Identification of a shared genetic risk locus for Kawasaki disease and immunoglobulin A vasculitis by a cross-phenotype meta-analysis

Objectives Combining of genomic data of different pathologies as a single phenotype has emerged as a useful strategy to identify genetic risk loci shared among immune-mediated diseases. Our study aimed to increase our knowledge of the genetic contribution to Kawasaki disease (KD) and IgA vasculitis (IgAV) by performing the first comprehensive large-scale analysis on the genetic overlap between them. Methods A total of 1190 vasculitis patients and 11 302 healthy controls were analysed. First, in the discovery phase, genome-wide data of 405 KD patients and 6252 controls and 215 IgAV patients and 1324 controls, all of European origin, were combined using an inverse variance meta-analysis. Second, the top associated polymorphisms were selected for replication in additional independent cohorts (570 cases and 3726 controls). Polymorphisms with P-values <= 5 x 10(-8) in the global IgAV-KD meta-analysis were considered as shared genetic risk loci. Results A genetic variant, rs3743841, located in an intron of the NAGPA gene, reached genome-wide significance in the cross-disease meta-analysis (P = 8.06 x 10(-10)). Additionally, when IgAV was individually analysed, a strong association between rs3743841 and this vasculitis was also evident [P = 1.25 x 10(-7); odds ratio = 1.47 (95% CI 1.27, 1.69)]. In silico functional annotation showed that this polymorphism acts as a regulatory variant modulating the expression levels of the NAGPA and SEC14L5 genes. Conclusion We identified a new risk locus with pleiotropic effects on the two childhood vasculitides analysed. This locus represents the strongest non-HLA signal described for IgAV to date.

Automated summary

This study aimed to increase knowledge on the genetic contribution to Kawasaki disease (KD) and IgA vasculitis (IgAV) by performing a comprehensive large-scale analysis on the genetic overlap between them. A new risk locus with pleiotropic effects on the two childhood vasculitides analyzed was identified, representing the strongest non-HLA signal described for IgAV to date.