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Kawasaki disease (KD) is a paediatric vasculitis associated with coronary artery aneurysms (CAA). Genetic variants influencing susceptibility to KD have been previously identified, but no risk alleles have been validated that influence CAA formation. We conducted a genome-wide association study (GWAS) for CAA in KD patients of European descent with 200 cases and 276 controls. A second GWAS for susceptibility pooled KD cases with healthy paediatric controls from vaccine trials in the UK (n = 1609). Logistic regression mixed models were used for both GWASs. The susceptibility GWAS was meta-analysed with 400 KD cases and 6101 controls from a previous European GWAS, these results were further meta-analysed with Japanese GWASs at two putative loci. The CAA GWAS identified an intergenic region of chromosome 20q13 with multiple SNVs showing genome-wide significance. The risk allele of the most associated SNV (rs6017006) was present in 13% of cases and 4% of controls; in East Asian 1000 Genomes data, the allele was absent or rare. Susceptibility GWAS with meta-analysis with previously published European data identified two previously associated loci (ITPKC and FCGR2A). Further meta-analysis with Japanese GWAS summary data from the CASP3 and FAM167A genomic regions validated these loci in Europeans showing consistent effects of the top SNVs in both populations. We identified a novel locus for CAA in KD patients of European descent. The results suggest that different genes determine susceptibility to KD and development of CAA and future work should focus on the function of the intergenic region on chromosome 20q13.

Original publication

DOI

10.1038/s41431-021-00838-5

Type

Journal article

Journal

European journal of human genetics : EJHG

Publication Date

26/03/2021

Addresses

Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK. clivehoggart@gmail.com.

Keywords

International Kawasaki Disease Genetics Consortium, UK Kawasaki Disease Genetics Consortium, EUCLIDS Consortium