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

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.

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.