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J Allergy Clin Immunol. 2017 Apr;139(4):1148-1157. doi: 10.1016/j.jaci.2016.07.017. Epub 2016 Aug 20.

Gene-based analysis of regulatory variants identifies 4 putative novel asthma risk genes related to nucleotide synthesis and signaling.

Author information

1
QIMR Berghofer Medical Research Institute, Brisbane, Australia. Electronic address: manuel.ferreira@qimrberghofer.edu.au.
2
Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands.
3
Department of Biological Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands.
4
QIMR Berghofer Medical Research Institute, Brisbane, Australia.
5
Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
6
PathWest Laboratory Medicine of Western Australia, Nedlands, Australia; School of Population Health, University of Western Australia, Nedlands, Australia; School of Pathology and Laboratory Medicine, University of Western Australia, Crawley, Australia; Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands, Australia.
7
23andMe Inc, Mountain View, Calif.
8
Institute for Respiratory Health, Harry Perkins Institute of Medical Research, Nedlands, Australia.
9
School of Paediatrics and Child Health, Princess Margaret Hospital for Children, Subiaco, Australia.
10
Respiratory Medicine, Murdoch Children's Research Institute, Melbourne, Australia.
11
Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands, Australia; School of Medicine and Pharmacology, University of Western Australia, Nedlands, Australia; Department of Pulmonary Physiology and Sleep Medicine, West Australian Sleep Disorders Research Institute, Nedlands, Australia.
12
Institute for Respiratory Health, Harry Perkins Institute of Medical Research, Nedlands, Australia; School of Medicine and Pharmacology, University of Western Australia, Nedlands, Australia.
13
School of Biomedical Sciences, University of Queensland, Brisbane, Australia.

Abstract

BACKGROUND:

Hundreds of genetic variants are thought to contribute to variation in asthma risk by modulating gene expression. Methods that increase the power of genome-wide association studies (GWASs) to identify risk-associated variants are needed.

OBJECTIVE:

We sought to develop a method that aggregates the evidence for association with disease risk across expression quantitative trait loci (eQTLs) of a gene and use this approach to identify asthma risk genes.

METHODS:

We developed a gene-based test and software package called EUGENE that (1) is applicable to GWAS summary statistics; (2) considers both cis- and trans-eQTLs; (3) incorporates eQTLs identified in different tissues; and (4) uses simulations to account for multiple testing. We applied this approach to 2 published asthma GWASs (combined n = 46,044) and used mouse studies to provide initial functional insights into 2 genes with novel genetic associations.

RESULTS:

We tested the association between asthma and 17,190 genes that were found to have cis- and/or trans-eQTLs across 16 published eQTL studies. At an empirical FDR of 5%, 48 genes were associated with asthma risk. Of these, for 37, the association was driven by eQTLs located in established risk loci for allergic disease, including 6 genes not previously implicated in disease cause (eg, LIMS1, TINF2, and SAFB). The remaining 11 significant genes represent potential novel genetic associations with asthma. The association with 4 of these replicated in an independent GWAS: B4GALT3, USMG5, P2RY13, and P2RY14, which are genes involved in nucleotide synthesis or nucleotide-dependent cell activation. In mouse studies, P2ry13 and P2ry14-purinergic receptors activated by adenosine 5-diphosphate and UDP-sugars, respectively-were upregulated after allergen challenge, notably in airway epithelial cells, eosinophils, and neutrophils. Intranasal exposure with receptor agonists induced the release of IL-33 and subsequent eosinophil infiltration into the lungs.

CONCLUSION:

We identified novel associations between asthma and eQTLs for 4 genes related to nucleotide synthesis/signaling and demonstrated the power of gene-based analyses of GWASs.

KEYWORDS:

AOAH; CLK3; EUGENE; Inflammation; P2Y13; P2Y14; PrediXcan; TWAS; UDP-glucose; VEGAS; ZNF707; expression quantitative trait locus; obesity; predisposition; transcriptome

PMID:
27554816
PMCID:
PMC5471111
DOI:
10.1016/j.jaci.2016.07.017
[Indexed for MEDLINE]
Free PMC Article

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