Association of asthma genetic variants with asthma‐associated traits reveals molecular pathways of eosinophilic asthma

Abstract

Abstract Introduction Asthma is a complex, polygenic, heterogenous inflammatory disease. Recently, we generated a list of 128 independent single nucleotide polymorphisms (SNPs) associated with asthma in genome‐wide association studies. However, it is unknown if asthma SNPs are associated with specific asthma‐associated traits such as high eosinophil counts, atopy, and airway obstruction, revealing molecular endotypes of this disease. Here, we aim to identify the association between asthma SNPs and asthma‐associated traits and assess expression quantitative trait locus (e‐QTLs) to reveal their downstream functional effects and find drug targets. Methods Association analyses between 128 asthma SNPs and associated traits (blood eosinophil numbers, atopy, airway obstruction, airway hyperresponsiveness) were conducted using regression modelling in population‐based studies (Lifelines N = 32,817/Vlagtwedde‐Vlaardingen N = 1554) and an asthma cohort (Dutch Asthma genome‐wide association study N = 917). Functional enrichment and pathway analysis were performed with genes linked to the significant SNPs by e‐QTL analysis. Genes were investigated to generate novel drug targets. Results We identified 69 asthma SNPs that were associated with at least one trait, with 20 SNPs being associated with multiple traits. The SNP annotated to SMAD3 was the most pleiotropic. In total, 42 SNPs were associated with eosinophil counts, 18 SNPs with airway obstruction, and 21 SNPs with atopy. We identified genetically driven pathways regulating eosinophilia. The largest network of eosinophilia contained two genes (IL4R, TSLP) targeted by drugs currently available for eosinophilic asthma. Several novel targets were identified such as IL‐18, CCR4, and calcineurin. Conclusion Many asthma SNPs are associated with blood eosinophil counts and genetically driven molecular pathways of asthma‐associated traits were identified.

Keywords

• asthma heterogeneity
• endotype
• genome wide association
• phenotype
• single nucleotide polymorphism