Population stratification in epidemiologic studies of common genetic variants and cancer: Quantification of bias
Population stratification in epidemiologic studies of common genetic variants and cancer: Quantification of bias
复制标题
DOI：
10.1093/jnci/92.14.1151
复制
发表时间：
2000-07-19
期刊：
影响因子：
--
通讯作者：
Caporaso, N
中科院分区：
文献类型：
--
作者：
Wacholder, S;Rothman, N;Caporaso, N
背景资料：一些批评者认为，来自人群分层（来自异质遗传背景的个体的混合）的偏见破坏了旨在估计基因型与疾病风险之间关联的流行病学研究的可信度。我们调查了在美国对欧洲血统的非西班牙裔高加索人癌症研究中可能来自人群分层的偏倚程度。研究方法：混杂风险比的表达-遗传因素对疾病风险的影响与种族校正和不校正的比率-被用来衡量潜在的相对偏差，从人口分层。我们首先使用经验数据的N-乙酰转移酶（NAT 2）慢乙酰化基因型的频率和男性膀胱癌和女性乳腺癌的发病率在非西班牙裔美国，高加索人的祖先来自8个欧洲国家，以评估在一个假设的人口为基础的美国研究，不考虑种族的偏见。然后，我们提供了理论计算的偏差在一个大范围的等位基因频率和疾病率。结果：在我们的NAT 2实证研究中，忽略种族会导致1%或更少的偏倚。此外，对欧洲人群中广泛的等位基因频率和癌症发病率代表性范围的评估表明，在美国研究中，风险比的偏倚小于10%，除非在极端条件下。我们注意到，随着种族阶层数量的增加，这种偏见会减少。结论：在一项设计良好的遗传因素病例对照研究中，忽略了欧洲血统的非西班牙裔美国高加索人的种族，只有一个很小的人群分层偏倚。需要进一步开展工作，以估计人口分层在其他人口中的影响。
Background: Some critics argue that bias from population stratification (the mixture of individuals from heterogeneous genetic backgrounds) undermines the credibility of epidemiologic studies designed to estimate the association between a genotype and the risk of disease. We investigated the degree of bias likely from population stratification in U.S. studies of cancer among non-Hispanic Caucasians of European origin. Methods: An expression of the confounding risk ratio-the ratio of the effect of the genetic factor on risk of disease with and without adjustment for ethnicity-is used to measure the potential relative bias from population stratification. We first use empirical data on the frequency of the N-acetyltransferase (NAT2) slow acetylation genotype and incidence rates of male bladder cancer and female breast cancer in non-Hispanic U.S, Caucasians with ancestries from eight European countries to assess the bias in a hypothetical population-based U.S. study that does not take ethnicity into consideration. Then, we provide theoretical calculations of the bias over a large range of allele frequencies and disease rates. Results: Ignoring ethnicity leads to a bias of 1% or less in our empirical studies of NAT2. Furthermore, evaluation of a wide range of allele frequencies and representative ranges of cancer rates that exist across European populations shows that the risk ratio is biased by less than 10% in U.S. studies except under extreme conditions. We note that the bias decreases as the number of ethnic strata increases. Conclusions: There will be only a small bias from population stratification in a well-designed case-control study of genetic factors that ignores ethnicity among non-Hispanic U.S. Caucasians of European origin. Further work is needed to estimate the effect of population stratification within other populations.