Abstract Background Pathogenic variants in KCNK3 have been implicated in pulmonary arterial hypertension (PAH); however, the molecular mechanisms underlying this association remain insufficiently defined. Methods Whole-exome sequencing was performed in a child with PAH and her mother. The impact of the identified variant on protein stability was evaluated using cycloheximide chase assays. Apoptotic activity in transfected cells was assessed through flow cytometry and western blotting analysis. RNA sequencing was conducted to identify signaling pathways associated with altered gene expression. Oxidative stress levels were examined using inverted fluorescence microscopy. Expression levels of NFE2L2 was quantified by quantitative real-time polymerase chain reaction and western blotting. Results A novel heterozygous KCNK3 variant (c.607G > C, p.G203R) was identified. The substituted glycine residue demonstrated high evolutionarily conservation, and in silico analysis predicted structural alteration of the protein. The p.G203R variant was associated with reduced KCNK3 protein stability and an increase in apoptosis in vitro. Transcriptomic analysis indicated enhanced vascular smooth muscle cell migratory potential in cells expressing the variant. Increased cellular OS and apoptosis were observed in cells expressing p.G203R KCNK3. Bioinformatic analysis identified NFE2L2 as a key downstream effector. Expression of NFE2L2 was reduced in pulmonary artery endothelial cells expressing p.G203R KCNK3, while overexpression of NFE2L2 partially reversed variant-induced apoptosis. Conclusion This study identifies a novel KCNK3 p.G203R variant associated with PAH and provides mechanistic evidence supporting its pathogenicity. These findings expand the variant landscape of KCNK3 in PAH and offer insights into disease pathogenesis that may inform future targeted therapeutic approaches.

Kawasaki disease (KD) is an acute systemic vasculitis in children that can result in severe cardiac complications. This study utilized an integrated proteomic and metabolomic approach to explore molecular dynamics in cardiac tissue from a Candida albicans cell wall extract (CAWS)-induced KD mouse model. Echocardiography demonstrated significant left ventricular dysfunction in the CAWS group, as evidenced by reduced ejection fraction and fractional shortening, alongside histopathological signs of inflammatory cell infiltration. Multi-omics analysis revealed 206 differentially expressed metabolites (DEMs) and 155 differentially expressed proteins (DEPs) compared to PBS controls. Bioinformatics analysis highlighted substantial disturbances in glycerophospholipid metabolism, amino acid metabolism, fatty acid synthesis, and cofactor biosynthesis pathways, with concurrent upregulation of immune- and inflammation-related proteins. Integrated analysis revealed co-enrichment in cofactor biosynthesis, amino acid metabolism, and purine metabolism pathways, and a regulatory network of key molecules was established. These findings suggest that KD-induced cardiac injury involves significant metabolic reprogramming and immune-inflammatory activation, offering new insights into the pathogenesis and providing a theoretical basis for the development of biomarkers and therapeutic targets.

Systemic vasculitides are associated with quantitative and functional abnormalities in regulatory T cells (Tregs). Current treatments control inflammation but do not reliably re-establish antigen-specific immune tolerance, and relapse and treatment toxicity remain common. This review addresses three questions: (1) which Treg defects are supported across major vasculitis subtypes; (2) what level of evidence supports endogenous Treg expansion, polyclonal Treg transfer, and antigen-specific engineered Tregs; and (3) which target-selection, manufacturing, safety, regulatory, and implementation barriers must be resolved before chimeric antigen receptor-engineered Tregs (CAR-Tregs) can be tested clinically. We distinguish direct human vasculitis evidence from human mechanistic studies, preclinical observations in other autoimmune diseases, and untested therapeutic hypotheses. Human studies support disease-associated Treg abnormalities and provide limited early evidence for low-dose interleukin-2, whereas no published study has yet demonstrated therapeutic efficacy of CAR-Tregs in a vasculitis model or patient. Proposed targets, including activated endothelium and myeloperoxidase- or proteinase 3-related autoreactive responses, therefore remain design hypotheses that require validation. We also compare CAR-Tregs with T cell receptor-engineered Tregs, tolerogenic dendritic cells, Treg-biased interleukin-2 agents, and antigen-specific tolerizing platforms. CAR-Tregs offer a testable framework for localized immune regulation, but they are not an established treatment for vasculitis. Translation should proceed through staged target validation, disease-relevant preclinical models, standardized product-release criteria, and carefully selected early-phase cohorts with long-term safety monitoring.

ABSTRACT Background Early detection of pediatric left ventricular systolic dysfunction (LVSD) remains challenging in resource‐limited settings. This study evaluates a novel synchronized heart sound‐electrocardiogram (HS‐ECG) system for LVSD detection in underserved pediatric populations. Hypothesis Cardiac acoustic biomarkers (CABs) enable age‐specific early detection of pediatric LVSD. Methods This prospective cohort study enrolled 212 children aged 3–16 years, classified into case (LVEF ≤ 55%, n = 80) and control (LVEF > 55%, n = 132) groups with age stratification (3–6 and 7–16 years). All underwent synchronized HS–ECG recording using a high‐fidelity wearable device. Signals were processed via wavelet analysis to derive CABs including electromechanical activation time (EMAT), pre ‐ ejection period (PEP), left ventricular ejection time (LVET), left ventricular systolic time (LVST), their rate‐corrected values (EMATc, PEPc, LVETc, LVSTc), and the PEP/LVET ratio. Echocardiographic LVEF served as the reference standard. Results In children aged 3–6 years, EMATc showed strong inverse correlation with LVEF (r = −0.529, p < 0.001) and AUC = 0.821 (cutoff: 11.80%; sensitivity 82.5%, specificity 84.7%). In those aged 7–16 years, EMAT demonstrated superior performance (r = −0.609, p < 0.001; AUC = 0.896; cutoff: 82.50 ms; sensitivity 82.5%, specificity 93.2%). Conclusion The synchronized HS‐ECG system provides clinically valuable biomarkers for pediatric LVSD diagnosis, demonstrating distinct age‐dependent diagnostic patterns: EMATc shows optimal performance in younger children (3–6 years), while EMAT exhibits superior efficacy in older children (7–16 years).

Background:Kawasaki disease (KD) is a pediatric systemic vasculitis often causing coronary lesions driven by aberrant T-cell activation. While FOS modulates T cells, its specific function in KD remains undefined. This study aims to investigate the role of FOS in T-cell activation and coronary endothelial inflammation in KD. Methods:The study integrated transcriptomic profiling of T cells from patients with KD and a murine model of Candida albicans water-soluble fraction (CAWS)-induced vasculitis to characterize FOS expression and vasculitis. Mechanistically, we employed lentiviral modulation of FOS in activated JURKAT cells co-cultured with human coronary artery endothelial cells (HCAECs) to delineate the impact of FOS on T-cell activation and endothelial inflammation. Results:Compared to controls, FOS expression was significantly upregulated in peripheral blood T cells of acute KD patients (P<0.001). FOS levels were also elevated in peripheral blood T cells and cardiac inflammatory regions of the KD model mice, and inhibition of FOS expression attenuated vasculitis. CD3/28 magnetic bead stimulation increased FOS expression in JURKAT cells, along with elevated levels of inflammatory cytokines interleukin-6 and tumor necrosis factor. Co-culture of activated JURKAT cells with HCAECs resulted in marked endothelial inflammation. Conversely, knocking down FOS in JURKAT cells prior to activation and co-culture mitigated endothelial inflammation. Conclusions:FOS contributes to the development and progression of coronary endothelial inflammation in KD by modulating T-cell activation. Targeting FOS may represent a potential therapeutic strategy for mitigating KD-associated coronary artery injury.

Smad2 is a well-established regulator involved in tissue development and in the pathogenesis of endothelial-to-mesenchymal transition (EndMT) mediated by TGF-β signaling. However, the mechanism underlying the regulation of SMAD2 in human coronary artery endothelial cells (HCAECs), particularly the identity of the responsible E3 ubiquitin ligase and its role during EndMT remain unclear. In this study, we identified Smad ubiquitination regulatory factor 1 (Smurf1) as a negative regulator of Smad2 protein levels in HCAECs and demonstrated that the E3 ligase activity of Smurf1 is essential for this function. Mechanistically, Smurf1 interacts with Smad2, promoting its ubiquitination, and subsequent proteasomal degradation. Specifically, Smurf1 catalyzes K48-linked polyubiquitination of Smad2 at lysine residues K156, K383 and K420. Functionally, Smad2 was found to promote EndMT in HCAECs, an effect that was partially attenuated either by co-expression of Smurf1 or by mutation of Smad2 at lysine 420 (Smad2-K420R), which replaces lysine with arginine. Taken together, our findings identify, for the first time, specific lysine residues on Smad2 targeted by Smurf1 for K48-linked ubiquitination and highlight their crucial regulatory role in modulating EndMT in HCAECs.

Purpose This study aimed to develop and validate an interpretable machine learning (ML) model using routinely collected clinical data to predict medium-to-giant coronary artery aneurysms (MGCAA) early in Kawasaki disease (KD).Methods This retrospective study included 2,777 KD patients from two centers in China. Eleven ML algorithms were developed using clinical and laboratory data from electronic medical records (EMRs). Recursive feature elimination and SHapley Additive exPlanations (SHAP) were used for feature selection and interpretability. The final model was internally and externally validated, with intercept-only recalibration to correct miscalibration, and evaluated by area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA). The model was deployed as an R Shiny-based online prediction tool.Results The support vector machine model implemented with kernlab (SVM kernlab) included seven key features: time to diagnosis, monocyte percentage, rash, eosinophil percentage, C-reactive protein, triglycerides, and neutrophil percentage. It achieved an AUC of 0.732 (95% CI, 0.597-0.866) in internal validation and 0.689 (95% CI, 0.611-0.767) in external validation. SHAP analysis provided both global feature importance and individualized explanations. Recalibration improved model calibration, and DCA demonstrated meaningful net clinical benefit across clinically relevant threshold probabilities.Conclusion This study presents an interpretable ML model to predict MGCAA risk in KD using routine clinical data, supporting clinical risk assessment.

Intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) increases coronary artery risk. Early prediction is crucial for improving outcomes. This study aimed to develop and validate a machine learning (ML) model for predicting IVIG resistance in children with KD. A retrospective cohort of patients with KD was used for model development, with external validation cohorts from Fuzhou and Yangzhou, and a prospective validation cohort. Clinical and laboratory variables were extracted from electronic medical records. We evaluated 12 algorithms and support vector machine (SVM) was selected for optimal performance. SHapley Additive exPlanations (SHAP) values assessed feature importance, followed by stepwise feature elimination. Model performance was evaluated using area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). A web-based calculator was developed. A total of 2371 patients with KD involved in the retrospective development cohort, 443 in Fuzhou cohort, 198 in Yangzhou cohort, and 253 in prospective validation cohort. The SVM model achieved AUCs of 0.782 in internal validation, 0.746 and 0.759 in the external validation cohorts from Fuzhou and Yangzhou, respectively, and 0.799 in prospective validation. The final model incorporated eight predictors, with SHAP analysis providing both global and local explanations of feature contributions. The model also demonstrated good calibration and favorable net benefit across clinically relevant thresholds in DCA. The SVM-based ML model using routine clinical data shows potential for predicting IVIG resistance in KD and may support early risk stratification.

Kawasaki disease (KD) is classified as a “WenBing” syndrome in traditional Chinese medicine (TCM), characterized by systemic inflammation and vasculitis. Jiawei Baihu Tang (JWBHT) is an optimized herbal formulation derived from the classical Baihu Tang (BHT), a renowned ancient TCM prescription traditionally used to treat WenBing syndromes by clearing heat, reducing fever, and promoting body fluid production. However, the precise pharmacological mechanisms underlying JWBHT’s intervention effects remain largely unexplored. We aimed to assess the protective effects of JWBHT on coronary artery inflammation in mice with KD and explore the underlying mechanisms, with a focus on the lipocalin-2/matrix metalloproteinase 9 (LCN2/MMP9) axis in vascular remodeling. Histopathological analysis, multiplex immunofluorescence, data-independent acquisition (DIA) proteomics, and non-targeted metabolomics were employed to comprehensively measure the effects of JWBHT on coronary artery injury. The experiments were conducted using a Candida albicans water-soluble fraction (CAWS)-induced murine model of KD vasculitis. Multi-omics integration also revealed the role of JWBHT in regulating extracellular matrix (ECM)-receptor interaction and enhancing α-linolenic acid metabolism. JWBHT significantly alleviated coronary arteritis by reducing inflammatory cell infiltration, preserving ECM integrity, and alleviating fibrosis. Multi-omics analysis indicated that JWBHT regulated ECM-receptor interaction and restored lipid metabolism, particularly α-linolenic acid metabolism, which was closely linked to ECM stabilization. Mechanistically, JWBHT suppressed the LCN2/MMP9 axis, a critical mediator of vascular remodeling. Validation based on the clinical dataset revealed elevated levels of LCN2/MMP9 in patients with acute KD, which were normalized after treatment. For the first time, this study unveiled the multi-target mode of action of JWBHT in KD through the crosstalk between ECM and lipid metabolism, and LCN2 was identified as a potential novel intervention target. Our findings suggest that JWBHT is a promising traditional Chinese medicine for preventing the cardiovascular complications of KD.

BACKGROUND:The effect of adjunctive glucocorticoids in the primary treatment of Kawasaki disease in unselected patients remains unknown. METHODS:In this multicenter, open-label, randomized, controlled trial in China, we assigned participants with newly diagnosed Kawasaki disease in a 1:1 ratio to receive prednisolone plus standard treatment or standard treatment alone. The primary outcome was the occurrence of coronary-artery lesions at 1 month after illness onset. Prespecified key secondary outcomes, for which analyses were not controlled for multiplicity, included receipt of rescue therapy, duration of fever, change in the C-reactive protein (CRP) level, and changes in coronary-artery z scores. RESULTS:A total of 3208 participants underwent randomization, with coronary-artery lesions detected at baseline in 870 of 3184 participants (27.3%). At 1 month, coronary-artery lesions were detected in 16.0% of the participants receiving prednisolone plus standard treatment and in 13.8% of those receiving standard treatment alone (adjusted risk difference, 1.1 percentage points; 95% confidence interval, -1.0 to 3.4; P = 0.31). Rescue therapy was used in 4.6% of the participants receiving prednisolone plus standard therapy and in 10.1% of those receiving standard treatment alone; the median duration of fever was 8.4 hours and 13.2 hours, respectively, and the reductions in the C-reactive protein level at 72 hours were 67.5 mg per liter and 59.8 mg per liter. Decreases in coronary-artery z scores were similar in the two groups. At 3 months, the incidence of coronary-artery lesions was 12.6% with prednisolone plus standard therapy and 10.5% with standard treatment alone; the percentage of participants with progression of coronary-artery lesions was 28.6% and 28.9%, respectively, and the incidence of medium-to-giant coronary-artery aneurysms was 1.9% and 1.1%. The overall incidence of adverse events did not differ significantly between the two groups. CONCLUSIONS:The addition of prednisolone to standard primary treatment for Kawasaki disease did not reduce the incidence of coronary-artery lesions at 1 month after illness onset. (Funded by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences and the National Natural Science Foundation of China; ClinicalTrials.gov number, NCT04078568.).

BACKGROUNDS:Kawasaki disease (KD) is an immune vasculitis of unknown etiology. Coronary artery lesions (CALs) and intravenous immunoglobulin resistance (IVIGR) are two major clinical challenges in KD. Previous studies had pointed out that neutrophil percentage‑to‑albumin ratio (NPAR) was associated with the prognosis of cardiac diseases. However, its role in KD has not been fully explored. METHODS:We enrolled patients with the main diagnosis of KD admitted to Children's Hospital of Soochow University between December 2018 and June 2024. Patients were stratified into tertiles based on NPAR, and comparisons among groups were conducted. Univariate and multivariable logistic regression were carried out. Restricted cubic splines and fitted curves were used to examine the relationships between NPAR and the presence of CALs and IVIGR. Subgroup analyses were also investigated. RESULTS:A total of 2371 patients were included in the present study. The incidences of IVIGR and CALs were 12.9% (305/2371) and 28.3% (670/2371), respectively. Patients with higher NPAR levels exhibited higher incidences of IVIGR. In contrast, NPAR was not associated with CALs. A positive linear relationship was noted between NPAR and IVIGR (p < 0.001). The expected presence of IVIGR was also positively related to NPAR. However, the association was modified by age and coronary artery status. CONCLUSIONS:NPAR may serve as a prognostic indicator for IVIGR, particularly in patients younger than 48 months and those without CALs, but not for CALs.

Background: Clinical prediction models can lose accuracy over time as case mix and clinical environments change, but evidence on temporal drift and model updating in pediatric prediction models remains limited. We evaluated temporal drift in a multicenter prediction model for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) and assessed whether half-life-weighted updating might help maintain performance over time. Methods: We conducted a multicenter retrospective cohort study including children with KD treated between 2006 and 2024. A baseline model was developed in the pre-COVID cohort (2006–2019) and temporally validated in the during-COVID (2020–2022) and after-COVID (2023–2024) cohorts. Five algorithms were compared, and Elastic Net was selected for further evaluation. Model performance was assessed by discrimination, calibration, Brier score, and decision curve analysis. Updating strategies included recalibration, cumulative refitting, and half-life-weighted updating. Findings: Among 6443 children with KD, 3788 were in the pre-COVID cohort, 1837 in the during-COVID cohort, and 818 in the after-COVID cohort; IVIG resistance occurred in 22.3%, 32.8%, and 12.8% of cases, respectively. Elastic Net showed the best temporal performance. Discrimination declined from an AUC of 0.846 during COVID to 0.703 after COVID. Calibration drift was more pronounced, with progressive underestimation of risk across periods. Recalibration and cumulative refitting only partly stabilized performance. Half-life-weighted updating showed modest improvement, and half-lives of 3–4 years provided a relatively balanced performance. Interpretation: This pediatric prediction model for IVIG resistance in KD showed temporal drift over time, particularly in calibration. Static deployment might be insufficient for long-term use in temporally changing settings.

Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD), also referred to as IVIG-refractory KD or refractory KD, is characterized by a high incidence of cardiovascular complications, particularly coronary artery lesions, and may result in severe outcomes that endanger the lives of affected children. Therefore, early identification, accurate diagnosis, and timely interventions are of paramount importance. In recent years, advances in epidemiological investigations, mechanistic studies, the establishment of high-risk predictive models, and pharmaceutical developments have created new opportunities for the early prediction and management of IVIG-resistant KD. This review summarizes the current research progress on IVIG-resistant KD, offering valuable perspectives for the prevention and clinical management of this condition.

This study aimed to systematically compare the predictive performance and methodological quality of logistic regression (LR) and machine learning (ML) models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) using the PROBAST + AI framework. We searched PubMed, Embase, and Web of Science to identify studies on prediction models for IVIG resistance in KD published between January 1, 2006, and July 31, 2025. We assessed methodological rigour, risk of bias, and applicability using PROBAST + AI. A meta-analysis was performed using random-effects models with logit-transformed area under the receiver operating characteristic curve (AUC) values. Subgroup, sensitivity, and publication bias analyses were additionally conducted. We identified 52 eligible studies (40 LR and 12 ML). In external validation, pooled AUCs were similar between ML and LR models (0.76 [95

BACKGROUND:Differentiating Kawasaki disease (KD) from other febrile illnesses remains challenging because of overlapping clinical and laboratory features. This study systematically evaluated the methodological quality, risk of bias, applicability, and predictive performance of machine learning (ML) and logistic regression-family (LR-family) models. METHODS:PubMed, Web of Science, and Embase were searched from January 1, 2006, to December 31, 2025, for studies developing or validating ML or LR-family models for differentiating KD from other febrile illnesses. Risk of bias and applicability were assessed using PROBAST + AI. The required minimum sample size for each study was formally estimated, and exploratory meta-analyses, subgroup analyses, and leave-one-out sensitivity analyses were performed. RESULTS:Twenty-eight studies (10 ML and 18 LR-family) were included. Common methodological limitations included inadequate sample size, retrospective design, inadequate handling of missing data, limited external validation, and poor calibration reporting; no ML study reported calibration metrics. Given the high risk of bias across all studies, pooled areas under the receiver operating characteristic curve (AUCs) were interpreted as exploratory quantitative summaries, showing no significant difference in internal validation performance between ML and LR-family models (0.95 [95% CI 0.91-0.97] vs. 0.92 [95% CI 0.89-0.94]; P = 0.222). CONCLUSIONS:Current evidence is limited by high risk of bias, substantial heterogeneity, and important methodological limitations, and limited independent external validation evidence precluded a reliable comparison of the external validation performance of ML and LR-family models. Accordingly, current prediction models are not yet ready for routine clinical decision-support deployment.

BACKGROUND:Radiofrequency catheter ablation (RFCA) is an established therapy for pediatric supraventricular tachycardia (SVT). However, data on long-term outcomes and predictors of success from sizable contemporary cohorts are limited. This study aimed to evaluate the long-term clinical success rate of RFCA in a pediatric cohort and to identify independent predictors of arrhythmia-free survival. METHODS:We conducted a retrospective analysis of 219 consecutive pediatric patients (age ≤18 years) who underwent their first RFCA for SVT (including atrioventricular reentrant tachycardia, atrioventricular nodal reentrant tachycardia, and atrial tachycardia) at a single tertiary center over a 6-year period. The primary outcome was long-term clinical success, defined as acute procedural success without clinical recurrence during follow-up. Univariable and multivariable logistic regression analyses were performed to identify factors associated with long-term success. RESULTS:The overall acute procedural success rate was 96.3% (211/219, excluding 3 with non-inducible SVT and 5 acute failures from the denominator). The long-term clinical success rate was 91.3% (based on 200/219 patients). Multivariable analysis identified older age as a significant independent predictor of long-term success (p=0.016). Furthermore, atrial tachycardia was associated with a lower odd of success compared to atrioventricular nodal reentrant tachycardia, although the difference was not statistical significance. CONCLUSION:RFCA is highly effective for treating pediatric SVT, with excellent long-term durability. Older age at procedure is a strong independent predictor of success, while patients with AT may have a higher risk of recurrence. These findings are valuable for pre-procedural counseling and patient selection.

BACKGROUND:Human breast milk-derived exosomes have been shown to prevent necrotizing enterocolitis (NEC). However, the mechanism remains unclear. This study aims to examine the role of miR-144-5p in repairing the damage of the tight junction barrier caused by NEC and its underlying mechanism. METHODS:Differentially expressed exosome-derived miRNAs from term and preterm breast milk were identified through miRNA sequencing. Subsequently, the biological role and mechanism of the miRNA were studied both in vitro and in vivo. RESULTS:We found that exosomal miR-144-5p enhances the viability of intestinal epithelial cells in vitro and increases claudin-1 protein levels in vivo; Overexpressed miR-144-5p decreases interleukin-1beta (IL-1β) protein levels both in vitro and in vivo. Mechanistically, miR-144-5p alleviates intestinal inflammation and improves epithelial barrier function by downregulating toll-like receptor 4 (TLR4) expression and inhibiting the NF-κB signaling pathway. CONCLUSIONS:Exosomal miR-144-5p protects against experimental NEC by inhibiting the TLR4/NF-κB signaling pathway. This study reveals a previously unknown regulatory mechanism in the progression of NEC. IMPACT:Overexpression of miR-144-5p significantly decreases TLR4 expression, thereby inhibiting the TLR4 signaling pathway. MiR-144-5p reduces the production of inflammatory cytokines and prevents disruption of the tight junction protein claudin-1. This study is the first to confirm that human milk exosome miRNAs protect tight junctions from LPS-induced damage by modulating the TLR4/NF-κB signaling pathway. It offers a new perspective on understanding the pathogenesis of NEC. It expands the therapeutic options for necrotizing enterocolitis.

BackgroundKawasaki disease (KD) is an acute systemic vasculitis affecting children under five years of age and a leading cause of acquired heart disease in developed countries. Although autopsy and biopsy studies provide important insights into disease progression, integrated summaries combining classical histopathology with modern molecular findings remain limited.MethodsThis narrative review searched PubMed and Web of Science from January 1, 1974 to December 31, 2025 for human autopsy and biopsy studies on KD. Findings were synthesized to characterize pathological features across cardiovascular and extracardiac systems, focusing on vascular progression based on the three-process model, multisystem involvement, and underlying molecular and genetic mechanisms.ResultsCoronary artery involvement follows a three-process model, including necrotizing arteritis, subacute/chronic vasculitis, and luminal myofibroblastic proliferation, which drives progressive luminal stenosis. The myocardium, pericardium, and cardiac valves are also frequently affected. Extracardiac tissues show intracytoplasmic inclusion bodies and IgA plasma cell infiltration, suggesting a potential infection-triggered mechanism. Key signaling pathways, including TLRs/NF-κB, NLRP3/IL-1β, Ca²+/NFAT, and TGF-β, along with genetic polymorphisms, contribute to immune dysregulation and vascular injury and may provide potential therapeutic targets.ConclusionKD is a systemic vasculitis primarily targeting the coronary arteries, with a dynamic pathological progression from acute inflammation to chronic vascular remodeling. Future research should focus on prospective pathology studies, long-term vascular remodeling, and underlying molecular mechanisms.

Background and Objective:Kawasaki disease (KD) is a systemic pediatric vasculitis characterized by dysregulated immune activation and substantial risk of coronary artery lesions. Emerging evidence suggests metabolic reprogramming is a critical link between immune responses and endothelial dysfunction during KD progression. This review aims to provide an integrated overview of metabolic alterations in KD pathogenesis, focusing on clinical observations, mechanistic insights, and experimental evidence. Methods:A literature search was conducted using PubMed and Web of Science to identify studies published up to July 2026, combining "Kawasaki disease" with terms related to metabolism and metabolic pathways, including metabolites, glucose, glycolysis, amino acids, lipids, fatty acid oxidation, succinic acid, the tricarboxylic acid (TCA) cycle, nitric oxide, urine, gut microbiota, mouse models, and therapeutic strategies. Relevant clinical, experimental, and mechanistic studies were reviewed and synthesized. Key Content and Findings:Accumulating evidence indicates extensive metabolic remodeling in KD, including enhanced glycolysis, disrupted lipid metabolism and fatty acid oxidation, altered amino acid metabolism, and TCA cycle perturbations. These abnormalities are closely linked to immune activation, mitochondrial dysfunction, oxidative stress, and vascular inflammation. KD mouse models further support metabolic reprogramming, marked by altered tryptophan and amino acid metabolism, lipid metabolism, and lactate production. Notably, kynurenine pathway activation with reduced tryptophan availability is associated with inflammatory amplification and mitochondrial impairment. Beyond host-derived changes, gut microbiota dysbiosis and its metabolites appear to correlate with immune responses and disease severity. However, clinical translation of these metabolic signatures into reliable biomarkers or therapeutic targets remains limited. Conclusions:This review highlights metabolic reprogramming as a key interface linking immune dysregulation, endothelial injury, and vascular complications in KD. Metabolic abnormalities may act not merely as consequences of inflammation but as active regulators of vascular dysfunction and disease progression. Significant gaps remain in establishing causal relationships between specific metabolic alterations and KD pathogenesis. Future studies integrating multicenter cohorts with cellular, multi-omics, and animal model approaches, particularly centered on the metabolic-immune-vascular injury axis, will be essential for identifying novel biomarkers and therapeutic strategies.

Kawasaki disease (KD) is a pediatric systemic vasculitis of unknown etiology. Although infections are thought to trigger the disease, the antigen-specific adaptive immune responses remain poorly characterized. This study aimed to comprehensively profile the adaptive immune response in KD patients using omics data to improve diagnosis and to assess how faithfully the Candida albicans water-soluble fraction (CAWS) mouse model recapitulates human KD immunopathology. We performed high-throughput sequencing of B-cell and T-cell receptor repertoires (BCR/TCR) in clinical cohorts comprising KD patients, febrile controls, and healthy children. A CAWS-induced vasculitis mouse model was established for comparative pathological and immunological analysis. We assessed immune repertoire diversity, clonal expansion, V(D)J gene usage, and clonal distribution. A previously developed physics and mathematics based model, was applied to classify immune states. KD patients showed oligoclonal expansion in the Ig-A and TCR-β repertoires, accompanied by significantly reduced diversity, consistent with antigen-driven clonal selection. The model effectively discriminated KD patients from control groups and identified misclassified febrile cases. Although the CAWS model recapitulated human-like coronary vasculitis and immune infiltration, it did not mirror the oligoclonal immune response seen in patients. Instead, the model exhibited polyclonal B-cell activation, increased Ig-G diversity, and predominant Ig-M expansion. Our findings reveal antigen-specific adaptive immune mechanisms in KD and provide an immune repertoire-based framework for diagnostic discrimination using minimal sample input. The marked divergence between human and mouse immune responses highlights the limitations of current animal models and underscores the need for more human-relevant systems to study KD pathogenesis and therapeutic strategies.