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Defining the contribution of SNPs identified in asthma GWAS to clinical variables in asthmatic children

Asif S Tulah13, John W Holloway2 and Ian Sayers1*

Author Affiliations

1 Division of Respiratory Medicine, Queen’s Medical Centre, University of Nottingham, Nottingham NG7 2UH, United Kingdom

2 Human Genetics and Medical Genomics, Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK

3 Institute of Cellular Medicine, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK

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BMC Medical Genetics 2013, 14:100  doi:10.1186/1471-2350-14-100

Published: 25 September 2013



Asthma genome-wide association studies (GWAS) have identified several asthma susceptibility genes with confidence; however the relative contribution of these genetic variants or single nucleotide polymorphisms (SNPs) to clinical endpoints (as opposed to disease diagnosis) remains largely unknown. Thus the aim of this study was to firstly bridge this gap in knowledge and secondly investigate whether these SNPs or those that are in linkage disequilibrium are likely to be functional candidates with respect to regulation of gene expression, using reported data from the ENCODE project.


Eleven of the key SNPs identified in eight loci from recent asthma GWAS were evaluated for association with asthma and clinical outcomes, including percent predicted FEV1, bronchial hyperresponsiveness (BHR) to methacholine, severity defined by British Thoracic Society steps and positive response to skin prick test, using the family based association test additive model in a well characterised UK cohort consisting of 370 families with at least two asthmatic children.


GSDMB SNP rs2305480 (Ser311Pro) was associated with asthma diagnosis (p = 8.9×10-4), BHR (p = 8.2×10-4) and severity (p = 1.5×10-4) with supporting evidence from a second GSDMB SNP rs11078927 (intronic). SNPs evaluated in IL33, IL18R1, IL1RL1, SMAD3, IL2RB, PDE4D, CRB1 and RAD50 did not show association with any phenotype tested when corrected for multiple testing. Analysis using ENCODE data provides further insight into the functional relevance of these SNPs.


Our results provide further support for the role of GSDMB SNPs in determining multiple asthma related phenotypes in childhood asthma including associations with lung function and disease severity.

Asthma; ENCODE; eQTL; GWAS; Clinical endpoints