Population structure, differential bias and genomic control in a large-scale, case-control association study
Population structure, differential bias and genomic control in a large-scale, case-control association study
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DOI：
10.1038/ng1653
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发表时间：
2005-11-01
期刊：
影响因子：
30.8
通讯作者：
Todd, JA
中科院分区：
文献类型：
--
作者：
Clayton, DG;Walker, NM;Todd, JA
从流行病学病例对照研究中得出因果推论的主要问题是未测量的外来因素造成的混杂、选择偏倚以及暴露的差异性错误分类(1)。在遗传学中，这些问题中的第一个，即群体结构形式的问题，在近期的争论中占主导地位(2 - 4)。在对来自英国的816例1型糖尿病患者和877例基于人群的对照的6322个非同义单核苷酸多态性（SNP）进行分析时，我们观察到检验统计量显著膨胀了 +11.2%，群体结构解释了部分膨胀原因。其余的膨胀是由于病例和对照DNA样本之间基因型评分的差异性偏倚造成的，这些样本来自两个实验室，导致了假阳性关联。为了避免排除SNP并丢失有价值的信息，我们通过对每个SNP应用可变的降权扩展了基因组控制方法(2 - 5)。
The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure(1). In genetics the first of these, in the form of population structure, has dominated recent debate(2-4). Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method(2-5) by applying a variable downweighting to each SNP.