Abstract

BackgroundCandidate gene and genome-wide association studies have identified hundreds of asthma risk loci. The majority of associated variants, however, are not known to have any biological function and are believed to represent markers rather than true causative mutations. We hypothesized that many of these associated markers are in linkage disequilibrium (LD) with the elusive causative variants.MethodsWe compiled a comprehensive list of 449 asthma-associated variants previously reported in candidate gene and genome-wide association studies. Next, we identified all sequence variants located within the 305 unique genes using whole-genome sequencing data from the 1000 Genomes Project. Then, we calculated the LD between known asthma variants and the sequence variants within each gene. LD variants identified were then annotated to determine those that are potentially deleterious and/or functional (i.e. coding or regulatory effects on the encoded transcript or protein).ResultsWe identified 10,130 variants in LD (r2 > 0.6) with known asthma variants. Annotations of these LD variants revealed that several have potentially deleterious effects including frameshift, alternate splice site, stop-lost, and missense. Moreover, 24 of the LD variants have been reported to regulate gene expression as expression quantitative trait loci (eQTLs).ConclusionsThis study is proof of concept that many of the genetic loci previously associated with complex diseases such as asthma are not causative but represent markers of disease, which are in LD with the elusive causative variants. We hereby report a number of potentially deleterious and regulatory variants that are in LD with the reported asthma loci. These reported LD variants could account for the original association signals with asthma and represent the true causative mutations at these loci.

Highlights

  • Candidate gene and genome-wide association studies have identified hundreds of asthma risk loci

  • Asthma loci We identified a total of 449 asthma-associated Single nucleotide polymorphism (SNP) from earlier genome-wide association studies (GWAS) and candidate gene studies

  • We identified loci reported by candidate gene studies, of which 224 SNPs did not overlap with GWAS loci and mapped to 81 unique genes (Additional file 1: Table S2)

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Summary

Introduction

Candidate gene and genome-wide association studies have identified hundreds of asthma risk loci. It is widely accepted that the majority of loci identified from genome-wide association studies (GWAS) as well as candidate gene studies are not causal but are genetic markers that tag causal variants [8]. This is supported by the fact that the majority of variants associated with complex diseases such as asthma have no known impact on the resulting transcripts or proteins, with over 80% from GWAS falling outside of protein coding regions [9]. Discovery of the causal variants underlying a disease would reveal the true genetic effect sizes [8] and help to facilitate the development of more accurate clinical tests for diagnosis and treatment of asthma [10]

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