Background: Kawasaki disease (KD) is the most common cause of acquired heart disease. A proportion of patients were resistant to intravenous immunoglobulin (IVIG), the primary treatment of KD, and the mechanism of IVIG resistance remains unclear. The accuracy of current models predictive of IVIG resistance is insufficient and doesn't meet the clinical expectations.Objectives: To develop a scoring model predicting IVIG resistance of patients with KD.Methods: We recruited 330 KD patients (50 IVIG non-responders, 280 IVIG responders) and 105 healthy children to explore the susceptibility loci of IVIG resistance in Kawasaki disease. A next generation sequencing technology that focused on 4 immune-related pathways and 472 single nucleotide polymorphisms (SNPs) was performed. An R package SNPassoc was used to identify the risk loci, and student's t-test was used to identify risk factors associated with IVIG resistance. A random forest-based scoring model of IVIG resistance was built based on the identified specific SNP loci with the laboratory data.Results: A total of 544 significant risk loci were found associated with IVIG resistance, including 27 previous published SNPs. Laboratory test variables, including erythrocyte sedimentation rate (ESR), platelet (PLT), and C reactive protein, were found significantly different between IVIG responders and non-responders. A scoring model was built using the top 9 SNPs and clinical features achieving an area under the ROC curve of 0.974.Conclusions: It is the first study that focused on immune system in KD using high-throughput sequencing technology. Our findings provided a prediction of the IVIG resistance by integrating the genotype and clinical variables. It also suggested a new perspective on the pathogenesis of IVIG resistance.
Purpose Kawasaki disease (KD) is an acute systemic vasculitis mainly found in the medium-sized arteries, especially the coronary arteries. Immune system is involved in the pathogenesis of acute KD in children, but the functional differences in the immune system between healthy children and KD patients remain unclear. Patients and Methods A total of 190 KD patients and 119 healthy controls were recruited for the next-generation sequencing of 512 targeted genes from 4 immune-related pathways. Subsequently, the peripheral blood mononuclear cells (PBMCs) were isolated. RNA sequencing of the LPS treated PBMCs from additional 20 KD patients and 20 healthy controls was used to examine the differentially expressed genes (DEGs). Then, an expression quantitative trait locus (eQTL) analysis combined with previously analyzed RNA data were used to examine the DEGs. Finally, the serum levels of 13 cytokines were detected before and after LPS treatment in 40 samples to confirm the findings from eQTL analysis. Results A total of 319 significant eQTL were found, and both eQTL analysis and RNA sequencing showed some DEGs were involved in the connective tissue disorders and inflammatory diseases. DEGs that function to negatively regulate immunity were closely related to the pathogenesis of KD. In addition, the serum levels of IL-10 (an inflammatory and immunosuppressive factor) and SCD25 (an important immunosuppressant) reduced significantly in the KD patients. Conclusion Our study shows the expression of factors responsible for the negative control of innate immunity is altered, which plays an important role in the etiology of KD.
Background: Phototherapy is a recommended method for the treatment of neonatal hyperbilirubinemia.However, biomarkers for predicting the more effective duration of phototherapy prior to treatment are lacking. Therefore, we aimed to determine novel predictors for the timing of phototherapy from the perspective of metabolomics.Methods: A total of 12 newborns with neonatal hyperbilirubinemia were recruited on the day of admission.The infants were divided into a short-duration (<30 hours) phototherapy group and a long-duration (≥30 hours) phototherapy group based on the length of phototherapy treatment. Metabolites in serum samples were then explored using an untargeted metabolomics strategy.Results: In total, 59 of 1,073 significantly different metabolites were identified between the shortduration and long-duration phototherapy groups, including 18 upregulated and 41 downregulated metabolites. The results of metabolomic analysis showed that the differentially expressed metabolites were enriched in glycerophospholipid metabolism, which is closely associated with the excretion of bilirubin.Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the metabolites were also enriched in alpha-Linolenic acid metabolism and fatty acid elongation. Spearman correlation hierarchical clustering analysis demonstrated that 9 metabolites were negatively correlated with the duration of phototherapy. Metabolites, especially phosphatidylethanolamine (PE) (22:1(13Z)/15:0), phosphatidylcholine (PC) (18:1(9Z)/18:1(9Z)), phosphatidylserine (PS) (22:0/15:0), 5,6-dihydrouridine, and PE (MonoMe(11,3)/MonoMe(13,5)), had better predictability for the duration of phototherapy [area under curve (AUC): 1; 95% confidence interval (CI): 1-1] than total serum total bilirubin and direct bilirubin (AUC: 0.806; 95% CI: 0.55-1), as revealed by receiver operating characteristic analysis.Conclusions: Our research found that the differential metabolites were associated with the duration of neonatal jaundice and that glycerophospholipid metabolism might have played a role in this biological process. Moreover, metabolites such as PE (22:1(13Z)/15:0), PC (18:1(9Z)/18:1(9Z)), PS (22:0/15:0), 5,6-dihydrouridine, and PE (MonoMe(11,3)/MonoMe(13,5)) could be used as predictors for phototherapy duration in neonatal hyperbilirubinemia and assist with decision-making.
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