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评估基因-基因(环境)相互作用研究中群体分层和样本选择的联合效应。

Assessing the joint effect of population stratification and sample selection in studies of gene-gene (environment) interactions.

机构信息

Biostatistics Center and Graduate Institute of Biostatistics, China Medical University, Taichung, Taiwan.

出版信息

BMC Genet. 2012 Jan 27;13:5. doi: 10.1186/1471-2156-13-5.

Abstract

BACKGROUND

It is well known that the presence of population stratification (PS) may cause the usual test in case-control studies to produce spurious gene-disease associations. However, the impact of the PS and sample selection (SS) is less known. In this paper, we provide a systematic study of the joint effect of PS and SS under a more general risk model containing genetic and environmental factors. We provide simulation results to show the magnitude of the bias and its impact on type I error rate of the usual chi-square test under a wide range of PS level and selection bias.

RESULTS

The biases to the estimation of main and interaction effect are quantified and then their bounds derived. The estimated bounds can be used to compute conservative p-values for the association test. If the conservative p-value is smaller than the significance level, we can safely claim that the association test is significant regardless of the presence of PS or not, or if there is any selection bias. We also identify conditions for the null bias. The bias depends on the allele frequencies, exposure rates, gene-environment odds ratios and disease risks across subpopulations and the sampling of the cases and controls.

CONCLUSION

Our results show that the bias cannot be ignored even the case and control data were matched in ethnicity. A real example is given to illustrate application of the conservative p-value. These results are useful to the genetic association studies of main and interaction effects.

摘要

背景

众所周知,人群分层(PS)的存在可能导致病例对照研究中的常规检验产生虚假的基因-疾病关联。然而,PS 和样本选择(SS)的影响知之甚少。本文在包含遗传和环境因素的更一般风险模型下,对 PS 和 SS 的联合效应进行了系统研究。我们提供了模拟结果,以显示在广泛的 PS 水平和选择偏差下,通常的卡方检验的偏倚程度及其对Ⅰ型错误率的影响。

结果

量化了主效应和交互作用估计的偏差,并推导出了它们的界。估计的界可用于计算关联检验的保守 p 值。如果保守的 p 值小于显著水平,那么无论是否存在 PS 或存在任何选择偏差,我们都可以安全地声称关联检验是显著的。我们还确定了零假设偏差的条件。偏差取决于亚群中的等位基因频率、暴露率、基因-环境比值和疾病风险,以及病例和对照的抽样。

结论

即使病例和对照数据在种族上匹配,我们的结果也表明偏倚不能被忽略。给出了一个实际的例子来说明保守 p 值的应用。这些结果对主效应和交互作用的遗传关联研究很有用。

相似文献

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Studying the joint effects of population stratification and sampling in case-control association studies.
Hum Hered. 2010;69(4):254-61. doi: 10.1159/000297658. Epub 2010 Mar 29.
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Environmental confounding in gene-environment interaction studies.基因-环境交互作用研究中的环境混杂。
Am J Epidemiol. 2013 Jul 1;178(1):144-52. doi: 10.1093/aje/kws439. Epub 2013 May 21.

本文引用的文献

1
Studying the joint effects of population stratification and sampling in case-control association studies.
Hum Hered. 2010;69(4):254-61. doi: 10.1159/000297658. Epub 2010 Mar 29.
8
Demonstrating stratification in a European American population.在欧美人群中显示分层情况。
Nat Genet. 2005 Aug;37(8):868-72. doi: 10.1038/ng1607. Epub 2005 Jul 24.

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