Identification of novel mitophagy-related biomarkers for Kawasaki disease by integrated bioinformatics and machine-learning algorithms.

Background: Kawasaki disease (KD) is a systemic vasculitis primarily affecting the coronary arteries in children. Despite growing attention to its symptoms and pathogenesis, the exact mechanisms of KD remain unclear. Mitophagy plays a critical role in inflammation regulation, however, its significance in KD has only been minimally explored. This study sought to identify crucial mitophagy-related biomarkers and their mechanisms in KD, focusing on their association with immune cells in peripheral blood. Methods: This research used four datasets from the Gene Expression Omnibus (GEO) database that were categorized as the merged and validation datasets. Screening for differentially expressed mitophagy-related genes (DE-MRGs) was conducted, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A weighted gene co-expression network analysis (WGCNA) identified the hub module, while machine-learning algorithms [random forest-recursive feature elimination (RF-RFE) and support vector machine-recursive feature elimination (SVM-RFE)] pinpointed the hub genes. Receiver operating characteristic (ROC) curves were generated for these genes. Additionally, the CIBERSORT algorithm was used to assess the infiltration of 22 immune cell types to explore their correlations with hub genes. Interactions between transcription factors (TFs), genes, and Gene-microRNAs (miRNAs) of hub genes were mapped using the NetworkAnalyst platform. The expression difference of the hub genes was validated using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Results: Initially, 306 DE-MRGs were identified between the KD patients and healthy controls. The enrichment analysis linked these MRGs to autophagy, mitochondrial function, and inflammation. The WGCNA revealed a hub module of 47 KD-associated DE-MRGs. The machine-learning algorithms identified cytoskeleton-associated protein 4 (CKAP4) and serine-arginine protein kinase 1 (SRPK1) as critical hub genes. In the merged dataset, the area under the curve (AUC) values for CKAP4 and SRPK1 were 0.933 [95% confidence interval (CI): 0.901 to 0.964] and 0.936 (95% CI: 0.906 to 0.966), respectively, indicating high diagnostic potential. The validation dataset results corroborated these findings with AUC values of 0.872 (95% CI: 0.741 to 1.000) for CKAP4 and 0.878 (95% CI: 0.750 to 1.000) for SRPK1. The CIBERSORT analysis connected CKAP4 and SRPK1 with specific immune cells, including activated cluster of differentiation 4 (CD4) memory T cells. TFs such as MAZ, SAP30, PHF8, KDM5B, miRNAs like hsa-mir-7-5p play essential roles in regulating these hub genes. The qRT-PCR results confirmed the differential expression of these genes between the KD patients and healthy controls. Conclusions: CKAP4 and SRPK1 emerged as promising diagnostic biomarkers for KD. These genes potentially influence the progression of KD through mitophagy regulation.

Plasma proteomic profiling reveals that SERPINE1 is a potential biomarker associated with coronary artery lesions in Kawasaki disease.

BACKGROUND: Kawasaki disease (KD) is the most common cause of acquired heart disease in childhood. Coronary artery lesions (CALs) are serious complications of KD that can result in stenosis and thrombosis, but the specific underlying pathogenic mechanisms have not been elucidated. Therefore, exploring biomarkers to help predict early CALs is urgently needed for clinical treatment. METHODS: Patients were recruited from three independent cohorts. In the discovery cohort, Data-Independent Acquisition Mass Spectrometry (DIA-MS) was performed to screen plasma proteins from healthy controls (HCs), KD patients prior to intravenous immunoglobulin (IVIG) treatment, and KD patients post-IVIG treatment. KD patients were further divided into KD patients without CALs (nCAL) and with CALs (CALs) groups. Bioinformatic analysis was carried out for the differentially expressed proteins (DEPs) and hub proteins. Candidate proteins were quantified by enzyme-linked immunosorbent assay (ELISA) in the validation cohort 1 and 2. Furthermore, candida albicans cell wall extract (CAWS)-induced KD vasculitis mice and cell models were established to investigate the expression of biomarkers identified in the aforementioned clinical cohort. RESULTS: According to the quantitative proteomics analysis, SERPINE1 was significantly increased in KD patients with CALs. Receiver operating characteristic curves (ROC) revealed that plasma SERPINE1 exhibited greater ability in predicting CALs (AUC = 0.824, P < 0.0001). After IVIG treatment, the concentrations of SERPINE1 in the nCALs group significantly decreased. However, the concentration of SERPINE1 remained persistently elevated in the CALs group. Moreover, the expression of SERPINE1 was significantly upregulated in the heart tissue of KD mice, KD plasma, or tumor necrosis factor-α (TNF-α)-stimulated human coronary artery endothelial cells (HCAECs). CONCLUSIONS: Overall, our results suggest that the plasma concentration of SERPINE1 might serve as a new potential predictive biomarker for CALs in KD patients.

Knowledge framework of intravenous immunoglobulin resistance in the field of Kawasaki disease: A bibliometric analysis (1997-2023).

BACKGROUND: Kawasaki disease (KD) is an autoimmune disease with cardiovascular disease as its main complication, mainly affecting children under 5 years old. KD treatment has made tremendous progress in recent years, but intravenous immunoglobulin (IVIG) resistance remains a major dilemma. Bibliometric analysis had not been used previously to summarize and analyze publications related to IVIG resistance in KD. This study aimed to provide an overview of the knowledge framework and research hotspots in this field through bibliometrics, and provide references for future basic and clinical research. METHODS: Through bibliometric analysis of relevant literature published on the Web of Science Core Collection (WoSCC) database between 1997 and 2023, we investigated the cooccurrence and collaboration relationships among countries, institutions, journals, and authors and summarized key research topics and hotspots. RESULTS: Following screening, a total of 364 publications were downloaded, comprising 328 articles and 36 reviews. The number of articles on IVIG resistance increased year on year and the top three most productive countries were China, Japan, and the United States. Frontiers in Pediatrics had the most published articles, and the Journal of Pediatrics had the most citations. IVIG resistance had been studied by 1889 authors, of whom Kuo Ho Chang had published the most papers. CONCLUSION: Research in the field was focused on risk factors, therapy (atorvastatin, tumor necrosis factor-alpha inhibitors), pathogenesis (gene expression), and similar diseases (multisystem inflammatory syndrome in children, MIS-C). "Treatment," "risk factor," and "prediction" were important keywords, providing a valuable reference for scholars studying this field. We suggest that, in the future, more active international collaborations are carried out to study the pathogenesis of IVIG insensitivity, using high-throughput sequencing technology. We also recommend that machine learning techniques are applied to explore the predictive variables of IVIG resistance.

Spexin ameliorated obesity-related metabolic disorders through promoting white adipose browning mediated by JAK2-STAT3 pathway.

BACKGROUND: Spexin, a 14 amino acid peptide, has been reported to regulate obesity and its associated complications. However, little is known about the underlying molecular mechanism. Therefore, this study aimed to investigate the effects of spexin on obesity and explore the detailed molecular mechanisms in vivo and in vitro. METHODS: Male C57BL/6J mice were fed a high-fat diet (HFD) for 12 weeks to induce obesity, and mice fed a standard fat diet were used as controls. Then, these mice were treated with SPX or Vehicle by intraperitoneal injection for an additional 12 weeks, respectively. The metabolic profile, fat-browning specific markers and mitochondrial contents were detected. In vitro, 3T3-L1 cells were used to investigate the molecular mechanisms. RESULTS: After 12 weeks of treatment, SPX significantly decreased body weight, serum lipid levels, and improved insulin sensitivity in HFD-induced obese mice. Moreover, SPX was found to promote oxygen consumption in HFD mice, and it increased mitochondrial content as well as the expression of brown-specific markers in white adipose tissue (WAT) of HFD mice. These results were consistent with the increase in mitochondrial content and the expression of brown-specific markers in 3T3-L1 mature adipocytes. Of note, the spexin-mediated beneficial pro-browning actions were abolished by the JAK2/STAT3 pathway antagonists in mature 3T3-L1 cells. CONCLUSIONS: These data indicate that spexin ameliorates obesity-induced metabolic disorders by improving WAT browning via activation of the JAK2/STAT3 signaling pathway. Therefore, SPX may serve as a new therapeutic candidate for treating obesity.

A bibliometric analysis of Kawasaki disease from 1974 to 2022.

Objective: To analyse the research history, development trends and current status of relevant literature in the field of Kawasaki disease, and to provide the basis for future directions in Kawasaki disease (KD) research. Methods: Literature on Kawasaki disease published between January 1974 and December 2022 was searched for in the Web of Science database, and CiteSpace was used to perform visual analyses. Results: The search yielded a total of 6950 articles. The number of publications related to Kawasaki disease showed an increasing trend. A collaborative network analysis revealed that the United States, Japan and mainland China were the most influential countries in this field. The University of California system contributed the most publications and the journal with the most publications was Circulation. JW Newburger was an authoritative author in this field. "Coronary artery lesion", "Intravenous immunoglobulin" (IVIG) and "Risk factor" were three prominent keywords. Keyword bursts changed from "TNF" and "IVIG", which focused on aetiology and treatment, to "Long term management", which emphasized the recovery period, and to "Kawasaki-like disease" and "Multisystem inflammatory syndrome" during the novel coronavirus pandemic. Trends of highly cited references indicated that landmark articles in different periods focused on Kawasaki disease guidelines, gene polymorphisms and multisystem inflammatory syndrome caused by the novel coronavirus. Conclusion: The aetiology of Kawasaki disease remains unclear, but viral infection is likely to play an important role. The combination of evolving sequencing technologies, large-scale epidemiological investigations and prospective cohort studies is likely to be important in exploring Kawasaki disease and improving its prognosis in future.

Identification of hub biomarkers and immune-related pathways participating in the progression of Kawasaki disease by integrated bioinformatics analysis.

BACKGROUND: Kawasaki disease (KD) is a systemic vasculitis that commonly affects children and its etiology remains unknown. Growing evidence suggests that immune-mediated inflammation and immune cells in the peripheral blood play crucial roles in the pathophysiology of KD. The objective of this research was to find important biomarkers and immune-related mechanisms implicated in KD, along with their correlation with immune cells in the peripheral blood. MATERIAL/METHODS: Gene microarray data from the Gene Expression Omnibus (GEO) was utilized in this study. Three datasets, namely GSE63881 (341 samples), GSE73463 (233 samples), and GSE73461 (279 samples), were obtained. To find intersecting genes, we employed differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, functional annotation, construction of protein-protein interaction (PPI) networks, and Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to identify hub genes. The accuracy of these hub genes in identifying KD was evaluated using the receiver operating characteristic curve (ROC). Furthermore, Gene Set Variation Analysis (GSVA) was employed to explore the composition of circulating immune cells within the assessed datasets and their relationship with the hub gene markers. RESULTS: WGCNA yielded eight co-expression modules, with one hub module (MEblue module) exhibiting the strongest association with acute KD. 425 distinct genes were identified. Integrating WGCNA and DEGs yielded a total of 277 intersecting genes. By conducting LASSO analysis, five hub genes (S100A12, MMP9, TLR2, NLRC4 and ARG1) were identified as potential biomarkers for KD. The diagnostic value of these five hub genes was demonstrated through ROC curve analysis, indicating their high accuracy in diagnosing KD. Analysis of the circulating immune cell composition within the assessed datasets revealed a significant association between KD and various immune cell types, including activated dendritic cells, neutrophils, immature dendritic cells, macrophages, and activated CD8 T cells. Importantly, all five hub genes exhibited strong correlations with immune cells. CONCLUSION: Activated dendritic cells, neutrophils, and macrophages were closely associated with the pathogenesis of KD. Furthermore, the hub genes (S100A12, MMP9, TLR2, NLRC4, and ARG1) are likely to participate in the pathogenic mechanisms of KD through immune-related signaling pathways.

A novel model for predicting intravenous immunoglobulin-resistance in Kawasaki disease: a large cohort study.

Background: Predicting intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD) can aid early treatment and prevent coronary artery lesions. A clinically consistent predictive model was developed for IVIG resistance in KD. Methods: In this retrospective cohort study of children diagnosed with KD from January 1, 2016 to December 31, 2021, a scoring system was constructed. A prospective model validation was performed using the dataset of children with KD diagnosed from January 1 to June 2022. The least absolute shrinkage and selection operator (LASSO) regression analysis optimally selected baseline variables. Multivariate logistic regression incorporated predictors from the LASSO regression analysis to construct the model. Using selected variables, a nomogram was developed. The calibration plot, area under the receiver operating characteristic curve (AUC), and clinical impact curve (CIC) were used to evaluate model performance. Results: Of 1975, 1,259 children (1,177 IVIG-sensitive and 82 IVIG-resistant KD) were included in the training set. Lymphocyte percentage; C-reactive protein/albumin ratio (CAR); and aspartate aminotransferase, sodium, and total bilirubin levels, were risk factors for IVIG resistance. The training set AUC was 0.825 (sensitivity, 0.723; specificity, 0.744). CIC indicated good clinical application of the nomogram. Conclusion: The nomogram can well predict IVIG resistance in KD. CAR was an important marker in predicting IVIG resistance in Kawasaki disease.

The role of FOXO4/NFAT2 signaling pathway in dysfunction of human coronary endothelial cells and inflammatory infiltration of vasculitis in Kawasaki disease.

Aims: The Ca+/NFAT (Nuclear factor of activated T cells) signaling pathway activation is implicated in the pathogenesis of Kawasaki disease (KD); however, we lack detailed information regarding the regulatory network involved in the human coronary endothelial cell dysfunction and cardiovascular lesion development. Herein, we aimed to use mouse and endothelial cell models of KD vasculitis in vivo and in vitro to characterize the regulatory network of NFAT pathway in KD. Methods and Results: Among the NFAT gene family, NFAT2 showed the strongest transcriptional activity in peripheral blood mononuclear cells (PBMCs) from patients with KD. Then, NFAT2 overexpression and knockdown experiments in Human coronary artery endothelial cells (HCAECs) indicated that NFAT2 overexpression disrupted endothelial cell homeostasis by regulation of adherens junctions, whereas its knockdown protected HCAECs from such dysfunction. Combined analysis using RNA-sequencing and transcription factor (TF) binding site analysis in the NFAT2 promoter region predicted regulation by Forkhead box O4 (FOXO4). Western blotting, chromatin immunoprecipitation, and luciferase assays validated that FOXO4 binds to the promoter and transcriptionally represses NFAT2. Moreover, Foxo4 knockout increased the extent of inflamed vascular tissues in a mouse model of KD vasculitis. Functional experiments showed that inhibition NFAT2 relieved Foxo4 knockout exaggerated vasculitis in vivo. Conclusions: Our findings revealed the FOXO4/NFAT2 axis as a vital pathway in the progression of KD that is associated with endothelial cell homeostasis and cardiovascular inflammation development.