Biomarkers for the Discrimination of Acute Kawasaki Disease From Infections in Childhood

Markers of Endothelial Dysfunction in Kawasaki Disease: An Update

Kawasaki disease (KD) is a medium vessel vasculitis that has a special predilection for coronary arteries. Cardiovascular complications include the development of coronary artery abnormalities (CAAs) and myocarditis. Endothelial dysfunction (ED) is now recognized to be a key component in the pathogenesis of KD and is believed to contribute to the development of CAAs. ED has been evaluated by several clinical parameters. However, there is paucity of literature on laboratory markers for ED in KD. The evaluation of ED can be aided by the identification of biomarkers such as oxidative stress markers, circulating cells and their progenitors, angiogenesis factors, cytokines, chemokines, cell-adhesion molecules, and adipokines. If validated in multicentric studies, these biomarkers may be useful for monitoring the disease course of KD. They may also provide a useful predictive marker for the development of premature atherosclerosis that is often a concern during long-term follow-up of KD. This review provides insights into the current understanding of the significance of ED in KD.

Role of Neutrophil Extracellular Traps in Health and Disease Pathophysiology: Recent Insights and Advances

Neutrophils are the principal trouper of the innate immune system. Activated neutrophils undergo a noble cell death termed NETosis and release a mesh-like structure called neutrophil extracellular traps (NETs) as a part of their defensive strategy against microbial pathogen attack. This web-like architecture includes a DNA backbone embedded with antimicrobial proteins like myeloperoxidase (MPO), neutrophil elastase (NE), histones and deploys in the entrapment and clearance of encountered pathogens. Thus NETs play an inevitable beneficial role in the host's protection. However, recent accumulated evidence shows that dysregulated and enhanced NET formation has various pathological aspects including the promotion of sepsis, pulmonary, cardiovascular, hepatic, nephrological, thrombotic, autoimmune, pregnancy, and cancer diseases, and the list is increasing gradually. In this review, we summarize the NET-mediated pathophysiology of different diseases and focus on some updated potential therapeutic approaches against NETs.

Retrospective analysis of children diagnosed with Kawasaki disease

BACKGROUND

The aim of our study was to evaluate the long-term impacts of Kawasaki disease on our patients regarding coronary involvement demographic characteristics, treatment regimens, and clinical course.

METHODS

Our study included 104 patients diagnosed and hospitalized with Kawasaki disease in our center, from January 2004 to January 2019. In our study, patients were divided into three groups according to coronary artery involvement. Patients in group 1 had no echocardiographic findings, while the ones in group 2 had coronary artery dilatation and ones in group 3 had coronary artery aneurysm (CAA).

RESULTS

Among 104 patients, the median age was 9.15 (3.0-22.0) years, and 61 of the patients were male while 43 of the patients were female. With a wide range of 1.50-16.50 years of follow-up time, the median diagnosis age of our patients was 31 months (3.0-164.0). Fever duration (median day 10 (5-21), p = 0.025) was statistically significantly higher in group 3. Blood C-reactive protein (CRP) levels, white blood cell (WBC) counts, and neutrophil counts were significantly higher in group 3. There was a statistically significant difference between patients in group 3 and group 2 in which the lowest strain deformation values were in the patients of group 3. In contrast to group 1, the time for initiation of IVIG therapy is significantly prolonged both in group 2 (median: 9.5 days, p = 0.028) and group 3 (median: 10 days, p = 0.036).

DISCUSSION

In our study, serum CRP levels, WBC count, and neutrophil count were higher in patients with coronary artery abnormalities, in agreement with the previous studies. In the light of our results, we consider that the most important determining factor for the development of coronary artery aneurysm is the time of intravenous immunoglobulin (IVIG) administration.

Metabolic profiling reveals altered tryptophan metabolism in patients with kawasaki disease

Kawasaki disease (KD) is a childhood vasculitis disease that is difficult to diagnose, and there is an urgent need for the identification of accurate and specific biomarkers. Here, we aimed to investigate metabolic alterations in patients with KD to determine novel diagnostic and prognostic biomarkers for KD. To this end, we performed untargeted metabolomics and found that several metabolic pathways were significantly enriched, including amino acid, lipid, and tryptophan metabolism, the latter of which we focused on particularly. Tryptophan-targeted metabolomics was conducted to explore the role of tryptophan metabolism in KD. The results showed that Trp and indole acetic acid (IAA) levels markedly decreased, and that l-kynurenine (Kyn) and kynurenic acid (Kyna) levels were considerably higher in patients with KD than in healthy controls. Changes in Trp, IAA, Kyn, and Kyna levels in a KD coronary arteritis mouse model were consistent with those in patients with KD. We further analyzed public single-cell RNA sequencing data of patients with KD and revealed that their peripheral blood mononuclear cells showed Aryl hydrocarbon receptor expression that was remarkably higher than that of healthy children. These results suggest that the Trp metabolic pathway is significantly altered in KD and that metabolic indicators may serve as novel diagnostic and therapeutic biomarkers for KD.

An Artificial Intelligence Derived Blood Test to Diagnose Kawasaki Disease

OBJECTIVE

To develop a highly sensitive and specific blood biomarker panel that identifies febrile children with Kawasaki disease (KD).

METHODS

We tested blood samples from a single-center cohort of KD (n = 50) and control febrile children (n = 100) to develop a biomarker panel from 11 candidates selected by their assay clinical availability. We used machine learning with least absolute shrinkage and selection operator regression to identify 11 blood markers with values incorporated into a model, which provided a binary predictive risk score for KD determined with Youden's index. We further reduced the model using least angle regression.

RESULTS

Using 10-fold cross-validation with least absolute shrinkage and selection operator regression on these 11 readouts plus patient age resulted in an area under the receiver operating characteristic curve of 0.94 (95% confidence interval [CI]: 0.90-0.98; P <.01). Using Youden's index, which provided an optimal cut off for a binary predictive risk score, 88 of 97 KD-negative patients were diagnosed negative, and 47 of 50 KD-positive patients were positive, yielding a sensitivity of 0.94 (95% CI: 0.87-1.0) and specificity of 0.91 (95% CI: 0.85-0.96). Least angle regression reduced the final panel to 3 biomarkers: C-reactive protein, NT-proB-type natriuretic peptide, and thyroid hormone uptake. The predictive model then provided an area under the receiver operating characteristic curve of 0.92 (95% CI: 0.87-0.96; P <.001) along with sensitivity and specificity at 86% each.

CONCLUSIONS

Machine learning identified a highly accurate diagnostic model for KD. The reduced model employs 3 biomarkers currently approved by regulatory bodies and performed on platforms commonly used by certified diagnostic laboratories.

Exploring the diagnostic value of eosinophil-to-lymphocyte ratio to differentiate Kawasaki disease from other febrile diseases based on clinical prediction model

Kawasaki disease (KD) is a febrile disease that affects children under 5 years of age and leads to serious cardiovascular complications such as coronary artery disease. The development of markers that can predict early is important to reduce the under- and misdiagnosis of KD. The aim of this research was to develop a diagnostic predictive model to differentiate Kawasaki disease (KD) from other febrile diseases using eosinophil-to-lymphocyte ratio (ELR) and other biomarkers. We recruited a total of 190 children with KD and 1604 children with other febrile diseases. We retrospectively collected clinical information from the children, which included laboratory data on the day of admission, such as white blood cells (WBC), hemoglobin (HGB), calcitoninogen (PCT), hypersensitive c-reactive protein (CRP), snake prognostic nutritional index (PNI), peripheral blood neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and ELR. We performed analyses using univariate analysis, multivariate logistic regression, and column line plots, and evaluated the diagnostic parameters of the predictive models. ELR was significantly increased in patients with KD. After multivariate logistic regression, WBC, HGB, CRP, NLR, ELR and PNI were finally included as indicators for constructing the prediction model. The ROC curve analysis suggested that the C-index of the diagnostic prediction model was 0.921. The calibration curve showed good diagnostic performance of the columnar graph model. The cut-off value of ELR alone for KD was 0.04, the area under the ROC curve was 0.809. Kids with KD show highly expressive level of ELR compared to children with febrile disease, which can be used to diagnose KD, and column line graphs constructed together with other indicators can help pediatricians to identify KD more effectively from febrile children.

S100A8/A9 Is a Marker for the Release of Neutrophil Extracellular Traps and Induces Neutrophil Activation

Neutrophils are the most abundant innate immune cells in the circulation and they are the first cells recruited to sites of infection or inflammation. Almost half of the intracellular protein content in neutrophils consists of S100A8 and S100A9, though there has been controversy about their actual localization. Once released extracellularly, these proteins are thought to act as damage-associated molecular patterns (DAMPs), though their mechanism of action is not well understood. These S100 proteins mainly form heterodimers (S100A8/A9, also known as calprotectin) and this heterocomplex is recognized as a useful biomarker for several inflammatory diseases. We observed that S100A8/A9 is highly present in the cytoplasmic fraction of neutrophils and is not part of the granule content. Furthermore, we found that S100A8/A9 was not released in parallel with granular content but upon the formation of neutrophil extracellular traps (NETs). Accordingly, neutrophils of patients with chronic granulomatous disease, who are deficient in phorbol 12-myristate 13-acetate (PMA)-induced NETosis, did not release S100A8/A9 upon PMA stimulation. Moreover, we purified S100A8/A9 from the cytoplasmic fraction of neutrophils and found that S100A8/A9 could induce neutrophil activation, including adhesion and CD11b upregulation, indicating that this DAMP might amplify neutrophil activation.

Kawasaki Disease Patient Stratification and Pathway Analysis Based on Host Transcriptomic and Proteomic Profiles

The aetiology of Kawasaki disease (KD), an acute inflammatory disorder of childhood, remains unknown despite various triggers of KD having been proposed. Host 'omic profiles offer insights into the host response to infection and inflammation, with the interrogation of multiple 'omic levels in parallel providing a more comprehensive picture. We used differential abundance analysis, pathway analysis, clustering, and classification techniques to explore whether the host response in KD is more similar to the response to bacterial or viral infections at the transcriptomic and proteomic levels through comparison of 'omic profiles from children with KD to those with bacterial and viral infections. Pathways activated in patients with KD included those involved in anti-viral and anti-bacterial responses. Unsupervised clustering showed that the majority of KD patients clustered with bacterial patients on both 'omic levels, whilst application of diagnostic signatures specific for bacterial and viral infections revealed that many transcriptomic KD samples had low probabilities of having bacterial or viral infections, suggesting that KD may be triggered by a different process not typical of either common bacterial or viral infections. Clustering based on the transcriptomic and proteomic responses during KD revealed three clusters of KD patients on both 'omic levels, suggesting heterogeneity within the inflammatory response during KD. The observed heterogeneity may reflect differences in the host response to a common trigger, or variation dependent on different triggers of the condition.

Future Biomarkers for Infection and Inflammation in Febrile Children

Febrile patients, suffering from an infection, inflammatory disease or autoimmunity may present with similar or overlapping clinical symptoms, which makes early diagnosis difficult. Therefore, biomarkers are needed to help physicians form a correct diagnosis and initiate the right treatment to improve patient outcomes following first presentation or admittance to hospital. Here, we review the landscape of novel biomarkers and approaches of biomarker discovery. We first discuss the use of current plasma parameters and whole blood biomarkers, including results obtained by RNA profiling and mass spectrometry, to discriminate between bacterial and viral infections. Next we expand upon the use of biomarkers to distinguish between infectious and non-infectious disease. Finally, we discuss the strengths as well as the potential pitfalls of current developments. We conclude that the use of combination tests, using either protein markers or transcriptomic analysis, have advanced considerably and should be further explored to improve current diagnostics regarding febrile infections and inflammation. If proven effective when combined, these biomarker signatures will greatly accelerate early and tailored treatment decisions.

Boolean analysis of the transcriptomic data to identify novel biomarkers of IVIG response

Intravenous immunoglobulin (IVIG) is used to treat several autoimmune and inflammatory diseases, but some patients are refractory to IVIG and require alternative treatments. Identifying a biomarker that could segregate IVIG responders from non-responders has been a subject of intense research. Unfortunately, previous transcriptomic studies aimed at addressing IVIG resistance have failed to predict a biomarker that could identify IVIG-non-responders. Therefore, we used a novel data mining technique on the publicly available transcriptomic data of Kawasaki disease (KD) patients treated with IVIG to identify potential biomarkers of IVIG response. By studying the boolean patterns hidden in the expression profiles of KD patients undergoing IVIG therapy, we have identified new metabolic pathways implicated in IVIG resistance in KD. These pathways could be used as biomarkers to segregate IVIG non-responders from responders prior to IVIG infusion. Also, boolean analysis of the transcriptomic data could be further extended to identify a universal biomarker that might predict IVIG response in other autoimmune diseases.

Clinical aspects for differential diagnosis of Kawasaki disease shock syndrome: a case control study

Background

Because of the absence of a specific diagnostic test and pathognomonic clinical features, physicians must rely on the presence of specific clinical criteria and laboratory data that support the diagnosis of KD. To help clinicians distinguish KD, KDSS, septic shock, and TSS earlier, we suggest differential diagnosis and treatment guideline.

Methods

Medical records of immunocompetent patients who were admitted to the pediatric department with a diagnosis of KDSS, septic shock or TSS (SS group) were retrospectively reviewed. In addition, KD patients were selected by seasonal matching to each case of KDSS patient by date of admission (± 2 weeks).

Results

There were 13 patients with KDSS, 35 patients with SS group, and 91 patients with KD. In comparison between KDSS and septic shock group, KDSS group had significantly higher rate of coronary aneurysm incidence, and higher left ventricle dysfunction rate. In comparison between KDSS and TSS, patients with KDSS had a significantly higher erythrocyte sedimentation rate (ESR) and significantly lower creatinine. Receiver operation characteristic curve revealed that the optimal ESR cut off value for determining the KDSS was 56.0 (sensitivity 75.0%, specificity of 100.0%) and the optimal creatinine cut off value for determining the TSS was 0.695 (sensitivity 76.9%, specificity 84.6%).

Conclusions

Clinical symptoms, laboratory finding, echocardiography, and culture studies can be used to differentiate KD, KDSS, septic shock and TSS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-020-02488-w.

Lower CMV and EBV Exposure in Children With Kawasaki Disease Suggests an Under-Challenged Immune System

Background: Kawasaki Disease (KD) is a pediatric vasculitis of which the pathogenesis is unclear. The hypothesis is that genetically pre-disposed children develop KD when they encounter a pathogen which remains most often unidentified or pathogen derived factors. Since age is a dominant factor, prior immune status in children could influence their reactivity and hence the acquisition of KD. We hypothesized that systemic immune responses early in life could protect against developing KD. With this study we tested whether the incidence of previous systemic cytomegalovirus (CMV) or Epstein-Barr virus (EBV) infection is lower in children with KD compared to healthy age-matched controls. Methods and Results: We compared 86 KD patients with an age-matched control group regarding CMV and EBV VCA IgG measurements (taken before or 9 months after IVIG treatment). We found that both CMV and EBV had an almost 2-fold lower seroprevalence in the KD population than in the control group. Conclusions: We suggest that an under-challenged immune system causes an altered immune reactivity which may affect the response to a pathological trigger causing KD in susceptible children.