A novel role for ciliary function in atopy:ADGRV1andDNAH5interactions

    loading  Checking for direct PDF access through Ovid

Abstract

Background

Atopy, an endotype underlying allergic diseases, has a substantial genetic component.

Objective

Our goal was to identify novel genes associated with atopy in asthma-ascertained families.

Methods

We implemented a 3-step analysis strategy in 3 data sets: the Epidemiological Study on the Genetics and Environment of Asthma (EGEA) data set (1660 subjects), the Saguenay-Lac-Saint-Jean study data set (1138 subjects), and the Medical Research Council (MRC) data set (446 subjects). This strategy included a single nucleotide polymorphism (SNP) genome-wide association study (GWAS), the selection of related gene pairs based on statistical filtering of GWAS results, and text-mining filtering using Gene Relationships Across Implicated Loci and SNP-SNP interaction analysis of selected gene pairs.

Results

We identified the 5q14 locus, harboring the adhesion G protein–coupled receptor V1 (ADGRV1) gene, which showed genome-wide significant association with atopy (rs4916831, meta-analysis P value = 6.8 × 10−9). Statistical filtering of GWAS results followed by text-mining filtering revealed relationships between ADGRV1 and 3 genes showing suggestive association with atopy (P ≤ 10−4). SNP-SNP interaction analysis between ADGRV1 and these 3 genes showed significant interaction between ADGRV1 rs17554723 and 2 correlated SNPs (rs2134256 and rs1354187) within the dynein axonemal heavy chain 5 (DNAH5) gene (Pmeta-int = 3.6 × 10−5 and 6.1 × 10−5, which met the multiple-testing corrected threshold of 7.3 × 10−5). Further conditional analysis indicated that rs2134256 alone accounted for the interaction signal with rs17554723.

Conclusion

Because both DNAH5 and ADGRV1 contribute to ciliary function, this study suggests that ciliary dysfunction might represent a novel mechanism underlying atopy. Combining GWAS and epistasis analysis driven by statistical and knowledge-based evidence represents a promising approach for identifying new genes involved in complex traits.

Related Topics

    loading  Loading Related Articles