一项大规模病例对照关联研究中的群体结构、差异偏倚与基因组控制

Population structure, differential bias and genomic control in a large-scale, case-control association study.

作者信息

Clayton David G, Walker Neil M, Smyth Deborah J, Pask Rebecca, Cooper Jason D, Maier Lisa M, Smink Luc J, Lam Alex C, Ovington Nigel R, Stevens Helen E, Nutland Sarah, Howson Joanna M M, Faham Malek, Moorhead Martin, Jones Hywel B, Falkowski Matthew, Hardenbol Paul, Willis Thomas D, Todd John A

机构信息

Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, University of Cambridge, Cambridge Institute for Medical Research, Wellcome Trust/MRC Building, Cambridge, CB2 2XY, UK.

出版信息

Nat Genet. 2005 Nov;37(11):1243-6. doi: 10.1038/ng1653. Epub 2005 Oct 9.

DOI:10.1038/ng1653

PMID:16228001

Abstract

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. In genetics the first of these, in the form of population structure, has dominated recent debate. 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 by applying a variable downweighting to each SNP.

摘要

从流行病学病例对照研究中得出因果推断的主要问题是未测量的外部因素导致的混杂、选择偏倚以及暴露的差异性错误分类。在遗传学中，其中第一个问题，以群体结构的形式，主导了最近的讨论。群体结构解释了我们在对来自英国的816例1型糖尿病病例和877例基于人群的对照中的6322个非同义单核苷酸多态性（SNP）进行分析时观察到的测试统计量显著的+11.2%膨胀的部分原因。膨胀的其余部分是由于来自两个实验室的病例和对照DNA样本之间基因型评分的差异偏差，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应用可变的权重降低来扩展基因组控制方法。