Up-regulated vitronectin in Kawasaki disease shock syndrome serves as a potential biomarker

Introduction

Kawasaki disease (KD) is an acute systemic vasculitis primarily affecting children under 5 years old. The most common complication of KD is coronary artery lesions (CALs), which are the leading cause of acquired heart disease in children (1). Kawasaki disease shock syndrome (KDSS) is a severe subtype of KD first defined by Kanegaye et al. in 2009, and is characterized by systolic arterial hypotension or peripheral perfusion insufficiency during the acute phase of KD (2). Although it is relatively rare, KDSS poses a threat to children’s health. Patients with KDSS have an increased risk of reduced cardiac systolic function, coronary artery dilation, and valvular regurgitation; the mortality rate in such individuals can reach 6.8% (3,4). Early shock syndromes in KDSS patients often precede the typical KD signs, resulting in misdiagnosis and delayed treatment in clinical practice. Therefore, the main question of research in this area is how to find specific markers that can help identify KDSS as early as possible and enable clinicians to plan individualized therapeutic strategies to improve prognosis.

KDSS pathogenesis is that an immune inflammatory response causes endothelial cell damage in microvessels, resulting in microcirculatory disorders. Previous studies on diagnostic KDSS markers have focused on the inflammatory response, which involves elevated levels of leukocytes, neutrophils, C-reactive protein (CRP), procalcitonin (PCT), interleukin 6 (IL-6), interleukin 10 (IL-10), interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α) (3,5-7), as well as decreased serum albumin (ALB), phosphorus, and hyponatremia (8-10). However, vascular endothelial dysfunction is an important pathological feature of KDSS. Few studies have been reported on biomarkers based on endothelial cell dysfunction in KDSS.

In the current study, we explored the dynamic changes in vascular endothelial cell dysfunction in the early stages of KDSS by using a cellular impedance measurement system, a novel non-invasive electrical detection technique based on electrical impedance spectroscopy (EIS). In addition, we utilized tandem mass tag (TMT)-based proteomics, an isotope-labeled quantitative technique that enables the precise measurement of peptides and proteins via tandem mass spectrometry (MS/MS) (11), to screen proteins associated with endothelial cell function in KDSS and further validated their expression using Western blotting. We present this article in accordance with the MDAR reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-159/rc).

Methods

Patients and samples

The recruited study population included patients diagnosed with classic KD and KDSS based on the 2017 Scientific Statement from American Heart Association (AHA) and the Kanegaye criteria (1,2), as well as healthy children who underwent physical examination at the Children’s Hospital Capital Institute of Pediatrics, between April 2023 and January 2024.

The inclusion criteria for KDSS were as follows: (I) patients with KD also had to exhibit a decrease in systolic blood pressure of ≥20% from baseline or show clinical signs of poor perfusion, including tachycardia, prolonged capillary refill time, cold extremities, decreased pulse rate, oliguria, and other related symptoms; (II) KDSS patients with complete clinical records. Exclusion criteria were as follows: (I) KDSS patients with other acute or chronic diseases; (II) KDSS patients with recurrent conditions. A total of six KDSS patients (KDSS group) meeting the inclusion and exclusion criteria were included in this study.

Six KD patients (KD group) and six healthy control children (HC group) were included in the study, matched according to age and gender.

All plasma samples from KDSS and KD patients were collected before the administration of intravenous immunoglobulin (IVIG). The samples were centrifuged and stored at −80 ℃ until use.

The study protocol was approved by the Ethics Committee of the Capital Institute of Pediatrics (ethics approval No. SHERLL2024003) and was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the parents or guardians of all children enrolled in the KDSS, KD, and HC groups.

Cell culture and stimulation

Primary human coronary artery endothelial cells (HCAECs) were obtained (Hunan Fenghui Biotechnology Co., Ltd., Changsha, China) and cultured in endothelial cell complete medium (Hunan Fenghui Biotechnology Co., Ltd.) supplemented with 1% endothelial cell growth supplement (ECGS), 1% penicillin-streptomycin, 5% L-glutamine, and 5% fetal bovine serum (FBS). The medium was refreshed every 24 h. Cells were cultured in a humidified incubator at 37 ℃ with 5% CO₂. When the HCAECs reached 80–90% confluence, they were digested by trypsin, resuspended in fresh medium, and seeded into culture plates for subsequent assays. All experiments were conducted using cells between generations 3 and 5.

For the stimulation assays, the HCAECs were cultured in a medium containing 15% FBS. Once the cells reached over 95% confluence, half of the medium was replaced with fresh medium containing 15% plasma from KDSS, KD, or HC groups, and the cells were used for real-time monitoring.

Cell barrier function assessment

To monitor real-time changes in cell impedance, 1×10⁴ HCAECs were seeded onto CytoView Z-plates (CytoView-ZTM 96-Black, Atlanta, USA) and cultured in endothelial cell culture medium containing 15% FBS in a 5% CO₂ incubator. After treatment with plasma from KDSS, KD, and HC patients, the impedance of monolayer HCAECs was then dynamically monitored via the MaestroZ (Axion Biosystems, Atlanta, USA) impedance-based system, according to the user guidance. Cell impedance, which is positively correlated with cell barrier function, was recorded every minute in each cabinet. Data analysis was performed using Axis Z software (Axion Biosystems).

Low-abundance plasma protein extraction and collection

To enrich low-abundance proteins, highly abundant proteins were removed from 14 µl of plasma using a Seppro IgY 14 spin column (SEP010, Sigma-Aldrich). The removed proteins included ALB, α1-antitrypsin, IgG, IgA, IgM, transferrin, haptoglobin, α2-macroglobulin, fibrinogen, complement C3, α1-acid glycoprotein (Orosomucoid), high-density lipoproteins (HDLs) (apolipoproteins A-I and A-II), and low-density lipoproteins (mainly apolipoprotein B).

Pre-processing of plasma protein mass spectrometry detection

Proteins from plasma were extracted by pooling six low-abundance protein samples per group to minimize individual variability and ensure sample homogeneity. Each pooled sample (~100 µg) was subjected to denaturation using 8 M urea, followed by reduction with 10 mM dithiothreitol (DTT) at 37 ℃ for 1 h. To prevent disulfide bond reformation and ensure complete cysteine modification, 40 mM iodoacetamide was added and incubated in the dark at 37 ℃ for 1 h. The modified proteins were then desalted using a PD-10 column to remove residual reagents. Proteolysis was performed using trypsin at a 1:50 enzyme-to-protein ratio and incubating at 37 ℃ for 3 h.

Following digestion, peptide purification was performed using C18 solid-phase extraction (SPE) columns (Discovery DSC-18, Supelco), and the eluted peptides were subsequently concentrated using a pipette. The resuspended and dried peptides were quantified using a colorimetric assay (Thermo Fisher). For TMT labeling, 50 µg of peptides was incubated with TMT3 reagent in acetonitrile (30% final concentration) for 1 h. The labeling reaction was quenched with 5% hydroxylamine for 15 min. Labeled peptides were then separated using high-pH, one-dimensional reversed-phase chromatography in a Dionex Ultimate 3000 HPLC system. The tryptic peptides were loaded onto a Phenomenex column (Gemini NX 3U C18 110A; 150×2.00 mm) at a 200 mL/min flow rate, with fractions collected every 1.5 minutes to capture the full peptide profile. The collected fractions were combined, freeze-dried, and stored at −80 ℃ for future nano-HPLC/MS/MS analysis.

Mass spectrometry data analysis

The samples were analyzed using a QExactive HF mass spectrometer (Thermo Scientific, Bremen, Germany) coupled with an UltiMate 3000 RSLC nano-HPLC system (Dionex, Germering, Germany). We collected mass spectrometry imaging (MSI) data in Orbitrap at 120,000 resolution (m/z range 350–1,350) with a maximum injection time of 100 ms. Precursor ions with charge states ranging from 2 to 6 were selected for fragmentation, with a dynamic exclusion window of 60 seconds, and isotope peaks were excluded. Peptides were isolated using a quadrupole, subjected to MSI fragmentation, and analyzed in the ion trap within an m/z range of 400–2,000 for MS2. Raw data were searched against the Homo sapiens database (www.uniprot.org, UP00005610) using Peaks X Studio (Version 10.0, BSI). The precursor mass error tolerance was set to 10 ppm, while the fragment mass error tolerance was 0.02 Da. Peptide identifications were validated using a q-value threshold, maintaining a false discovery rate (FDR) of ≤1%. Post-translational modifications and chemical labeling settings included fixed cysteine alkylation, TMT-3plex labeling, variable methionine oxidation, and protein N-terminal acetylation. Identified proteins were required to contain at least one unique peptide, and only those with high confidence scores (−10logP>20) were considered reliably identified.

For technical repetition, mass spectrometry analyses were conducted in triplicate. Proteins detected in only one replicate were excluded, and missing values for the remaining proteins were imputed using the mean of the replicates. After excluding duplicates and unnamed proteins, the remaining proteins were retained for differential expression analysis. Differentially expressed proteins (DEPs) between KDSS, KD, and HC groups were identified using the “DESeq2” R package (1.20.0) with the thresholds of |log₂fold change| >1 and P<0.05. Volcano plots and Venn diagrams were plotted using an online platform (https://www.bioinformatics.com.cn) for data visualization (12). A trend analysis was then conducted using the OmicsShare online tools (https://www.omicsshare.com/tools/Home/Soft/getsoft).

Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)/REACTOME pathway enrichment analysis

GO enrichment analysis was performed for biological processes, cellular components, and molecular functions of DEPs. KEGG and REACTOME pathway enrichment analyses were conducted to predict the potential pathways associated with DEPs. All three analyses were carried out using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) online tools. The GO term enrichment of key proteins was visualized as a GO tree using the “ClueGo” plugin within Cytoscape software version 3.10.2.

Western blot analysis

The concentration of plasma proteins was assessed using a bicinchoninic acid (BCA) assay kit (PC0020, Solarbio, Beijing, China). SDS-PAGE gels were used to separate the proteins and nitrocellulose membranes were used to transfer them. After blocking with nonfat milk, the membranes were incubated with primary antibodies, followed by anti-rabbit IgG horseradish peroxidase (HRP)-conjugated secondary antibody (ZSGB-BIO, Beijing, China, ZB-2301; 1:5,000). Protein bands were visualized using enhanced chemiluminescence (ECL) detection reagents (7Sea Biotech., Shanghai, China). Western blot signals were normalized to the β-actin level. Densitometric analysis was performed using Image J software. The following primary antibodies were used: anti-β-actin (Proteintech, 20536-1-AP; 1:2,000); anti-vitronectin (Proteintech, 15833-1-AP; 1:2,000); anti-serotransferrin (Proteintech, 17435-1-AP; 1:3,000); anti-fibrinogen γ (Proteintech, 15841-1-AP; 1:2,000); S100A8 (Proteintech, 15792-1-AP; 1:4,000).

Correlation analyses between the validated protein and clinical laboratory parameters

We performed correlation analyses between the level of validated key protein and common laboratory parameters, including serum ALB, CRP, erythrocyte sedimentation rate (ESR), serum sodium, sIL-2R, IL-6, and IL-10. The values of these laboratory indicators were obtained from the medical record system after admission.

Statistical analysis

Statistical analyses were performed using SPSS Statistics (version 27.0.1) and GraphPad Prism (version 10.0). An independent-sample t-test was used to compare the two groups. One-way analysis of variance (ANOVA), followed by Bonferroni’s post hoc tests, was used to evaluate differences among multiple groups. Spearman’s correlation analysis was used to assess the relationships between the key protein identified in our study and clinical laboratory parameters. Data were expressed as mean ± standard deviation (SD). Statistical significance was defined as P<0.05.

Results

General information

The demographics, clinical characteristics, and laboratory indicators of the participants are presented in Table 1. Inflammatory cytokines, including IL-6 (259.37±385.20 vs. 32.96±22.84 pg/mL, P=0.02), sIL-2R (2,529.78±2,016.38 vs. 1,250.50±359.76 pg/mL, P=0.01), and IL-10 (63.20±49.91 vs. 12.85±9.47 pg/mL, P=0.005), were significantly increased in the patients with KDSS compared to those with KD.

Endothelial cell barrier dysfunction in KDSS

The endothelial barrier showed more rapid and severe dysfunction after treatment with KDSS plasma compared to KD plasma. A peak in cellular impedance was observed at the 10-hour point in all of the groups (indicated by the green arrow), indicating heightened cellular activity. A platform phase was observed between the 15-hour point (black arrow) and the 24-hour point (red arrow), followed by a falling sharply, which was more pronounced in the KDSS group. In contrast, the cellular impedance remained relatively stable in the HC groups (Figure 1A).

Figure 1 Severe coronary endothelial barrier disruption in KDSS acute phase. HCAECs were treated with plasma from KD, KDSS, or HC children (n=3), and cellular impedance was continuously monitored using the MaestroZ system. (A) Line graph showing the temporal dynamics of impedance after plasma intervention, starting at 0 hours. A notable peak in impedance was observed at the 10-hour point (green arrow), followed by a platform phase between the 15-hour point (black arrow) and the 24-hour point (red arrow). After 24 hours, impedance fell sharply, with a more pronounced decrease in the KDSS group. (B) Bar graph representing the impedance values of HCAECs after a 60-hour incubation period. Error bars represent mean ± SD; ^‡, P<0.001. HC, healthy control; HCAECs, human coronary artery endothelial cells; KD, Kawasaki disease; KDSS, Kawasaki disease shock syndrome; SD, standard deviation.

After 60 hours of plasma treatment, endothelial barrier dysfunction was evident in both the KD and KDSS plasma-treated cells, in contrast with the HC plasma-treated cells (P<0.001). Notably, the dysfunction was more pronounced in the KDSS group than in the KD group (P<0.001) (Figure 1B).

Proteomics reveals overall protein profiling of KDSS

A schematic diagram of the proteomic analysis and validation process is illustrated in Figure 2A. Western blotting confirmed the successful depletion of highly abundant proteins in the plasma samples (Figure 2B). A total of 1,196 proteins were identified by MS/MS across the three technical replicates. After data cleaning, as described in the Methods Section, 455 proteins were retained for further proteomic analysis. A cluster analysis of these proteins revealed distinct expression patterns between the KD and KDSS groups (Figure 2C).

Figure 2 Proteomics experimental procedure and basic information for all proteins. (A) Schematic diagram illustrating the experimental flow. (B) Quality control of plasma proteins after depletion of highly abundant proteins. (C) Heatmap showing protein expression levels across different plasma samples. HC, healthy control; KD, Kawasaki disease; KDSS, Kawasaki disease shock syndrome; MS, mass spectrometry; TMT, tandem mass tag.

Identification of DEPs in KDSS patients

The volcano plots visualized the DEPs in both the KDSS and KD groups compared with those in the HC group (Figure 3A,3B). By integrating these DEPs, we identified 58 up-regulated (Figure 3C) and 52 down-regulated proteins in the KDSS group (Figure 3D).

Figure 3 Proteomic analysis of protein profiles in KDSS patients. (A) Volcano plot showing DEPs between KDSS and HC groups. (B) Volcano plot showing DEPs between KD and HC groups. (C) Venn diagrams highlighting up-regulated DEPs (n=58) exclusively in KDSS vs. HC, compared with KD vs. HC. (D) Venn diagrams highlighting down-regulated DEPs (n=52) exclusively in KDSS vs. HC, compared with KD vs. HC. (E) GO analysis of up-regulated DEPs unique to KDSS. (F) KEGG pathway analysis of up-regulated DEPs unique to KDSS. (G) REACTOME pathway analysis of up-regulated DEPs unique to KDSS. (H) GO analysis of down-regulated DEPs unique to KDSS. (I) KEGG pathway analysis of down-regulated DEPs unique to KDSS. (J) REACTOME pathway analysis of down-regulated DEPs unique to KDSS. DEPs, differentially expressed proteins; GO, Gene Ontology; HC, healthy control; KD, Kawasaki disease; KDSS, Kawasaki disease shock syndrome; KEGG, Kyoto Encyclopedia of Genes and Genomes.

The GO biological process enrichment analysis of the 58 up-regulated proteins revealed their significant involvement in inflammation-related processes (e.g., complement activation and the innate immune response); coagulation-related pathways (e.g., blood coagulation and the negative regulation of fibrinolysis); and the killing of cells of another organism. The GO cellular components category further emphasized inflammation- and coagulation-associated functions, highlighting the membrane attack complex, fibrinolysis, platelet granules, and extracellular components involved in KDSS pathogenesis. The GO molecular functions enrichment analysis was primarily focused on heparin binding, extracellular matrix (ECM) structural constituents, calcium ion binding, complement component C3b binding, and serine-type endopeptidase activity (Figure 3E). The KEGG pathway analysis underscored ubiquitin-mediated proteolysis, mitophagy, and autophagy—key processes contributing to cellular damage in KDSS. Additionally, the regulation of the actin cytoskeleton pathway in plasma indicated the exposure of cellular contents following injury. Immune-related pathways, such as those associated with complement pathways, systemic lupus erythematosus, coronavirus disease 2019 (COVID-19), staphylococcus aureus infection, and amoebiasis, reflected the intense inflammatory environment in KDSS (Figure 3F). Similarly, the REACTOME pathway analysis revealed enrichment in pathways related to complement activation, immune response, coagulation, and cell death (Figure 3G).

Conversely, the GO biological process analysis of the 52 down-regulated proteins indicated their associations with lipid metabolism-related processes, including lipoprotein metabolic process, HDL particle remodeling, reverse cholesterol transport, lipid transport, negative regulation of very-low-density lipoprotein (VLDL) particle remodeling, and cholesterol efflux. The GO cellular components category was enriched in lipid-related components such as VLDL and HDL particles. In addition, extracellular components were also enriched among the down-regulated proteins. The GO molecular functions enrichment analysis focused on HDL particle receptor binding, HDL particle binding, lipid binding, and phospholipid binding. These included the positive regulation of cyclic-nucleotide phosphodiesterase activity, the negative regulation of calcium channel activity, and enzyme regulator activity, suggesting disrupted cellular functions in KDSS (Figure 3H). The KEGG pathway analysis pointed to several key signaling and lipid metabolism pathways, such as apelin signaling, phosphatidylcholine metabolism, cGMP-PKG signaling, and atherosclerosis-related pathways, along with cell adhesion, mitosis, and senescence (Figure 3I). The REACTOME pathway analysis further confirmed the down-regulation of basic biological functions and lipid metabolism pathways (Figure 3J). These results underscored the involvement of DEPs and their related pathways in KDSS pathophysiology.

Expression trend analysis of DEPs in KDSS

An expression trend analysis of 110 KDSS-specific DEPs across the HC, KD, and KDSS groups identified 84 DEPs with significant expression patterns. In profile 2, 42 DEPs were significantly up-regulated exclusively in the KDSS group (P<0.001), while 16 proteins showed a gradient up-regulation from KD to KDSS in profile 3 (P<0.001). Meanwhile, 26 proteins were exclusively down-regulated in the KDSS group in profile 1 (P<0.001) (Figure 4A). The expression profiles of the top 10 proteins in profiles 1, 2, and 3 are shown in Figure 4B-4D, including serotransferrin, immunoglobulin heavy constant alpha 1 (IGHA1), immunoglobulin heavy chain G 1-8 (IGHG1-8), and mucin 5B (MUC5B) in profile 1; fibrinogen γ, CRP, Coagulation factor XIII B chain (F13B), vitronectin, N-Deacetylase-N-Sulfotransferase 1 (NDST1), and Heparin cofactor 2 (SERPIND1) in profile 2; and S100A8 in profile 3.

Figure 4 Trend analysis of DEPs specifically expressed in KDSS plasma. (A) Major expression trend profiles of 110 DEPs across HC, KD, and KDSS groups. (B) Top 10 expressed proteins enriched in Profile 1. (C) Top 10 proteins in Profile 2. (D) Top 10 proteins in profile 3. (E) GO enrichment analysis of biological processes for proteins in the trend pattern profiles. The X-axis corresponds to the profile numbers shown in (A). (F) GO enrichment analysis of cellular components for proteins in the trend pattern profiles. (G) GO enrichment analysis of molecular functions for proteins in the trend pattern profiles. (H) KEGG pathway enrichment analysis for proteins in the trend pattern profiles. (I) REACTOME pathway enrichment analysis for proteins in the trend pattern profiles. APCS, serum amyloid P-component; APOA1, apolipoprotein A-I; APOA2, apolipoprotein A-II; APOM, apolipoprotein M; C2, complement C2; C5, complement C5; C6, complement C6; C8B, complement C8 beta chain; C9, complement C9; CFHR1, complement factor H-related protein 1; CRP, C-reactive protein; DEPs, differentially expressed proteins; DNAH5, dynein heavy chain 5 axonemal; F11, coagulation factor XI; F13B, coagulation factor XIII B chain; FGG, fibrinogen gamma chain; FGL1, fibrinogen-like protein 1; GO, Gene Ontology; HC, healthy control; HRG, histidine-rich glycoprotein; IGHA1, immunoglobulin heavy constant alpha 1; IGHV1-8, immunoglobulin heavy variable 1-8; IGKV2-30, immunoglobulin kappa variable 2-30; IGLV4-60, immunoglobulin lambda variable 4-60; ISLR, immunoglobulin superfamily containing leucine-rich repeat protein; KD, Kawasaki disease; KDSS, Kawasaki disease shock syndrome; KEGG, Kyoto Encyclopedia of Genes and Genomes; LDHB, L-lactate dehydrogenase B chain; MUC5B, Mucin-5B; NDST1, N-deacetylase-N-sulfotransferase 1; S100A8, Protein S100-A8; SERPIND1, heparin cofactor 2; TF, serotransferrin; TTR, transthyretin; VTN, vitronectin.

The GO biological processes enrichment analysis indicated that profile 1 was primarily associated with lipid metabolism, while profiles 2 and 3 were associated with inflammation and cell killing (Figure 4E). In the GO cellular components category, extracellular components, including the extracellular space, region, exosome, and collagen-containing ECM, were enriched across all three profiles. Profile 1 highlighted lipid particles, while profile 2 was uniquely associated with the membrane attack complex (Figure 4F). The GO molecular functions enrichment analysis yielded consistent results (Figure 4G). The KEGG pathway enrichment for DEPs in profile 1 emphasized cholesterol metabolism and ferroptosis, while profiles 2 and 3 focused on pathways related to cell death (e.g., ubiquitin-mediated proteolysis, mitophagy, and autophagy) and inflammation (Figure 4H). The REACTOME pathway enrichment confirmed these findings, with the down-regulation of lipid metabolism pathways and up-regulation of inflammatory pathways. Additionally, both up-regulated and down-regulated profiles were concentrated in pathways related to insulin-like growth factor (IGF) transport and uptake by IGF-binding proteins (IGFBPs), as well as platelet degranulation (Figure 4I).

Identification and validation of key proteins

We identified 13 candidate proteins by performing a differential expression analysis on 84 DEPs from trend profiles 1, 2, and 3 between the KDSS and KD patients, with |log₂fold change| >2 (Figure 5A). Detailed information on these proteins is provided in Table 2. The GO biological process enrichment analysis of these proteins highlighted that serotransferrin, fibrinogen γ, vitronectin, and S100A8 were strongly associated with inflammation cascades and cell functions (Figure 5B). The Western blot analysis confirmed that the plasma vitronectin level was significantly higher in the KDSS patients than in both the KD patients (P=0.02) and HC children (P=0.04) (Figure 5C,5D). Fibrinogen γ demonstrated a borderline significant difference in the overall ANOVA analysis (P=0.049), while subsequent post hoc multiple comparisons did not identify any statistically significant differences between the groups (KDSS vs. KD, P>0.99; KDSS vs. HC, P=0.09; KD vs. HC, P=0.11). Similarly, no significant differences were observed in the expression levels of serotransferrin (P=0.26) and S100A8 (P=0.43) among the three groups (Figure S1). The original Western blot images are provided in Figure S2. The increase in vitronectin was related to the regulation of endopeptidase activity, cell surface receptor signaling, and wound healing (Figure 5B).

Figure 5 Identification and validation of key proteins in KDSS plasma. (A) Candidate key proteins selected from 84 DEPs in trend profiles 1, 2, and 3 with |log₂fold change| >2 in KDSS vs. KD. (B) GO biological processes analysis of candidate proteins conducted using ClueGO. Different node colors correspond to the functional annotation of ontologies. (C) Western blot visualizing the level of vitronectin in plasma from KDSS, KD, and HC groups. β-actin was used as the loading control. The two black arrows indicate vitronectin bands at 75 kDa and 65 kDa, representing the natural single-chain forms. (D) Relative intensity values of the vitronectin are expressed as the mean ± SD, normalized to β-actin. *, P<0.05. AMOTL1, angiomotin-like protein 1; CRP, C-reactive protein; DEPs, differentially expressed proteins; F13B, coagulation factor XIII B chain; FC, fold change; FGG, fibrinogen gamma chain; GO, Gene Ontology; IGHA1, immunoglobulin heavy constant alpha 1; IGHV1-8, immunoglobulin heavy variable 1-8; KD, Kawasaki disease; KDSS, Kawasaki disease shock syndrome; MUC5B, mucin-5B; NDST1, N-deacetylase-N-sulfotransferase 1; S100A8, protein S100-A8; SD, standard deviation; SERPINA5, plasma serine protease inhibitor; SERPIND1, heparin cofactor 2; TF, serotransferrin; VTN, vitronectin.

In addition, the correlation analyses between the level of plasma vitronectin and clinical laboratory parameters indicated that significant positive correlations were observed between the level of plasma vitronectin and that of both serum sIL-2R (r=0.7545, P=0.04) and IL-10 (r=0.8498, P=0.01) (Figure S3).

Discussion

KDSS, a severe form of KD, is primarily characterized by shock caused by peripheral circulatory disturbances and exhibits a higher incidence of CALs than KD. In this study, we used dynamic cellular electrical impedance monitoring to explore the changes in endothelial cell barrier function in KD and KDSS patients. Our findings demonstrated that endothelial cell function impairment occurred 15 hours after the KDSS plasma treatment and persisted until the 24-hour point, with a sharp decline following this, which indicated that endothelial cell function was disrupted earlier and more severely in the KDSS patients than in those with KD. An important aspect of this finding was that the endothelial cell disruption started before the onset of KDSS symptoms. If early identification and intervention were achieved at this stage, this could potentially prevent subsequent disease progression.

Using TMT-labeled proteomics, we identified plasma proteins and pathways related to inflammation and endothelial barrier dysfunction in KDSS. Vitronectin was identified and validated to be up-regulated in KDSS, suggesting that it may be a potential biomarker.

The prevailing opinion on KDSS pathogenesis is that a severe inflammation cascade induces vascular endothelial dysfunction, leading to increased vascular permeability and serum ALB and sodium leakage (13,14). Elevated levels of inflammatory cytokines have frequently been observed in KDSS studies. Li et al. (6) identified values of IL-6 >66.7 pg/mL, IL-10 >20.85 pg/mL, and IFN-γ >8.35 pg/mL as high-risk factors for the development of KDSS in KD patients. Other studies have also reported that elevated IL-6 and IL-10 are particularly characteristic of KDSS in children (15,16). In our study, not only were the IL-6 and IL-10 levels higher in the KDSS patients than in those with KD but the proteomic analysis also revealed a broader activation of inflammatory pathways in KDSS plasma. These findings indicate that the intense inflammatory response plays a critical role in KDSS pathogenesis.

Orenstein et al. (17) reported that autopsy findings in KD patients indicated that endothelial barrier destruction in coronary arteries was an early event in KD, suggesting its role in initiating coronary artery injury. Considering the significant peripheral vascular dysfunction and the high risk of CALs observed in KDSS, we hypothesized that KDSS patients may experience more pronounced endothelial barrier disruption than KD patients. Previous studies have demonstrated disrupted endothelial permeability in KD in vitro by evaluating endothelial permeability using transwell assays or measuring the expression of junctional proteins through molecular biology techniques (18,19). However, these findings fail to capture the dynamic changes in endothelial function and do not provide a clear indication of whether there are differences in the timing and severity of endothelial barrier injury between KD and KDSS. The EIS-based technique we used has been proven to be effective for the real-time monitoring of endothelial barrier function and is widely applied in other vascular injury-related diseases (20,21). Using this technique, we also confirmed the timing and severity of endothelial barrier dysfunction in KD and KDSS patients, revealing that endothelial cell dysfunction occurred 15 hours after the KDSS plasma treatment and persisted until the 24-hour point, followed by a sharp decline. Our results provided strong evidence for more profound endothelial barrier disruption in children with KDSS than in those with KD, aligning with clinical observations of hypotension or peripheral perfusion insufficiency.

Vitronectin is a multifunctional, ubiquitous cell adhesion and spreading factor primarily produced by the liver and secreted as part of serum proteins and the ECM. Under physiological conditions, vitronectin can improve the endothelial permeability, while aberrantly expressed vitronectin is involved in inflammatory responses and cardiovascular pathology under pathological conditions (22). Overexpressed vitronectin can modulate several key biological processes, including coagulation, membrane attack complex formation, and cell migration (23). It promotes the expression of inflammatory factors such as IL-6 and leukemia inhibitory factors in dry eye disease (24). Large-scale proteomic studies on heart failure also reported increased vitronectin, which can trigger nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome activation and induce pyroptosis (25,26). In inflammatory bowel disease, elevated vitronectin disrupts intestinal epithelial cell differentiation through phosphodiesterase 4 (PDE4)-mediated ferroptosis (27). Wang et al. reported an elevated soluble urokinase plasminogen activator receptor (uPAR) level in a subgroup of KD patients with a high rate of shock (28). uPAR has been identified as one of the downstream receptors of vitronectin (29). Therefore, we hypothesized that the over-activation of the vitronectin-uPAR pathway may mediate the inflammatory response and endothelial cell barrier dysfunction seen in KDSS. Hirose et al. (30) reported that gap formation and the fenestration of endothelial cells contribute to increased vascular permeability through skin biopsy in KD patients. Vascular endothelial growth factor (VEGF) plays a key role in this process, which is a key factor in vascular permeability (31,32). Vitronectin acts downstream of the VEGF receptor 2 pathway (33). Based on this, we suggest that vitronectin may be involved in the VEGF-induced endothelial permeability disorder seen in KDSS.

Increased sIL-2R levels are recognized as markers of ongoing immune activation (34). Previous studies have demonstrated that sIL-2R is elevated in KD patients and may serve as a predictor of disease activity (35,36). In our study, the serum sIL-2R level was significantly higher in the KDSS patients compared to that in the KD patients without shock, indicating a more severe inflammatory state in KDSS patients. Furthermore, IL-2Rγ has been implicated in epidermal barrier disruption (37). Given the significant positive correlation observed between the plasma vitronectin and sIL-2R levels in this study, we speculate that sIL-2R may also be involved in endothelial barrier dysfunction in KDSS.

The IL-10 family cytokines are crucial for maintaining tissue homeostasis during infection and inflammation, primarily by limiting excessive immune responses, enhancing innate immunity, and promoting tissue repair (38). IL-10 is typically up-regulated as part of a compensatory anti-inflammatory response. Our findings showed that the IL-10 level was higher in the KDSS patients than that in the KD patients without shock, consistent with the findings of previous studies (6,35). Moreover, we identified a significant positive correlation between the plasma vitronectin and IL-10 levels. Acharya et al. (39) demonstrated that the combined stimulation of dendritic cells with lipopolysaccharide (LPS) and vitronectin leads to enhanced IL-10 production. Based on these findings, we propose that elevated plasma vitronectin during systemic inflammation may contribute to the increased IL-10 level in KDSS patients.

This study has several limitations. First, the small sample size may limit the statistical power and the robustness of our conclusions. Further studies with a large KDSS cohort are required to validate our findings and confirm the identified biomarkers. Second, the proteomics results were not validated at the cellular level, requiring further experiments to confirm vitronectin’s role in endothelial barrier dysfunction in HCAECs. Additionally, the removal of high-abundance plasma proteins may have influenced the outcomes of the protein assays.

Conclusions

In conclusion, this study provides a potential plasma proteomic profile for KDSS. DEPs in KDSS plasma were enriched in the cell activation signaling- and inflammatory cascade-related pathways. Vitronectin may serve as a diagnostic pathogenesis-based biomarker for KDSS.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-159/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-159/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-159/prf

Funding: This study was supported by the National Natural Science Foundation of China (No. 82370511 to X.L.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-159/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol was approved by the Ethics Committee of the Capital Institute of Pediatrics (ethics approval No. SHERLL2024003) and was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the parents or guardians of all children enrolled in the KDSS, KD, and HC groups.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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