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

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

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  • 1Biostatistics Center and Graduate Institute of Biostatistics, China Medical University, Taichung, Taiwan. kfcheng@mail.cmu.edu.tw

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.

[PubMed - indexed for MEDLINE]
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