Vascular endothelial growth factor (VEGF) is an important factor in mediating the inflammation of Kawasaki disease (KD). The literature regarding the relationship between VEGF and KD is sparse. The purpose of this study was to investigate the correlation of VEGF and KD. In a prospective study of 42 Taiwanese KD patients (18.9 ± 12.2 months, M/F 22/20) treated with intravenous immunoglobulin (IVIG), a series of VEGF levels was measured from the acute to convalescent phases. KD patients were classified into two subgroups with (n =20) and without (n = 22) acute coronary artery lesions (CALs). Control samples were obtained from 30 febrile controls (19.1 ± 13.7 months, M/F 13/17). In KD patients, VEGF levels in the pre-IVIG acute phase were significantly higher than those in the subacute and convalescent phases (both p < 0.001). In KD patients with CALs, VEGF levels significantly increased immediately in the post-IVIG phase (p = 0.039), and then significantly decreased in the subacute phase (p = 0.002). KD patients with acute CALs had higher median VEGF levels than those without acute CALs from acute to convalescent phases. In the subacute phase, KD patients with acute CALs had significantly higher VEGF levels (p = 0.022) than those without acute CALs. Our data show that VEGF did not decrease after IVIG treatment, and increased significantly after IVIG treatment in KD patients with acute CALs in acute phase. VEGF might be related to the complications of CALs in KD patients.

Coronary artery lesions (CAL) are a major complication of Kawasaki disease (KD). The early prediction of CAL enables the medical personnel to apply adequate medical intervention. We collected the serum samples from the KD patients with CAL (n = 32) and those without CAL (n = 31), followed by a global screening with isobaric tagging for relative and absolute quantification (iTRAQ) technology and specific validation with an enzyme-linked immunosorbent assay (ELISA). iTRAQ identified 846 proteins in total in the serum samples, and four candidate proteins related to CAL were selected for ELISA validation as follows: Protein S100-A4 (S100A4), Catalase (CAT), Folate receptor gamma (FOLR3), and Galectin 10 (CLC). ELISA validation showed that the S100A4 level was significantly higher in KD patients with CAL than in those without CAL (225.2 ± 209.5 vs. 143.3 ± 83 pg/mL, p < 0.05). In addition, KD patients with CAL had a significantly lower CAT level than those without CAL (1.6 ± 1.5 vs. 2.7 ± 2.3 ng/mL, p < 0.05). Next, we found that S100A4 treatment on human coronary artery endothelial cells (HCAECs) reduced the abundance of cell junction proteins, which promoted the migration of HCAECs. Further assays also demonstrated that S100A4 treatment enhanced the permeability of the endothelial layer. These results concluded that S100A4 treatment resulted in an incompact endothelial layer and made HCAECs more susceptible to in vitro neutrophil infiltration. In addition, both upregulated S100A4 and downregulated CAT increased the risk of CAL in KD. Further in vitro study implied that S100A4 could be a potential therapeutic target for CAL in KD.

A quick prediction method may help confirm the diagnosis of Kawasaki disease (KD), and reduce the risk of coronary artery lesions. The purpose of this study was to evaluate potential candidate diagnostic serum proteins in KD using isobaric tagging for relative and absolute quantification (iTRAQ) gel-free proteomics. Ninety two subjects, including 68 KD patients (1.6 ± 1.2 years, M/F 36/32) and 24 fever controls with evident respiratory tract infection (2.1 ± 1.2 years, M/F 13/11) were enrolled. Medical records were reviewed for demographic and laboratory data. The iTRAQ gel-free proteomics was used to screen serum proteins completely and compare the difference between two groups followed by specific validation with ELISA. The candidate proteins and conventional laboratory items were selected for the prediction model of KD diagnosis by support vector machine. Five selected candidate proteins, including protein S100-A8, protein S100-A9, protein S100-A12, neutrophil defensin 1, and alpha-1-acid glycoprotein 1 were identified for developing the prediction model of KD diagnosis. They were used to develop an efficient KD prediction model with an area under receiver operating characteristic (auROC) value of 0.92 (95% confidence interval: 0.84, 0.98). These protein biomarkers were significantly correlated with the conventional laboratory items as follows: C-reactive protein, glutamic pyruvic transaminase, white blood count, platelet, segment and hemoglobin. These conventional laboratory items were used to develop a prediction model of KD diagnosis with an auROC value of 0.88 (95% confidence interval: 0.80, 0.96). Our result demonstrated that the prediction model with combined five selected candidate protein levels may be a good diagnostic tool of KD. Further prediction model with combined six conventional laboratory data is also an acceptable alternative method for KD diagnosis.