Positionally cloned asthma susceptibility gene polymorphisms and disease risk in the British 1958 Birth Cohort
Positionally cloned asthma susceptibility gene polymorphisms and disease risk in the British 1958 Birth Cohort
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DOI：
10.1136/thx.2008.102053
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发表时间：
2009-05-01
期刊：
影响因子：
10
通讯作者：
Hall, I. P.
中科院分区：
文献类型：
--
作者：
Blakey, J. D.;Sayers, I.;Hall, I. P.
目的：本研究的目的是在一个具有全国代表性的大型人群中，评估定位克隆的哮喘候选基因ADAM 33、PHF 11、DPP 10、GPRA和PTGDR多态性对哮喘风险、总免疫球蛋白E水平和特异性免疫球蛋白E水平、肺功能和喘息的贡献。使用标记基因型数据和先前相关的单核苷酸多态性（SNPs）进行关联分析这些基因的区域和纵向表型数据来自英国1958年出生队列DNA档案中的白色种族的单例（n=7703）。人群归因于风险分数的SNPs显示associationwere calculated.Results：多态性产生小，但统计学上显着增加哮喘的风险（OR 1.1每等位基因）被确定在DPP 10和ADAM 33，最有力的证据是SNP标记的DPP 10基因。没有个别SNP在任何基因的研究显着增加风险的任何表型在populationstudyed.Conclusions：这些数据表明，DPP 10和ADAM 33影响哮喘的风险在英国人口。然而，由任何给定的基因座驱动的影响是小的，并且需要对许多基因中的多个多态性进行基因分型以定义疾病风险的完整遗传谱。
Objective: The aim of this study was 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: An association analysis was undertaken 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). Population-attributable risk fractions for SNPs showing association were calculated.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 SNPs tagging the DPP10 gene. 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.