Kawasaki Disease (KD) is an acute childhood febrile illness predominately affecting children below 5 years. It is a systemic vasculitis with a special predilection for coronary arteries (Newburger et al., 2004). It is now recognized as the most common cause of acquired heart disease in children in the developed world (Banday et al., 2021). The incidence of the KD ranges from 10 to 25 per 100,000 children below five years in North America and Europe. The highest incidence of KD is reported in children of Japanese ancestry; 350 per 100,000 children below 5 (Singh et al., 2015). Approximately 1% of all Japanese children would develop KD by the age of 10. Although many centers in India are now diagnosing children with KD on a regular basis, the vast majority of patients are perhaps still going undiagnosed and unreported (Singh et al., 2015). KD has the potential to cause severe complications and significant morbidity and mortality. We have reported that the mortality rate in our cohort has been 0.8%. This is significantly higher than mortality figures of ≤0.04% reported in developed countries (Singh et al., 2016).

Even after more than five decades of the initial description of the disease, the diagnosis of KD is still clinical and based on a constellation of clinical features. There is no pathognomonic laboratory feature. Differential diagnosis of KD includes several febrile illnesses in children, including viral infections (e.g., measles, Epstein Barr virus, and adenovirus), scarlet fever, toxic shock syndrome, and drug reactions like Stevens-Johnson syndrome or serum sickness. Clinical symptoms of KD include persistent fever for more than five days, rash, swelling of the dorsum of hands and feet, red strawberry tongue, conjunctival nonsuppurative injection, cervical lymphadenopathy, periungual peeling, and diffuse mucosal inflammation (McCrindle et al., 2017; CDC, 2020). Children with scarlet fever do not have lip changes and eye changes, which are present in KD. While rash in scarlet fever is characteristically sandpaper, KD can have a pleomorphic rash. Elevated antistreptolysin O (ASO) titer, positive throat culture for β hemolytic streptococcal group A, and brisk response to antimicrobials are other characteristic features of scarlet fever. Similarly, one can differentiate KD from other common differentials based on the constellation of clinical features (Jindal et al., 2019). Standard of care involves high-dose of intravenous immunoglobulin (IVIG) along with oral aspirin in the acute phase of the disease, which helps to resolve inflammation and minimize the risk of coronary arteries abnormalities (CAAs) (Oates-Whitehead et al., 2003). Approximately 10%–20% of children with KD doses did not respond to first-line therapy and persisted in having inflammation, known as IVIG resistant KD. Despite timely treatment, 3%–5% of patients with KD can develop CAAs. In patients having IVIG resistant KD, the chances of development of CAAs remain high (Ogata et al., 2013; Skochko et al., 2018; Brogan et al., 2020). KD remains the most common cause of acquired heart disease among children in Japan, North America, and Europe (Banday et al., 2021).

Multiple theories regarding the etiology of KD have been hypothesized such as infectious theory, infectious plus autoimmunity, RNA virus theory, and superantigen theory. However, none of them has been independently able to provide an exact mechanism for the initiation and progression of pathogenic mechanisms in KD (Ramphul and Mejias, 2018; Nakamura et al., 2019). The present consensus strongly indicates a complex interplay of infectious triggers in children with a genetic predisposition of KD, followed by an abnormal immune response (Dietz et al., 2017; Nakamura et al., 2019).

Over the last few years, high-throughput platforms such as microarray have emerged as potent tools to detect differential gene expression profiles and have been recognized as significant clinical approaches with efficient diagnosis at the molecular level, prognostic prediction, stratification of patients, and identification of therapeutic targets. To date, quite a number of genes have been examined in KD, which were usually selected based on information regarding their function in inflammation, immune response, and other biological mechanisms. Recently, gene expression profiling studies have been conducted to understand the pathophysiology of KD (Hoang et al., 2014; Dietz et al., 2017; Wu et al., 2019; Rahmati et al., 2020; Gao et al., 2021); however, the prognostic power of identified genes still remains unclear. Therefore, understanding the pathogenesis of KD is essential for identifying novel pathways that can be targeted for therapy. The current study was conducted to find out the most important hub genes among the known ones.

In our recent study, we explored the role of epigenetic factors in modulating the gene expression in KD (Sharma et al., 2021). Transcriptomic profiles in KD can reveal perturbations caused by inflammation or infection, which could help to delineate the pathogenesis of KD. In the present study, we extracted a large-scale expression dataset of a similar microarray-based platform to investigate the pathogenesis of KD. Using an integrated transcriptomic approach, we identified differentially expressed genes (DEGs) in KD. The underlying pathways were recognized using functional annotation and via constructing protein–protein interaction (PPI) network. This data from the present study could help to conceptualize the molecular events underpinning KD and identify diagnostic biosignature and design a biomarker panel.

A systematic search of the studies was carried out up to December 2021. The search with the keywords “Kawasaki Disease” in Homo sapiens and “expression profiling by array” resulted in 13 microarray gene expression datasets (Table 1). We have combined those studies which implement the same methodology/platform and where >2 datasets were available. From 13 data sets, we have chosen four datasets which belong to the same platform GPL10558 (Table 2).

Despite recent advancements in clinical research, the exact etiology of KD is still poorly understood, and there is no laboratory test for confirmation of diagnosis, especially when the clinical presentation is incomplete or atypical. As a result, early diagnosis of KD may be different to establish. Growing evidence from the immunological, molecular, genetic, and epigenetic studies reveal that epidemiology might differ based on the infectious trigger for KD, especially in some children with a predilection based on genetic factors (Agarwal and Agrawal, 2017; McCrindle et al., 2017; Noval Rivas and Arditi, 2020; Sharma et al., 2021). In such individuals, a putative primary immune response may be activated in mucosal lymphoid tissues. This is then followed by activation of a cytokine cascade resulting in an uncontrolled systemic immune response. Inflammation of medium-sized vessels (especially the coronary arteries) probably results from the extravasation of immune cells in the sub-endothelium. Involvement of coronary arteries results in the development of coronary artery abnormalities (CAAs) (Senzaki, 2006). Therefore, early diagnosis of KD is essential for management decisions in children with KD.

In the last decade, several studies have been conducted to identify the genetic markers for KD; however, a consistent molecular marker having a significant prognostic value has not yet been determined. Furthermore, it is known that despite treatment, approximately 3%–5% of patients with KD would still develop CAAs. Therefore, understanding the pathogenesis of KD is essential for identifying novel pathways that can be targeted for therapy. The current study used an integrated transcriptomic analysis approach to identify DEGs with significant expression change in KD. These molecular biomarkers may be used as a novel multifunctional biomarker panel for diagnosis and therapeutic targets in patients with KD.

Recently, several studies have been conducted on gene expression and genome-wide association in patients with KD. However, there is no consensus on specific genes or biological pathways responsible for the pathogenesis of KD (Popper et al., 2007; Burgner et al., 2009; Onouchi et al., 2012; Xie et al., 2018; Chen et al., 2020; Johnson et al., 2021). The present study aims to pin down specific genes using large-scale datasets on microarray profiles from the GEO database and with the aid of bioinformatics provide key hub genes. Genome-wide expression data in whole-blood samples of KD patients and in controls were obtained using four different GSE datasets with the same array platform, and an integrated bioinformatic analysis was performed. As a result, 126 shared DEGs were screened out and these were mainly enriched in immune and inflammatory responses. The identified 15 hub genes were all significantly upregulated in KD. After careful inspection, we found that five of the 15 hub genes, including ITGAM, MMP9, S100A12, TLR2, and FCER1G, were involved in the top GO item neutrophil degranulation.

The top 10 hub genes from the analyzed data sets in our study were IL-1β, ITGAM, TLR2, CXCL8, SPI1, S100A12, MMP9, PRF1, TLR8, and TREM1. Of these, IL-1β had the highest degree of a node (Lau et al., 2008). IL-1β is a potent proinflammatory cytokine that has been responsible for chronic inflammatory conditions such as cardiovascular disease, coronary artery lesions, and vasculopathy, relevant to the pathogenesis of KD (Lee et al., 2012). Enhanced circulating levels of IL-1β have been reported in KD patients as compared to controls (Hoang et al., 2014; Porritt et al., 2020). Upregulated IL-1β expression is associated with IVIG resistance (Weng et al., 2010; Fu et al., 20192019). Studies have shown that administration of IL-1 receptor antagonist (anakinra) in the KD mice model effectively prevents the development of coronary artery aneurysm, vasculitis, and myocarditis (Lee et al., 2012; Wakita et al., 2016). Based on the genetic and transcriptomic studies and evidence from the mice-model studies, anakinra is undergoing clinical trials (clinicaltrials.gov: NCT02179853) for the treatment of patients with KD.

The KEGG pathway analysis indicated that most DEGs were enriched in SLE and may thus be immune response-associated genes. While overlap of SLE and KD has been occasionally reported in the literature, this is extremely unusual. Both KD and SLE are immune-mediated disorders characterized by distinctive clinical features. However, some clinical findings are common to both conditions. These include fever, lymphadenopathy, arthritis or arthralgia, ocular and mucosal manifestations, rash, and multisystemic involvement. In addition, there appears to be a strong interplay between immunological and genetic factors in the pathogenesis of both KD and SLE (Guleria et al., 2020; Saez-de-Ocariz et al., 2020). ITGAM (Integrin αM) was one such gene with the second highest degree of nodes (44) in our analysis. ITGAM is associated with SLE (Han et al., 2009) and is found to be upregulated in KD patients with vasculopathy (Hom et al., 2008; Reindel et al., 2013). ITGAM, also known as CD11b, belongs to the integrin family and is involved in the regulation of neutrophils, monocyte activation, adhesion, and migration to damaged endothelium associated extracellular matrix. Moreover, studies have shown increased ITGAM levels in peripheral blood and upregulated protein expression in patients with KD (Reindel et al., 2013; Wu et al., 2019).

Immune system activation is one of the major pathogenic mechanisms of KD. These pathways play a crucial role in the innate immune response by recognizing pathogen-associated molecular patterns (PAMPs) of infectious agents. Huang et al. (2009) found that mRNA levels of TLR2 and TLR8 were significantly elevated in patients with KD as compared to controls. Furthermore, after treatment with IVIG therapy, the level of TLR mRNA expression in KD patients was decreased. Studies have shown that augmented expression of TLR2 on CD14⁺ monocytes is observed in patients with KD and in coronary arteritis mice model, suggesting their role in immunopathogenesis (Rosenkranz et al., 2005; Lin et al., 2012; Mitsui et al., 2014). Therefore, these TLRs may be used as inflammatory biomarkers for the identification of patients with KD.

CXCL2, also known as interleukin-8 (IL8), is a member of the CXC chemokine family, known to possess tumorigenic properties. It is involved in proinflammatory activities, such as neutrophil degranulation, amelioration of adhesion molecule expression on neutrophils’ surfaces and directional migration of neutrophils (Brat et al., 2005). In the acute phase of KD, IL-8 is overexpressed in mononuclear cells and polymorphonuclear neutrophils of patients with KD as compared to controls (Lin et al., 1992; Asano and Ogawa, 2001). Furthermore, Asano et al. showed that IL-8 protein and the neutrophil chemoattractant activity within plasma were increased in the acute phase of KD and were significantly elevated following IVIG therapy (Asano and Ogawa, 2001).

Spi-1 proto-oncogene (SPI1) is a protein-coding gene mainly involved in the activation, differentiation, activation, and migration of macrophages or B cells. This gene was also identified as one of the hub genes in a study by Gao et al. (2021). The role of the SPI1 gene is yet not explored in KD.

Activation of TREM-1 (triggering receptor expressed on myeloid cells-1), trigger receptor is found to be associated with the pathogenesis of KD. Zhao et al. have shown that serum soluble TREM-1 protein concentrations were significantly higher in the acute phase of KD as compared to controls, indicating its involvement in vasculitis and CAAs in patients with KD (Zhao and Wang, 2016). Our results confirm that the expression of the TREM gene was significantly upregulated in patients with KD.

S100 calcium-binding protein A12 (S100A12) belongs to the S100 protein family. Serum SAA00A12 levels were significantly higher in patients with KD, and the levels declined significantly after treatment with IVIG (Foell et al., 2003; Abe et al., 20051950; Armaroli et al., 2019; Lech et al., 2019; Gao et al., 2021). Furthermore, expression of S100A12 increased on the surface of circulating endothelial cells of patients with KD and persisted for a longer duration in KD patients with CAAs, indicating the role of S100A12 in the development of CAAs. In addition, S100A12 stimulates monocytes to produce IL-8, which in turn induces coronary artery endothelial cell dysfunction (Armaroli et al., 2019). Li et al. have shown that IVIG therapy and S100A12 antibody had similar effects on reducing neutrophil infiltration (Lin et al., 1992). Data from these studies highlight the potential of S100A12 as an imperative biomarker for monitoring patients with KD. Despite this, detailed mechanisms through which S100A genes regulate the pathogenesis of KD have not yet been well studied. We hope that our results will enhance our understanding of the role of the S100A gene family in the pathogenesis of KD.

Matrix metalloproteinases-9 (MMP-9) has been implicated in the pathogenesis of several disorders, including tumor metastasis, inflammatory disorders, and atherosclerosis (Sakata et al., 2010). The role of MMP-9 in the pathogenesis of KD has also been highlighted. Overexpression of MMPs induces degradation of the extracellular matrix. Takeshita et al. (2001) hypothesized that in patients with KD, activated neutrophils and monocytes produce MMP-9 in large amounts, that upon migration leads to the breakdown of basement membrane that resulting in vascular damage and coronary artery inflammation. This hypothesis was validated in the mice model by Lau et al. (2008). Studies have shown that serum levels of MMP-9 are elevated in KD patients and were found to play an important role in the development of CAAs (Takeshita et al., 2001; Chua et al., 2003; Gavin et al., 2003; Wu et al., 2019). Perforin-1 (PRF1) is one of the major cytolytic proteins of cytolytic granules. One of the main pathways of lymphocyte-mediated cytolysis entails the secretion onto target membranes of cytolytic granules contained in cytolytic effector lymphocytes of T-cell or NK-cell type (https://omim.org/entry/170280). This gene is related to hemophagocytic lymphohistiocytosis (HLH) but has no reports in KD. We assumed that together all these hub genes may play a key role in the pathogenesis of KD. However, future studies need to be conducted to verify this hypothesis.

The integrated transcriptomic approach, along with the bioinformatic analysis used in the present study, helped to reveal deregulated molecular mechanisms explaining the underlying etiology of KD. Furthermore, using data from more than one microarray dataset and their healthy controls helped eliminate the potential influences of clinical, demographic, and environmental factors on transcriptomic analysis. The 10 hub genes may provide clues to understanding the pathogenesis of KD pathogenesis and could be used to design a biomarker panel to monitor patients with KD.