Bai Jian-ling, Xun Peng-cheng, Zhao Yang, Yu Hao, Shen Hong-bing, Wei Qing-yi, Chen Feng
Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 210029, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2006 Jan;27(1):72-5.
To introduce the approaches for estimating gene-environment interaction based on partial case-control studies.
The effects of logistic model and log-linear model for estimating the main effects and gene-environment interaction effect were estimated by means of maximum likelihood methods in traditional case-control studies, case-only studies and partial case-control studies, respectively. An example was also illustrated.
In traditional case-control study with complete data, the results of logistic model and log-linear model were equivalent. In case-only study without any information about controls, the logistic model can also efficiently estimate gene-environment interaction. In partial case-control study, environmental information was collected from all of the cases and controls, while genetic information was only collected from cases. For this case-control study with incomplete data, a suitable parameterized log-linear model could simultaneously and efficiently estimate the main effect of environment and gene-environment interaction, whereas the logistic model could not.
For a partial case-control study, log-linear model could estimate not only the main effect of environment but also gene-environment interaction. If genotype and exposure were independent, estimators from partial case-control were as precisely as those from complete-data case-control studies.
介绍基于部分病例对照研究估计基因 - 环境相互作用的方法。
分别采用最大似然法,在传统病例对照研究、病例单组研究和部分病例对照研究中,估计逻辑模型和对数线性模型用于估计主效应和基因 - 环境相互作用效应的效果。并给出了一个实例。
在具有完整数据的传统病例对照研究中,逻辑模型和对数线性模型的结果是等效的。在没有任何对照信息的病例单组研究中,逻辑模型也能有效估计基因 - 环境相互作用。在部分病例对照研究中,环境信息从所有病例和对照中收集,而遗传信息仅从病例中收集。对于这种具有不完整数据的病例对照研究,合适的参数化对数线性模型可以同时有效地估计环境主效应和基因 - 环境相互作用,而逻辑模型则不能。
对于部分病例对照研究,对数线性模型不仅可以估计环境主效应,还可以估计基因 - 环境相互作用。如果基因型和暴露是独立的,部分病例对照研究的估计量与完整数据病例对照研究的估计量一样精确。