Deciphering Kawasaki disease genetics through next-generation sequencing: A scoping review

Abstract

BACKGROUND

Kawasaki disease (KD) is an acute self-limiting childhood vasculitis. KD is considered the most common cause of acquired heart disease in children worldwide. Despite being the leading cause of acquired heart disease in children, its etiology remains poorly understood. Several epidemiological studies reveal a strong genetic predisposition to KD susceptibility, underlying coronary artery abnormalities (CAAs) and treatment resistance to intravenous immunoglobulin (IVIG).

AIM

To evaluate the current literature on the roles of targeted next-generation sequencing (NGS), whole-exome sequencing (WES) and/or whole-genome sequencing (WGS) in identifying genetic susceptibility loci, immunopathogenic pathways, and mechanisms of IVIG resistance in KD.

METHODS

We performed a literature search to identify key genes and pathways associated with genetic susceptibility, IVIG resistance, and CAAs development in KD. Our search was conducted across PubMed, Scopus, and Google Scholar. Studies investigating these features using targeted NGS, WES or WGS were included in this review. Studies employing other methods to investigate genetic susceptibility, IVIG resistance, and CAA among KD patients were excluded.

RESULTS

Targeted NGS, WES and WGS studies of the KD cohort across different regions have identified both rare and common variants associated with KD-related phenotypes. Genes with these variants were linked to immune regulation and vascular biology. Genes linked with innate and adaptive immune responses included TLR6, MEF2A, HLA-DRB1, IL6ST, MYH14, RBP3, EFCC1, FCRLA, PTGER4, IL17F, CARD11, and SIGLEC10. Studies have also revealed genes associated with CAA. These genes were IL17RC, FGFR4, IL31RA, FNDC1, MMP8, and FOXN1, all of which were implicated in inflammatory and vascular remodelling processes. WGS studies also identified novel loci associated with IVIG resistance. These were FANK1, MAP2K3, KCNJ12, CA10, CWH43, EDN1, PPP2R5E, and SFMBT2, as well as previously established genes such as ITPKC, CASP3, FCGR2A, CD40, and IL1B. Many of these genes have known or proposed functions in biological pathways potentially relevant to KD, including TLR and NF-κB signalling, IL-17-mediated cytokine pathways, calcium/NFAT signalling, MAPK signalling, vascular remodelling, and endothelial dysfunction. Moreover, sex-biased variants (EFCC1, LMO7, CEMIP, and USH2A) also revealed gender-based differences in KD susceptibility, indicating a higher risk of KD in boys.

CONCLUSION

Studies using NGS-based approaches have significantly advanced understanding of KD by identifying key candidate genes and pathways associated with disease susceptibility, CAAs, and IVIG response, and IVIG resistance. These findings support a multi-pathway immunovascular model of KD. Future studies involving larger, ethnically diverse cohorts and functional validation are essential for clinical translation.

Key Words: Kawasaki disease; Whole genome sequencing; Whole exome sequencing; Coronary artery abnormalities; Genetic susceptibility; Intravenous immunoglobulin resistance

Core Tip: Whole exome sequencing and whole-genome sequencing are emerging as important tools for understanding the genetic basis of Kawasaki disease (KD). This review summarises current evidence showing how these techniques help identify key genes, immune pathways, and factors linked with coronary artery complications and intravenous immunoglobulin resistance. The findings suggest that KD is a genetically complex and heterogeneous disease involving multiple immune and vascular pathways. These insights are useful for improving risk prediction and guiding personalised treatment. Further large-scale studies in diverse populations are required to translate these findings into routine clinical practice.

INTRODUCTION

Kawasaki disease (KD) is an acute, self-limiting childhood systemic vasculitis of unknown etiology that predominantly affects children under 5[1]. Since its first description in 1967 by Kawasaki[2], the diagnosis of KD has remained primarily clinical. KD has now replaced rheumatic fever as the most common cause of acquired heart disease in children worldwide[3]. Diagnosis continues to rely entirely on clinical criteria, including persistent fever for at least 4 days, accompanied by mucocutaneous manifestations such as conjunctival injection, oropharyngeal changes, polymorphous rash, peripheral extremity involvement (palmar erythema, oedema, periungual desquamation), and cervical lymphadenopathy[1]. Although primary and secondary observations of KD have been extensively studied over the last few decades, no pathognomonic laboratory marker has yet been established to confirm the diagnosis[4].

Symptom-based clinical variability among KD patients leads to complications and delays in timely diagnosis[5]. Children with KD can develop coronary artery abnormalities (CAAs) in up to 25% of untreated cases and even in 3%-5% of those receiving timely therapy[1,6].

CAAs in KD can progress to thrombosis, myocardial infarction, and sudden cardiac death[7-10]. The aetiology of KD remains elusive, but clinical and epidemiological features, including seasonal clustering, low recurrence, and spatial-temporal case aggregations, suggest an infectious trigger in genetically predisposed individuals[11,12]. KD incidence demonstrates striking ethnic and geographic disparities[13]. There is an unusually high rate of KD among children of East Asian ancestry, specifically in Japan, Korea and Taiwan. Each year, Japan alone reports more than 15000 children with KD[14,15]. In addition to this familial clustering, KD appears to be predominantly seen in males; furthermore, it often recurs among multiple siblings of affected individuals[16-19].

The current standard of care for KD includes administering high-dose intravenous immunoglobulin (IVIG) (2 g/kg) along with oral aspirin[1]. When given early in the course of the illness, IVIG significantly reduces the likelihood of the development of CAAs in a child with KD. However, despite this therapy, approximately 10%-20% of patients who have received IVIG continue to experience a poor outcome, with significant increases in the risks for development of CAAs[1]. This highlights the need to identify biomarkers that can predict how well a patient will respond to IVIG therapy and how severe their disease is likely to be.

Over the past decade, high-throughput next-generation sequencing (NGS) has greatly enhanced our ability to study the genetics of KD[20,21]. Specifically, whole-exome sequencing (WES) and whole-genome sequencing (WGS) have been used by researchers to investigate many previously unexplored aspects of the genetic basis of KD[22,23].

Previously published genetic studies have identified several genes, including IL-10, CD40L, IL-4, CASP3, IL-18, ITPKC, and certain HLA alleles, as contributing to KD susceptibility[24-28]. Studies have also demonstrated that variants in various components of the TGF-β signalling pathway (including TGFB2, TGFBR2, and SMAD3) contribute to an individual’s susceptibility to KD and CAAs[29,30].

In addition to Genome-Wide Association Study (GWAS) and candidate-gene studies, targeted NGS panels have identified immune-related variants associated with KD susceptibility and IVIG resistance. These studies complement WES/WGS by providing high-depth analysis of predefined candidate genes, whereas WES and WGS enable unbiased genome-wide discovery of both common and rare variants.

WES/WGS have significantly advanced our understanding of the genetic basis of complex diseases, including KD[23,31]. These approaches, powered by NGS technology, enable simultaneous interrogation of millions of DNA fragments. WES targets protein-coding regions (only 1%-2% of the genome), where most known disease-causing variants occur[32]. In contrast, WGS encompasses both coding and non-coding regions, enabling a more comprehensive evaluation of genetic variation, including structural variants and regulatory elements[32].

In contrast to GWAS and candidate gene studies, which primarily detect common genetic variants, WES and WGS enable the identification of novel and rare variants across the genome (both coding and non-coding changes)[23,33]. WES and WGS have helped identify novel variants related to immune response, inflammation, and vascular injury, as well as genes associated with IVIG resistance and CAAs development in KD cohort studies[22,23,33,34].

Given the complexities of KD pathogenesis and its complex genetics, the objective of this review is to synthesise and critically assess current developments in the use of WES and WGS to unravel the genetic susceptibility of KD. We have summarized the role of NGS technologies for understanding disease mechanisms, IVIG resistance, CAAs development, and population-specific risk loci in children with KD. A better understanding of the genetic basis of KD could enable early diagnosis, patient stratification, and targeted therapeutic interventions.

MATERIALS AND METHODS

A literature search was conducted through PubMed, Google Scholar, and Scopus to identify relevant peer-reviewed studies. This review aimed to identify studies that used targeted NGS, WES and/or WGS to detect variants in both coding and non-coding DNA regions associated with genetic susceptibility, IVIG resistance, and CAAs in KD. The search strategy combined Medical Subject Headings (MeSH) terms and keywords to identify articles for the review. We used the following search terms: “Kawasaki disease”, “genetic predisposition”, “whole exome sequencing”, “whole genome sequencing”, “next-generation sequencing”, “coronary artery aneurysms”, “coronary artery lesions”, “coronary artery abnormalities”, and “IVIG resistance”. Studies published between 2015 and 2025 were included.

This scoping review was conducted in accordance with the PRISMA guidelines. A systematic literature search was performed in PubMed, Scopus, and Google Scholar to identify studies investigating the genetic basis of KD using sequencing-based approaches. The search included articles published from 2015 to 2025 and was restricted to English-language studies.

Studies were included if they were original, peer-reviewed articles that investigated the genetic basis of KD using whole-exome, whole-genome, or targeted sequencing approaches and reported sequencing-derived genetic variants associated with disease susceptibility, CAA, IVIG resistance, or other clinically relevant outcomes. Review articles, book chapters, conference abstracts, studies focusing exclusively on non-coding RNA or microRNA, single-cell sequencing studies, GWAS without sequencing data, single-nucleotide polymorphism (SNP)-array or single-SNP studies, and non-English publications were excluded (Figure 1). A total of 12 studies were included in the scoping review.

Figure 1 Flow diagram illustrating the literature search and study selection process for this scoping review. GWAS: Genome-Wide Association Study; SNP: KD: Kawasaki disease.

RESULTS

Findings from whole-exome and whole-genome sequencing in KD

We identified 12 relevant studies that were selected and critically analyzed for this review. These genetic studies on KD have shown that the condition arises in genetically susceptible children, with multiple loci influencing susceptibility and coronary artery complications[23,33-35]. Early candidate-gene approaches and GWAS identified variants in immune-related genes, including FCGR2A, CD40, HLA class II, and ITPKC, suggesting possible involvement of immune activation, B-cell signalling, and T-cell regulation in KD[24,36,37].

Complementary targeted sequencing studies have further strengthened the evidence generated by WES and WGS. Amano et al[38] employed pooled genome sequencing targeting 39 immune-related cytokine receptor genes and identified a low-frequency IL4R variant (rs563535954) that was significantly associated with IVIG unresponsiveness. Although no alteration in IL4R expression was observed. This variant was absent among IVIG-responsive patients, suggesting its potential utility as a predictive biomarker for IVIG resistance, pending validation in larger cohorts. Song et al[39] employed targeted capture sequencing of 512 immune-related genes and 472 previously reported GWAS loci, identifying 319 significant expression quantitative trait loci (eQTL) associated with KD. Notably, variants in ITPR3 (rs2229634), PIK3CD (rs11121484, rs1141402), and PRKCZ (rs34108055) were associated with altered gene expression, supporting a role for dysregulated innate immune signalling in KD pathogenesis[39]. These findings complement unbiased WES/WGS studies by providing functional evidence linking immune dysregulation to disease pathogenesis.

A schematic overview integrating genes identified through WES and WGS, along with their roles in immune activation, cytokine signalling, and vascular inflammation, is presented in Figure 2.

Figure 2  Genes identified in whole exome sequencing and whole genome sequencing studies highlighting their association with immune response, intravenous immunoglobulin resistance, intravenous immunoglobulin responsiveness, coronary artery abnormalities, and gender-biased susceptibilities in Kawasaki disease patients.

Genetic susceptibility of KD

High-throughput sequencing studies have identified candidate variants associated with KD susceptibility across genes involved in immune signalling and vascular biology[22,23,33,34,40]. Worldwide, several groups have identified SNPs in various genes that may contribute to the predisposition to KD. Associations involving ITPKC, CASP3, and FCGR2A have been reported in multiple cohorts, although effect estimates and reproducibility may vary across populations and ancestries[37,41].

WGS analyses have identified several novel susceptibility loci, including TLR6 and MEF2A, which implicate innate immune signalling and vascular integrity in KD pathogenesis[23]. A large KD cohort study using WGS further highlighted FANK1, MAP2K3, KCNJ12, CA10, CWH43, FRG1DP, and gene-based associations with EDN1, PPP2R5E, SFMBT2, CSMD2, HIVEP1, and HSP90AB1. SNPs in these genes have been shown to be associated with IVIG resistance and immune modulation in KD[35]. In another independent KD cohort, Shrestha et al[34] have identified several genes associated with KD, including KLRC2, ZMAT4, NDUFA5, MICU2, PTPRD, TCAF2, WHAMM, LOC100127, ACTR3BP2, MYBPC3, and FRG1DP. Among these genes, NDUFA5 has been shown to be associated with CAA in KD, while MICU and ZMAT4 may be indirectly linked to CAA development. The utility of the WGS method in a boy (8-month-old age) with refractory KD identified variants in the ORAI1 and BLK genes[42]. These genes have been linked to the calcineurin/NFAT signalling pathway[43].

Complementary WES studies reinforce immune and vascular pathways. Variants in HLA-DRB1, IL6ST, VEGFB, ITPKC, CASP3, ORAI1, and SMAD9 have been associated with KD susceptibility and CAAs risk[8,21,22,40]. These studies emphasise the role of T-cell activation, apoptosis, and cytokine signalling in KD. Other WES findings have revealed rare genetic variants in MYH14 and RBP3 associated with KD susceptibility, while EFCC1 and sex-biased variants in USH2A, LMO7, and CEMIP highlight genetic heterogeneity across cohorts[22,40]. Importantly, pathway-level analyses consistently implicate NF-kappaB signalling, calcium-dependent processes, and endothelial regulation, aligning with prior GWAS studies but offering deeper resolution at the rare-variant level[23,34,42]. These gene-level associations, along with their corresponding SNPs and functional implications, are systematically summarized in Table 1.

Table 1 Summary of genes identified in Kawasaki disease through whole exome sequencing, whole genome sequencing, and targeted sequencing approaches.

Ref.	Cohort size	Sequencing approach	Genetic variants identified	rs IDs (reference SNP IDs)	Observed associations
Kim et al[23]	6 family members including 2 siblings affected with KD (n = 6)	WGS	Rare: TLR6, MEF2A common: ARRDC4, SLK, TACSTD2	rs5743809, rs35220466, rs12650224, rs6822503, rs12645200, rs5743826, rs6837101, rs373652230, rs1552673, rs10786779, rs6584583 and rs14008	TLR6-NF-κB signalling pathway upregulation
Kanda et al[42]	Refractory KD (n = 1)	WGS	ORAI1, BLK	rs3741596 and rs2254546	Calcineurin/NFAT signalling pathway upregulation
Shrestha et al[34]	KD (n = 472)	WGS	FANK1, MAP2K3, KCNJ12, FRG1DP, FRG1BP, DEFB115, CWH43, CCZ1B, MIR3683, FRG1JP, FLJ43315	rs77740910, rs73368612, rs113336767, rs75317727, C20_29079715, C20_30491365, C4_49554582, C7_6981323, C9_63906587	IVIG resistance
			CA10	rs74255119	IVIG responsiveness
Shrestha et al[35]	KD (n = 504)	WGS	KLRC2, ZMAT4, NDUFA5, MICU2, PTPRD, TCAF2, WHAMM, LOC100127, ACTR3BP2, MYBPC3, FRG1DP	rs62154092, rs28730284, rs9643846, rs9643847, rs57504215, rs60545202, rs59556769, rs73677451, rs12676292, rs4332118, rs6988966, rs10276547, rs10280266, rs600075, rs5896385, rs1218424730, rs11259953, rs11259954, rs34163760, rs12585631, rs1052373, rs1424006606, rs1396081550, rs1258107032, rs1379390981, rs1424309393	Disease susceptibility, severity, and CAAs involving immune dysregulation, mitochondrial dysfunction and vascular remodelling pathways
Kim et al[33]	KD (n = 200)	WES	FCRLA, PTGER4, IL17F, CARD11, SIGLEC10	rs2275603, rs755244149, rs117796773, rs41493047, and rs201376644	Disease susceptibility
			IL31RA, FGFR4, FNDC1, MMP8, FOXN1	rs148721785, rs201812753, rs374967242, rs61754773, and rs188424977	Development of CAAs
Zhang et al[22]	KD (n = 93)	WES	RBP3 and MYH14	RBP3: c.2650G>A, MYH14: c.566G>A, MYH14: c.1109C>T, MYH14: c.3917T>G, MYH14: c.4301G>A, MYH14: c.5026C>T, MYH14: c.5329 C>T, MYH14: c.5393 C>A, and MYH14: c.5476 C>T	Rare coding variants
Xu et al[40]	KD (n = 1272)	WES	USH2A, LMO7, CEMIP, EFCC1	rs148135241, rs142687160, rs12441101, and rs142391828	Sex-biased variants
Wang et al[44]	KD (n = 110)	WES	HLA-DRB1, IL6ST, IL17RC, VEGFB, ITPKC, CASP3, ORAI1, MYH11, SMAD9	rs17882084, rs781455079, rs143781415, rs776229557, rs76358638, rs577739464, rs769061106, rs146388001, rs185661462, rs758895653, rs767136120, rs397514715 and rs200651392	Disease susceptibility and development of CAAs
Nakamura et al[46]	KD + PFAPA (n = 3)	WES	CARD8	rs140826611	Inflammasome link (NLRP3 regulation)
Chen et al[21]	KD (n = 330)	Targeted gene panel	CD247, PPIE, FLT4, CUL1, LBP, IL2RA, MAP2K1, MAPK11	rs840016, rs2463260, rs56401579, rs56193546, rs10271133, rs2007404, rs12358961, rs16949924, rs2232595, and rs742185	IVIG resistance
			ACVR2B, CD24	rs77317995, rs6530599, rs6530600, rs1136210	IVIG responsiveness
Amano et al[38]	KD (n = 82)	Targeted gene panel	IL-4R	rs563535954	IVIG responsiveness
Song et al[39]	KD (n = 190)	Targeted gene panel	ITPR3, PIK3CD, PRKCZ	rs2229634, rs11121484, rs1141402, rs34108055	Dysregulated innate immune signaling in KD

KD: Kawasaki disease; WES: Whole exome sequencing; WGS: Whole genome sequencing; IVIG: Intravenous immunoglobulin; CAA: Coronary artery abnormalities; SNP: Single nucleotide polymorphism; rs ID: Reference SNP identifier.

Genetic factors contributing to the development of CAAs

WGS approach: Kim et al[23] reported the first application of WGS in KD, involving 6 family members, 2 of whom had KD. The study developed a systematic pipeline for variant filtration to identify disease-associated loci and stratified variants into two levels. Authors used 3 layers of filtering: (1) Recessive homozygotes variants in exons, promoters, splice sites or the 3’-UTR with an minor allele frequency (MAF) < 1% or missing in the 1000 Genomes database; (2) Compound heterozygotes variants, with an MAF < 3% prioritized by relevance to KD-related genes and KD transcriptomic data; and (3) Common variants (MAF > 5%) predicted as deleterious via in silico tools[23]. These variants are grouped into Tier 1 and Tier 2. Tier 1 contained homozygous or compound heterozygous mutations in exons, promoters, splice sites, or UTRs, with an allele frequency of < 1%. Tier 2 included the common variants (allele frequency > 5%) identified as deleterious by in silico methods[23]. TLR6 and MEF2A were grouped into Tier 1 variants and identified as candidate genes associated with KD[23]. Interestingly, TLR6 variants (p.Leu194Pro and p.Arg247 Lys) were identified only in affected siblings, suggesting a role for TLR6 in both familial and sporadic KD[23]. Further, 41 variants in regulatory and coding areas of TLR6 (the promoter, intron 1, exons 2 and 3, the 3’ UTR) were correlated with a predisposition to KD[23]. eQTL analysis revealed intronic SNPs (rs56245262, rs56083757, and rs7669329) in TLR6 that may mediate IL-6 expression during the acute phase of KD and are potentially linked to inflammatory pathways implicated in coronary vasculitis[23].

Transcriptional upregulation of TLR6 and MEF2A was observed during the acute phase of KD, whereas their expression decreased during the convalescent phase[23]. In addition, a CAG repeat variant (rs373652230) in MEF2A was identified in 2 affected siblings and may be associated with coronary pathology[23]. Together, these findings suggest that TLR6 and MEF2A may contribute to CAAs development in KD[23].

WES approach: Kim et al[33] were the first to use WES to investigate the genetic predisposition to CAAs in children with KD, using a Korean cohort of 200 patients with KD and 902 healthy controls. Subgroup analysis of KD patients with CAAs (n = 26) and without CAAs (n = 124) identified 5 coding-region SNPs associated with CAAs[33]. These variants included rs148721785 in IL31RA, rs201812753 in FGFR4, rs374967242 in FNDC1, rs61754773 in MMP8, and rs188424977 in FN1 gene[33].

Wang et al[44] subsequently performed a WES study in 55 KD patients (15 with CAAs and 40 without CAAs) and 55 age- and gender-matched healthy controls. CAAs were defined according to the Z-score classification criteria of Dallaire and Dahdah[45]. The study identified 4 SNPs in KD patients: rs17882084 in HLA-DRB1, rs781455079 in IL6ST, rs143781415 in IL17RC, and rs776229557 in VEGFB[44]. Among these, rs17882084 and rs781455079 were significantly enriched in patients with KD compared with healthy controls[44]. Importantly, rs143781415 in IL17RC was significantly enriched in patients with KD who developed CAAs, suggesting a possible CAAs-specific genetic association[44]. In contrast, rs17882084 did not differ significantly between the KD with CAA and KD without CAA subgroups[44].

Nakamura et al[46] identified a CARD8 variant in 3 patients with Periodic Fever, Aphthous Stomatitis, Pharyngitis, Adenitis (PFAPA) syndrome who subsequently developed KD. Two of the 3 patients who presented with KD later developed PFAPA syndrome without any cardiovascular complications. The third patient developed KD one year after the onset of PFAPA syndrome and exhibited dilatation of the left main coronary artery[46]. WES was performed to identify disease-susceptibility variants in the 3 KD patients[46]. WES data analysis predicted a single heterozygous TT insertion (p.V148fs; rs140826611) in exon 8 of the CARD8 gene[46]. The CARD8 gene is an essential component of the NLRP3 inflammasome (a complex of NLRP3, ASC, caspase-1, and CARD8). The study by Ito et al[47] has shown that the CARD8 gene negatively regulates inflammasome activation and modulates IL-1β levels. Recent studies have also demonstrated the potential role of the NLRP3 inflammasome in the pathogenesis of KD[48-50]. However, this observation was based on 3 patients with overlapping PFAPA syndrome and KD, and the identified CARD8 variant should therefore be considered a hypothesis-generating finding rather than an established KD susceptibility variant.

IVIG resistance in KD

WGS approach: WGS in KD has substantially improved our understanding of its genetic basis, particularly regarding IVIG resistance[35]. Since 2017, a series of studies has employed WGS to identify both rare and common variants associated with KD susceptibility, disease severity, and treatment response[23,34,35,42]. These studies have progressed from exploratory familial investigations to larger population-based analyses, each providing complementary insights.

In the WGS-based study by Kim et al[23], the expression of TLR6 and MEF2A was upregulated during the acute phase and downregulated during the convalescent phase of KD. Although this study did not specifically investigate IVIG response, the immune-related functions of these genes provide a mechanistic rationale for further exploration of their roles in refractory KD[23].

Expanding on the concept of immune dysregulation in KD, Kanda et al[42] reported a case of an 8-month-old male infant presenting with refractory KD. The patient failed to respond to 2^nd dose of IVIG, 4 cycles of methylprednisolone pulse therapy, infliximab and oral prednisolone. Clinical remission was eventually achieved after treatment with cyclosporine A[42]. To explore possible genetic factors associated with the refractory clinical course, WGS was performed, which identified two SNPs: ORAI1 (rs3741596) and BLK (rs2254546)[42]. The former variant was a non-synonymous missense mutation (p.Ser218Gly) in exon 2 of ORAI1 and was classified as benign according to the ACMG guidelines[42]. Although classified as benign, it has previously been associated with KD and atopic dermatitis[51,52]. ORAI1 encodes a calcium channel that regulates store-operated calcium entry, a process crucial for T-cell activation, and is expressed across a range of hematopoietic cells[28]. Functional studies suggest that this variant may confer a gain-of-function effect, leading to increased calcium influx and contributing to excessive cytokine production and IVIG resistance in patients with KD[42,53].

The second variant, rs2254546, in the BLK gene, is known to influence B lymphocyte tyrosine kinase expression and has also been implicated in rheumatoid arthritis[54,55]. Reduced BLK activity impairs B-cell receptor signalling and increases T-cell activation via CD86, promoting a pro-inflammatory environment. Together, these findings suggested that increased calcium signalling, driven by polymorphisms in ORAI1 and BLK, may underlie IVIG refractoriness in children with KD[42].

To further examine genetic susceptibility in patients with KD who do not respond to IVIG, Shrestha et al[34] performed a large-scale WGS study to systematically identify genetic loci associated with IVIG response. The study included 472 patients with KD, of whom 305 were IVIG responders, and 167 were non-responders. Genome-wide association mapping revealed significant signals on chromosomes 10, 17, and 20, and several loci showed potential associations with inter-individual variability in IVIG response[34]. The top 10 SNPs were found on chromosome 20, and the major genes were FANK1, MAP2K3, KCNJ12, CA10, FRG1DP, and CWH43[34]. To measure the effects of rare genetic variants associated with KD, the authors adopted a gene-based aggregation approach using the SNP-set Kernel Association Test to improve in-depth detection[34]. This methodology identified additional genetic variants in MAN1A2, EDN1, SFMBT2 and PPP2R5E, CSMD2, LINC01317, HIVEP1, HSP90AB1 and TTLL11, showing association with KD. These genes are involved in key biological processes associated with immune regulation, vascular function, and cell signalling pathways. Nevertheless, their functional relevance to KD and IVIG response has not yet been fully established[34].

WES and targeted NGS approach: The study of genes associated with IVIG resistance in KD has also accelerated with the use of more cost-effective NGS technologies (particularly WES)[21]. Chen et al[21] applied an NGS multi-gene panel (560 candidate genes) to a cohort comprising 330 KD patients (50 IVIG-resistant and 280 IVIG-responders) and 105 healthy controls to identify genes associated with IVIG resistance in KD. This sequencing panel covered 4 major immune-related pathways: TLR signalling, cytokine receptor interaction, TGF-β signalling, and T-cell receptor signalling[21]. After stringent quality filtering and variant calling with GATK Haplotype Caller, 15677 SNPs were identified; of these, 577 showed significant differences between IVIG-resistant and responder groups[21]. Among these, 14 key SNPs were significantly associated with IVIG resistance[21].

IL2RA, which is involved in immune regulation and has been implicated in autoimmune conditions, emerged as a particularly relevant gene for IVIG resistance[21]. The role of CD247 in T cell activation, well established in autoimmune diseases such as systemic lupus erythematosus, further supports the immunogenetic basis of IVIG resistance in patients with KD[56,57]. Kuo et al[58] independently validated the association of the IL2RA SNP rs3118470 with CAAs in KD patients, linking IVIG resistance to CAAs development.

Gender-biased variants in KD susceptibility

Several studies have reported gender bias in KD incidence[59,60]. Earlier work also identified male-specific associations of SNPs in the FCGR2A, SEMA6A, and IL17REL genes[61]. Despite these observations, sex-biased genetic variants contributing to KD susceptibility remain insufficiently studied, particularly using high-throughput sequencing approaches[40].

To investigate this, Xu et al[40] performed WES in 25 patients (15 male and 10 female) with KD. For validation, the authors analysed genotype data from an additional 1247 patients with KD (713 males and 534 females) and 803 healthy children (481 males and 322 females)[40]. After filtering, 34 sex-biased variants across 34 genes were identified in the WES cohort[40]. These 34 variants were subjected to functional enrichment analysis for sex-biased genes in KD[40]. Among the 34 variants, enrichment analysis identified 6 as priorities: USH2A (rs148135241), EFCC1 (rs142391828), CEMIP (rs12441101), F5 (rs13306334), LMO7 (rs142687160), and PLOD3 (rs75592752)[40]. Of these, 4 variants-LMO7, CEMIP, EFCC1, and USH2A-were significantly different between male and female patients with KD[40]. Notably, only one variant in the EFCC1 gene (rs142391828) in the allele/dominant model (CA + AA) has been reported to be associated with KD susceptibility[40]. The minor allele frequencies of SNPs rs148135241, rs142687160, and rs12441101 were higher in female patients than in male patients, whereas rs142391828 (EFCC1) showed the opposite pattern, with a higher frequency in boys[40].

Tissue-specific expression data indicate that EFCC1 is highly expressed in platelets of normal individuals, suggesting a role in maintaining platelet function[40]. Earlier studies have reported increased platelet activation, apoptosis, and mitochondrial autophagy (mitophagy) in KD patients complicated by thrombosis during the convalescent phase[62-64].

A comprehensive summary of genes identified through WES, WGS, and targeted sequencing approaches, along with their associated SNPs and clinical implications, is presented in Table 1, while the comparative evaluation of study design, cohort characteristics, strengths, and limitations across these studies is detailed in Table 2.

Table 2 Critical evaluation of whole exome sequencing, whole genome sequencing, and targeted sequencing studies in Kawasaki disease.

Ref.	Enrolled patients	Major strengths	Study constraints	Associated pathways/clinical implications
Kim et al[23]	Familial KD (n = 6)	(1) First WGS in KD; (2) Tier-based variant filtering; and (3) Linkage-based study	Small sample size; no replication cohort; limited functional validation	Innate immunity role in KD susceptibility
Kanda et al[42]	Refractory KD (n = 1)	(1) Deep phenotyping; therapeutic; and (2) Correlation study with calcium signalling	Single case study; limited generalizability	Pharmacogenomic importance of the genes involved in calcium signalling in KD
Shrestha et al[34]	IVIG-responder (n = 305) vs IVIG-resistant (n = 167)	(1) Large cohort; (2) Gene-based rare variant analysis; and (3) Aggregation (SKAT) study to find the IVIG response	Population-specific; limited mechanistic validation	Potential genes that may serve as predictors of IVIG response in KD
Shrestha et al[35]	KD (n = 504) (CAA vs non-CAA)	(1) Large multi-ethnic cohort; (2) WGS-based comprehensive variant discovery; and (3) Integration of SNP association with FUMA mapping and genetic risk scoring	No independent validation cohort; limited functional validation	Genetic variants linked to CAAs development and persistence, highlighting mitochondrial dysfunction, immune regulation, and vascular remodelling, with potential for predictive risk modelling in KD
Kim et al[33]	KD (n = 200) vs controls (n = 902)	(1) Replication, cohort-based study; and (2) Identification of coding variant focus associated with CAA	Mostly rare SNP associations; need functional data	5 rare coding SNPs associated with CAAs in KD
Zhang et al[22]	KD (n = 93) vs controls (n = 91)	(1) Identification of rare variants and their enrichment based on stringent filtering (CADD > 25); and (2) Identification of novel loci	A modest sample size; no external validation was performed	Rare variants in the MYH14 and RBP3 genes are associated with disease susceptibility
Xu et al[40]	Sex-biased analysis with a validation cohort	(1) Utilisation of a large validation group; (2) Sex-stratified analysis; and (3) Pathway enrichment	Biological mechanisms not experimentally tested	Sex-specific KD risk and emphasis for considering sex-biased models for disease susceptibility
Wang et al[44]	CAA vs non-CAA KD	(1) CAA-focused study 2; and (2) Clinical phenotype integration	Small CAA subgroup (n = 15); lacks longitudinal data	The IL17RC (rs143781415) genotype can predispose KD patients to develop CAAs
Nakamura et al[46]	KD + PFAPA overlap	Identification of inflammasome associated variant (CARD8)	Very small sample (n = 3); population frequency similar to controls	CARD8 frameshift variant in KD patients having PFAPA syndrome
Chen et al[21]	KD (n = 330); IVIG resistance	(1) Large cohort-based study; (2) Robust bioinformatics pipeline; and (3) Random forest predictive model for IVIG response in KD	Limited to predefined immune genes; intronic variants are dominant	14 SNPs associated with IVIG responsiveness and IVIG resistance
Amano et al[38]	KD (n = 82)	Pooled genome sequencing with validation identified	Pooled all patient DNA for sequencing, limitation of individual patient’s variant assessment	IL-4/IL4R signaling; potential biomarker for predicting IVIG resistance and coronary artery lesions,
Song et al[39]	KD (n = 190)	Multi-omics integration of targeted sequencing, RNA-seq, eQTL, and cytokine profiling	Limited predefined immune genes, small sample size for transcriptomic analyses, and absence of external validation, and no functional confirmation of identified variants	Dysregulation of T-cell receptor, Toll-like receptor, TGF-β, and cytokine signaling

KD: Kawasaki disease; WES: Whole exome sequencing; WGS: Whole genome sequencing; IVIG: Intravenous immunoglobulin; CAAs: Coronary artery abnormalities; SKAT: Sequence Kernel Association Test; FUMA: Functional Mapping and Annotation; CADD: Combined Annotation Dependent Depletion; PFAPA: Periodic fever, aphthous stomatitis, pharyngitis, and adenitis syndrome; SNP: Single nucleotide polymorphism; eQTL: Expression quantitative trait loci.

DISCUSSION

Limitations

While this review provides a comprehensive synthesis of existing WES and WGS studies in patients with KD, several limitations must be acknowledged. This review is based on a limited number of studies carried out using WGS/WES methods. Most studies are from East Asian and North American populations, which may limit the applicability of their findings across diverse global KD cohorts[22,23,34,35,44]. Also, most studies used small sample sizes in clinical subgroups such as IVIG resistance and CAAs. Moreover, variations in study methodologies, including differences in sequencing platforms, variant-calling pipelines, clinical phenotypes, definitions of IVIG resistance, coronary artery outcomes, and a lack of functional validation, can pose challenges to comparing results across studies. Further, most variants identified in the included studies represent statistical associations or hypothesis-generating candidate findings rather than established causal variants. Therefore, associations between the reported variants and KD susceptibility, coronary artery outcomes, or IVIG response should not be interpreted as proof of causality or as evidence of immediate clinical utility.

Future directions

Future research should focus on analysing large, multi-ethnic populations by integrating findings from genomics, transcriptomics, epigenomics, and proteomics. Integrating multi-omics will provide a more comprehensive understanding of the complex disease mechanisms of KD. Analysis of large-scale, multi-ethnic cohort studies will help validate existing genetic findings and uncover population-specific novel risk variants. Furthermore, functional validation of identified variants using in vitro and in vivo models will help establish causal relationships and biological relevance. Longitudinal studies are needed to assess the predictive value of genetic markers for IVIG resistance and CAAs. The utilisation of artificial intelligence and machine learning models can further enhance CAA and IVIG risk prediction, as well as patient stratification. Genetic factors, along with environmental infectious triggers such as viral and fungal infections, can provide deeper insight into KD pathogenesis. The primary goal of these integrative findings is to contribute to patient care by improving early diagnosis, therapeutic decision-making, enabling precision medicine approaches, and improving long-term cardiovascular outcomes in affected children with KD.

CONCLUSION

Recent advances in NGS have substantially improved the understanding of the genetic underpinnings of KD. In this review, we identified key genes linked to disease susceptibility, CAAs, IVIG resistance, and sex-biased predisposition, based on evidence from WES and WGS studies. The key susceptibility genes included TLR6, MEF2A, IL6ST, MYH14, RBP3, HLA-DRB1, EFCC1, FCRLA, PTGER4, IL17F, and CARD11; many of these are primarily associated with innate and adaptive immune responses.

Variants in IL17RC, FGFR4, IL31RA, FNDC1, MMP8, FOXN1, and VEGFB have been reported to be associated with coronary artery outcomes. The known functions of these genes are consistent with possible involvement of inflammatory signalling, endothelial biology, and vascular remodelling. WGS studies have identified variants in several genes that have been reported to be associated with IVIG response, including FANK1, MAP2K3, KCNJ12, CA10, CWH43, EDN1, PPP2R5E, and SFMBT2. In addition, previously recognised genes ITPKC, CASP3, FCGR2A, CD40, and IL1B are involved in calcium signalling and immune regulation, further confirmed by WES studies.

Overall, these findings indicate that KD is a multifaceted immunovascular disorder involving multiple pathways, namely TLR/NF-κB signalling, IL-17-mediated cytokine pathways, calcium/NFAT signalling, MAPK signalling, and vascular remodelling pathways. Advances in understanding the genetic and environmental factors that regulate disease mechanisms will assist in early diagnosis, risk stratification, and the development of targeted therapies. Nevertheless, larger multicentre studies and functional validation are essential before these genetic findings can be translated into routine clinical practice.