New biomarkers of Kawasaki disease identified by urine proteomic analysis

Abstract

Kawasaki disease (KD) is an acute systemic vasculitis that mainly afflicts infants and young children. The symptoms of KD are similar to those of various febrile diseases. Here, we attempted to develop accurate diagnostic biomarkers of KD by performing urine proteomic analysis of samples from healthy controls, patients with KD, and patients with another febrile disease, pneumonia (two patients). We identified differentially expressed proteins (DEPs) in KD as compared to normal controls. We also constructed functional annotation and protein-protein interaction (PPI) networks of DEPs in KD and pneumonia. DEPs common to both KD and pneumonia were identified, as well as DEPs specific to KD. Compared to normal control, 43 and 62 DEPs were identified in KD and pneumonia, respectively. Serine hydroxymethyltransferase 1 is a hub protein of the KD-specific PPI network. Thirteen DEPs common to both KD and pneumonia and 30 DEPs specific to KD were identified. Of these, the expression of eight DEPs could cluster normal and pneumonia samples into one group and cluster KD samples into another group based on hierarchical clustering. Our study identified several DEPs that may play a role in KD and that may serve as diagnostic biomarkers to distinguish patients with KD from both normal control and other febrile diseases.

Keywords: Kawasaki disease; biomarker; pneumonia; protein; urine proteomics.

Figure 1

Hierarchical clustering analysis of the expression levels of DEPs in KD and pneumonia compared to normal control. Rows and columns represent the accession of each DEP and sample, respectively. The color scale indicates the expression level of each DEP. Red and green indicated up‐ and down‐regulation, respectively. (A) DEPs in pneumonia compared to normal control. (B) DEPs in KD compared to normal control.

Figure 2

The top 15 most significantly enriched GO terms in DEPs of KD. The x‐axis represents the −log (P‐value) and the y‐axis represents the GO terms. (A) Biological process (BP); (B) molecular function (MF); (C) cellular component (CC).

Figure 3

The KD‐ and pneumonia‐specific PPI network. (A) Pneumonia‐specific PPI network. (B) KD ‐specific PPI network.

Figure 4

Hierarchical clustering analysis in KD, pneumonia and normal control. Rows and columns represented the accession of each DEP and sample, respectively. The color scale indicates the expression level of each DEP. Red and green indicate up‐ and down‐regulation, respectively. (A) Common DEPs in both KD and pneumonia compared to normal control; (B) KD‐specific DEPs that did not belong to DEPs in pneumonia; (C) eight candidate KD‐specific DEPs that did not belong to DEPs in pneumonia.