Article Text

other Versions

PDF

Positionally cloned Asthma susceptibility gene polymorphisms and disease risk in the British 1958 Birth Cohort
  1. John D Blakey (john.blakey{at}nottingham.ac.uk)
  1. University of Nottingham, United Kingdom
    1. Ian Sayers (ian.sayers{at}nottingham.ac.uk)
    1. University of Nottingham, United Kingdom
      1. Susan Ring
      1. Department of Community Based Medicine, University of Bristol, United Kingdom
        1. David Strachan
        1. Division of Community Health Sciences, St George’s Hospital, University of London, United Kingdom
          1. Ian Hall (ian.hall{at}nottingham.ac.uk)
          1. University of Nottingham, United Kingdom

            Abstract

            Objective: We set out to estimate the contribution of polymorphisms in the positionally-cloned asthma candidate genes ADAM33, PHF11, DPP10, GPRA and PTGDR to the risk of asthma, total and specific immunoglobulin E level, lung function and wheezing in a large, nationally representative, population.

            Methods: We undertook an association analysis using genotype data for tagging and previously associated single nucleotide polymorphisms (SNPs) in regions of these genes and longitudinal phenotype data from singletons of white ethnicity in the British 1958 Birth Cohort DNA archive (n=7703), and calculated population attributable risk fractions for SNPs showing association.

            Results: Polymorphisms producing small but statistically significant increases in asthma risk (OR 1.1 per allele) were identified in DPP10 and ADAM33, with the strongest evidence being for single nucleotide polymorphisms (SNPs) tagging the gene for DPP10. No individual SNP in any gene under study markedly increased risk for any of the phenotypes in the population studied.

            Conclusions: These data suggest that DPP10 and ADAM33 influence asthma risk in the UK population. However, the effects driven by any given locus are small and genotyping of multiple polymorphisms in many genes will be needed to define a full genetic profile for disease risk.

            Statistics from Altmetric.com

            Request permissions

            If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

            Linked Articles

            • Editorial
              Michael Kabesch