Wang Liang-Yi, Lee Wen-Chung
Research Center for Genes, Environment, and Human Health and the Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei, Taiwan, Republic of China.
Am J Epidemiol. 2008 Jul 15;168(2):197-201. doi: 10.1093/aje/kwn130. Epub 2008 May 22.
The case-only study is a convenient approach and provides increased statistical efficiency in detecting gene-environment interactions. The validity of a case-only study hinges on one well-recognized assumption: The susceptibility genotypes and the environmental exposures of interest are independent in the population. Otherwise, the study will be biased. The authors show that hidden stratification in the study population could also ruin a case-only study. They derive the formulas for population stratification bias. The bias involves three terms: 1) the coefficient of variation of the exposure prevalence odds, 2) the coefficient of variation of the genotype frequency odds, and 3) the correlation coefficient between the exposure prevalence odds and the genotype frequency odds. The authors perform simulation to investigate the magnitude of bias over a wide range of realistic scenarios. It is found that the estimated interaction effect is frequently biased by more than 5%. For a rarer gene and a rarer exposure, the bias becomes even larger (>30%). Because of the potentially large bias, researchers conducting case-only studies should use the boundary formula presented in this paper to make more prudent interpretations of their results, or they should use stratified analysis or a modeling approach to adjust for population stratification bias in their studies.
病例对照研究是一种便捷的方法,在检测基因-环境相互作用方面具有更高的统计效率。病例对照研究的有效性取决于一个广为人知的假设:在总体人群中,易感性基因型与感兴趣的环境暴露是独立的。否则,该研究会产生偏差。作者表明,研究人群中的隐藏分层也可能破坏病例对照研究。他们推导了人群分层偏差的公式。该偏差涉及三个项:1)暴露患病率比值的变异系数,2)基因型频率比值的变异系数,以及3)暴露患病率比值与基因型频率比值之间的相关系数。作者进行了模拟,以研究在广泛的现实场景中的偏差程度。结果发现,估计的交互作用效应经常偏差超过5%。对于更罕见的基因和更罕见的暴露,偏差会变得更大(>30%)。由于可能存在较大偏差,进行病例对照研究的研究人员应使用本文给出的边界公式对其结果进行更谨慎的解释,或者他们应使用分层分析或建模方法来调整研究中的人群分层偏差。