at admission was 15.8 years (IQR, 10.5–14.7 years), and the median time from admission to vaccination was 7 months (IQR, 6–8 months). Five children each had injection site or systemic reactions (Figure 1); the majority were mild or moderate and occurred within 2 days of vaccination. Children were followed for a median of 5.6 months (4.3–6.2 months) postvaccination; none developed MIS-C recurrence. Following vaccination, mean anti-RBD and anti-ECD levels increased by 2.0 (1.2–2.9; p < 0.001) and 1.9 (1.2–2.6; p < 0.001) absorbance units, respectively (Figure 2). A sensitivity analysis excluding children with antibody evidence of reinfection (increase in anti-N level ≥ 0.5) showed similar results. Figure 1Safety of SARS-CoV-2 vaccination in children with a history of MIS-C. Figure 2 Immunogenicity of SARS-CoV-2 vaccination in children with a history of MIS-C. The best-fit lines (LOESS) are indicated in black. The dashed line indicates the day of vaccination. Conclusion SARS-CoV-2 vaccination is safe and immunogenic in children with a history of MIS-C, with no documented recurrence of MIS-C–like illness. Further studies are needed to determine the optimal timing, safety, and immunogenicity of vaccination following MIS-C. Disclosures Natasha B. Halasa, MD, Quidel: Grant/Research Support|Quidel: equipment donation|Sanofi: Grant/Research Support|Sanofi: HAI testing and vaccine donation.

Background Multisystem inflammatory syndrome in children (MIS-C) is a febrile syndrome that is observed in the pediatric population following severe acute respiratory syndrome 2 (SARS-CoV-2) infection. Vaccines have prevented or lessened the severity of the initial acute respiratory infection, while their effectiveness against severe MIS-C is just beginning to be reported. Case presentation Here we report a fully vaccinated teenage female with no known history of SARS-CoV-2 infection who presented with shock and heart failure. Her presentation was initially thought secondary to a retropharyngeal abscess but was later identified as MIS-C after confirmed nucleocapsid antibody. Conclusions Given the recent Omicron waves, the ongoing international outbreaks with evolving variants and the continued evolution of the COVID-19 pandemic, this case emphasizes the need to include MIS-C in the differential diagnosis, even in a fully vaccinated, previously healthy child.

Objective Features of multisystem inflammatory syndrome in children (MIS‐C) overlap with other syndromes, making the diagnosis difficult for clinicians. We aimed to compare clinical differences between patients with and without clinical MIS‐C diagnosis and develop a diagnostic prediction model to assist clinicians in identification of patients with MIS‐C within the first 24 hours of hospital presentation. Methods A cohort of 127 patients (<21 years) were admitted to an academic children's hospital and evaluated for MIS‐C. The primary outcome measure was MIS‐C diagnosis at Vanderbilt University Medical Center. Clinical, laboratory, and cardiac features were extracted from the medical record, compared among groups, and selected a priori to identify candidate predictors. Final predictors were identified through a logistic regression model with bootstrapped backward selection in which only variables selected in more than 80% of 500 bootstraps were included in the final model. Results Of 127 children admitted to our hospital with concern for MIS‐C, 45 were clinically diagnosed with MIS‐C and 82 were diagnosed with alternative diagnoses. We found a model with four variables—the presence of hypotension and/or fluid resuscitation, abdominal pain, new rash, and the value of serum sodium—showed excellent discrimination (concordance index 0.91; 95% confidence interval: 0.85‐0.96) and good calibration in identifying patients with MIS‐C. Conclusion A diagnostic prediction model with early clinical and laboratory features shows excellent discrimination and may assist clinicians in distinguishing patients with MIS‐C. This model will require external and prospective validation prior to widespread use.

In juvenile idiopathic arthritis (JIA) inflammatory T cells and their produced cytokines are drug targets and play a role in disease pathogenesis. Despite their clinical importance, the sources and types of inflammatory T cells involved remain unclear. T cells respond to polarizing factors to initiate types of immunity to fight infections, which include immunity types 1 (T1), 2 (T2), and 3 (T17). Polarizing factors drive CD4+ T cells towards T helper (Th) cell subtypes and CD8+ T cells towards cytotoxic T cell (Tc) subtypes. T1 and T17 polarization are associated with autoimmunity and production of the cytokines IFNγ and IL-17 respectively. We show that JIA and child healthy control (HC) peripheral blood mononuclear cells are remarkably similar, with the same frequencies of CD4+ and CD8+ naïve and memory T cell subsets, T cell proliferation, and CD4+ and CD8+ T cell subsets upon T1, T2, and T17 polarization. Yet, under T1 polarizing conditions JIA cells produced increased IFNγ and inappropriately produced IL-17. Under T17 polarizing conditions JIA T cells produced increased IL-17. Gene expression of IFNγ, IL-17, Tbet, and RORγT by quantitative PCR and RNA sequencing revealed activation of immune responses and inappropriate activation of IL-17 signaling pathways in JIA polarized T1 cells. The polarized JIA T1 cells were comprised of Th and Tc cells, with Th cells producing IFNγ (Th1), IL-17 (Th17), and both IFNγ-IL-17 (Th1.17) and Tc cells producing IFNγ (Tc1). The JIA polarized CD4+ T1 cells expressed both Tbet and RORγT, with higher expression of the transcription factors associated with higher frequency of IL-17 producing cells. T1 polarized naïve CD4+ cells from JIA also produced more IFNγ and more IL-17 than HC. We show that in JIA T1 polarization inappropriately generates Th1, Th17, and Th1.17 cells. Our data provides a tool for studying the development of heterogeneous inflammatory T cells in JIA under T1 polarizing conditions and for identifying pathogenic immune cells that are important as drug targets and diagnostic markers.

Abstract Background Multi-system inflammatory syndrome in children (MIS-C) is a rare consequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MIS-C shares features with common infectious and inflammatory syndromes and differentiation early in the course is difficult. Identification of early features specific to MIS-C may lead to faster diagnosis and treatment. We aimed to determine clinical, laboratory, and cardiac features distinguishing MIS-C patients within the first 24 hours of admission to the hospital from those who present with similar features but ultimately diagnosed with an alternative etiology. Methods We performed retrospective chart reviews of children (0-20 years) who were admitted to Vanderbilt Children’s Hospital and evaluated under our institutional MIS-C algorithm between June 10, 2020-April 8, 2021. Subjects were identified by review of infectious disease (ID) consults during the study period as all children with possible MIS-C require an ID consult per our institutional algorithm. Clinical, lab, and cardiac characteristics were compared between children with and without MIS-C. The diagnosis of MIS-C was determined by the treating team and available consultants. P-values were calculated using two-sample t-tests allowing unequal variances for continuous and Pearson’s chi-squared test for categorical variables, alpha set at < 0.05. Results There were 128 children admitted with concern for MIS-C. Of these, 45 (35.2%) were diagnosed with MIS-C and 83 (64.8%) were not. Patients with MIS-C had significantly higher rates of SARS-CoV-2 exposure, hypotension, conjunctival injection, abdominal pain, and abnormal cardiac exam (Table 1). Laboratory evaluation showed that patients with MIS-C had lower platelet count, lymphocyte count and sodium level, with higher c-reactive protein, fibrinogen, B-type natriuretic peptide, and neutrophil percentage (Table 2). Patients with MIS-C also had lower ejection fraction and were more likely to have abnormal electrocardiogram. Conclusion We identified early features that differed between patients with MIS-C from those without. Development of a diagnostic prediction model based on these early distinguishing features is currently in progress. Disclosures Natasha B. Halasa, MD, MPH, Genentech (Other Financial or Material Support, I receive an honorarium for lectures - it’s a education grant, supported by genetech)Quidel (Grant/Research Support, Other Financial or Material Support, Donation of supplies/kits)Sanofi (Grant/Research Support, Other Financial or Material Support, HAI/NAI testing) Natasha B. Halasa, MD, MPH, Genentech (Individual(s) Involved: Self): I receive an honorarium for lectures - it’s a education grant, supported by genetech, Other Financial or Material Support, Other Financial or Material Support; Sanofi (Individual(s) Involved: Self): Grant/Research Support, Research Grant or Support James A. Connelly, MD, Horizon Therapeutics (Advisor or Review Panel member)X4 Pharmaceuticals (Advisor or Review Panel member)

Abstract Background Multisystem inflammatory syndrome in children (MIS-C) is an illness associated with recent SARS-CoV-2 infection or exposure. Kawasaki disease (KD), a vasculitis with an unknown etiology, has overlapping clinical presentation with MIS-C, making it difficult to clinicians for distinguish between them. Therefore, we aimed to compare demographic, laboratory, and clinical characteristics between MIS-C and KD in hospitalized children in Nashville, TN. Methods We conducted a single-center retrospective chart review for hospitalized children under 18 years who met American Heart Association criteria for KD and were treated with intravenous immunoglobulin from May 2000 to December 2019, and children meeting the CDC criteria for MIS-C from July 2020 to May 2021. Data abstraction for patients’ demographics, clinical presentation, laboratory values and imaging results was performed. Pearson’s chi-squared test for categorical variables and Wilcoxon rank sum test for continuous variables, with alpha=5%, were used to compare groups. Results A total of 603 KD and 52 MIS-C hospitalized patients were included. Children with MIS-C were older than those with KD. A higher frequency of male sex was noted in both groups, with no significant differences in race and ethnicity (Table). MIS-C children frequently presented with symptoms similar to KD (63.5% rash, 55.8% conjunctivitis, 28.9% mucous membrane changes); however, only one MIS-C patient met criteria for complete KD (Figure). Both MIS-C and KD children presented with elevated CRP and ESR, but the median value of CRP in MIS-C children was significantly higher (Table). In addition, white cell count was lower in MIS-C children, which is primarily driven by the lower absolute lymphocyte count in this group (0.9 vs 2.7, p< 0.001), and echocardiography was more likely to be abnormal at presentation compared to KD (Table). Table. Comparison of Sociodemographic, Clinical, and Laboratory Characteristics among Children with Kawasaki Disease and Multisystem Inflammatory Syndrome in Nashville Figure. Comparison of Kawasaki Criteria Between Children with Multisystem Inflammatory Syndrome and Kawasaki Disease Conclusion MIS-C and KD present similarly in children; however, age, laboratory and echocardiography findings can help differentiate between them. Different laboratory values suggest different pathophysiology and inflammatory mediators behind these two illnesses, warranting further research. Disclosures Natasha B. Halasa, MD, MPH, Genentech (Other Financial or Material Support, I receive an honorarium for lectures - it’s a education grant, supported by genetech)Quidel (Grant/Research Support, Other Financial or Material Support, Donation of supplies/kits)Sanofi (Grant/Research Support, Other Financial or Material Support, HAI/NAI testing) Natasha B. Halasa, MD, MPH, Genentech (Individual(s) Involved: Self): I receive an honorarium for lectures - it’s a education grant, supported by genetech, Other Financial or Material Support, Other Financial or Material Support; Sanofi (Individual(s) Involved: Self): Grant/Research Support, Research Grant or Support

Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein that disrupt its folding pathway. The most common mutation causing CF is a deletion of phenylalanine at position 508 (ΔF508). CFTR contains five domains that each form cotranslational structures that interact with other domains as they are produced and folded. CFTR is comprised of two transmembrane spanning domains (TMDs), two nucleotide binding domains (NBDs) and a unique regulatory region (R). The first domain translated, TMD1, forms interdomain interactions with the other domains in CFTR. In TMD1, long intracellular loops extend into the cytoplasm and interact with both NBDs via coupling helices and with TMD2 via transmembrane spans (TMs). We examined mutations in TMD1 to determine the impact on individual domain and multidomain constructs. We found that mutations in a TM span or in the cytosolic ICLs interfere with specific steps in the hierarchical folding of CFTR. TM1 CF-causing mutants, G85E and G91R, directly affect TMD1, whereas most ICL1 and ICL2 mutant effects become apparent in the presence of TMD2. A single mutant in ICL2 worsened CFTR trafficking in the presence of NBD2, supporting its role in the ICL2-NBD2 interface. Mutation of hydrophobic residues in ICL coupling helices tended to increased levels of pre-TMD2 biogenic intermediates but caused ER accumulation in the presence of TMD2. This suggests a tradeoff between transient stability during translation and final structure. NBD2 increased the efficiency of mutant trafficking from the ER, consistent with stabilization of the full-length constructs. While the G85E and G91R mutants in TM1 have immediately detectable effects, most of the studied mutant effects and the ΔF508 mutant are apparent after production of TMD2, supporting this intermediate as a major point of recognition by protein quality control.

Neonatal multisystem onset inflammatory disorder (NOMID) is a severe autoinflammatory syndrome that can have an initial presentation as infantile urticaria. Thus, an immediate recognition of the clinical symptoms is essential for obtaining a genetic diagnosis and initiation of early therapies to prevent morbidity and mortality. Herein, we describe a neonate presenting with urticaria and systemic inflammation within hours after birth who developed arthropathy and neurologic findings. Pathologic evaluation of the skin revealed an infiltration of lymphocytes, eosinophils, and scattered neutrophils. Genetic analysis identified a novel heterozygous germline variant of unknown significance in the NLRP3 gene, causing the missense mutation M408T. Variants of unknown significance are common in genetic sequencing studies and are diagnostically challenging. Functional studies of the M408T variant demonstrated enhanced formation and activity of the NLRP3 inflammasome, with increased cleavage of the inflammatory cytokine IL-1β. Upon initiation of IL-1 pathway blockade, the infant had a robust response and improvement in clinical and laboratory findings. Our experimental data support that this novel variant in NLRP3 is causal for this infant’s diagnosis of NOMID. Rapid assessment of infantile urticaria with biopsy and genetic diagnosis led to early recognition and targeted anti-cytokine therapy. This observation expands the NOMID-causing variants in NLRP3 and underscores the role of genetic sequencing in rapidly identifying and treating autoinflammatory disease in infants. In addition, these findings highlight the importance of establishing the functional impact of variants of unknown significance, and the impact this knowledge may have on therapeutic decision making.

AbstractObjectiveT helper cells develop into discrete Th1, Th2 or Th17 lineages that selectively express IFNγ, IL-4/IL-5/IL-13, or IL-17, respectively and actively silence signature cytokines expressed by opposing lineages. Our objective was to compare Th1, Th2 and Th17 polarization in cell culture models using JIA patient samples.MethodsPeripheral blood mononuclear cells were isolated from JIA or healthy prepubescent children. T cell naïve and memory phenotypes were assessed by flow cytometry. T cell proliferation was measured using a fluorescence-based assay. Th cell cultures were generated in vitro and IFNγ, IL-17, and TNFα measured by ELISA and flow cytometry.ResultsJIA Th1 cells produced increased IFNγ and inappropriately produced IL-17. JIA Th17 cells produced increased IL-17. JIA Th1 cell cultures develop dual producers of IFNγ and IL-17, which are Th1.17 cells. JIA Th1 cultures expressed elevated levels of both T-bet and RORγT. RNA sequencing confirmed activation of immune responses and inappropriate activation of IL-17 signaling pathways in Th1 cultures. A subset of JIA patient samples was disproportionally responsible for the enhanced IFNγ and IL-17 phenotype and Th1.17 phenotype.ConclusionsThis study reveals that JIA patient uncommitted T cell precursors, but not healthy children, inappropriately develop into inflammatory effector Th1.17 and Th17 cells under Th1 polarizing conditions.Rheumatology key messagesTh1 differentiation of JIA PBMCs generates high IFNγ, IL-17, and dual IFNγ-IL-17 producing cells.JIA Th1 differentiation increases master transcription factor expression for Tbet and RORγT.Enhanced JIA Th1 IFNγ and IL-17 production occurs in a subset of JIA patients.

Background: The objective of this study was to develop an algorithm that accurately identifies juvenile idiopathic arthritis (JIA) patients in the electronic health record (EHR). Methods: Algorithms were developed in a de-identified EHR by searching for a priori JIA ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes and JIA-related keywords. Exclusion criteria were selected to remove other autoimmune diseases. A training set of 200 patients was randomly selected from patients containing >= 1 occurrence of a JIA ICD-9 or ICD-10-CM code. Case status was determined by a rheumatology clinic note documenting a JIA diagnosis before age 20. For each algorithm, positive predictive value (PPV), sensitivity, and Fmeasure were determined using the training set. Results: We developed 103 algorithms using combinations of ICD codes, keywords, and exclusion criteria. The algorithm requiring 4 or more counts of JIA ICD-9 or ICD-10-CM codes, keywords "enthesitis" and "uveitis", and exclusion of ICD-9 or ICD-10-CM codes for systemic lupus erythematosus, dermatomyositis, polymyositis, and dermatopolymyositis had the highest PPV of 97% in the training set with an F-measure of 87%. There were 1,131 JIA cases returned by this algorithm. We validated the highest performing algorithm in a separate cohort from the training set with a PPV of 92% and an F-measure of 75%. Conclusion: We developed and validated JIA EHR algorithms with ICD-9 and ICD-10-CM codes to accurately identify a JIA cohort. Three algorithms achieved PPVs of 97%, each with different algorithm criteria, allowing for users to select an algorithm to best fit their research needs.

GATA3 is a transcription factor that is important during development and plays a role in differentiation and activity of immune cells, particularly T cells. Abnormal T cell function is found in autoimmune arthritis. We present the first known case of autoimmune arthritis associated with a novel GATA3 mutation. Whole exome sequencing of the proband was performed on a clinical basis. Peripheral blood mononuclear cells (PBMCs) were collected from the proband, healthy sibling, and parent. cDNA prepared from RNA was analyzed with polymerase chain reaction and Sanger sequencing. Intracellular proteins were assessed by immunoblot of PBMC homogenates. GATA3 in vitro activity was measured in HeLa cell cultures expressing a mammalian expression vector containing GATA3 or mutants generated by site-directed mutagenesis. GATA3 transcriptional activity was examined using a luciferase reporter assay system. T helper cell ex vivo function was evaluated by stimulating PBMCs to differentiate into effector T cells along Th0, Th1, Th2, and Th17 lineages, and re-stimulating effector cells to secrete cytokines. Cytokine production was measured by enzyme-linked immunosorbent assay. The proband is the first known case of autoimmune arthritis associated with a mutation in GATA3. The proband M401VfsX106 protein is expressed and has a dominant negative function on GATA3 transcriptional activity. The proband PBMCs have markedly increased differentiation along the Th1 and Th17 pathways, with decreased differentiation along the Th2 pathway. Unexpectedly, Th0 cells from the proband express high levels of IFNγ. Our research presents the first known case of autoimmune arthritis associated with a mutation in GATA3. This work expands the phenotypic spectrum of GATA3 mutations. It reveals the novel insight that decreased and altered GATA3 activity coincides with autoimmune arthritis. This work suggests that modulation of GATA3 may be a therapeutic approach for patients with autoimmune arthritis.