利用哈代-温伯格不平衡系数检验配对病例对照数据的关联性(英文)

Testing genetic association in pair-matched case-control design by incorporating Hardy-Weinberg disequilibrium

针对配对的病例对照数据,利用偏离哈代-温伯格平衡的信息构造了用于估计基因模型的检验,称为配对的哈代-温伯格不平衡检验(mHWD).基于mHWD估计基因模型并应用相应的配对趋势检验进行关联性分析,称为基于模型选择的趋势检验(GMS).GMS是从数据驱动的角度提出的一种稳健有效的检验,模拟结果显示GMS在现有的关联性检验方法中具有最大的稳健有效性.对类肉样瘤病研究数据的分析进一步表明了基于模型选择的趋势检验的良好性质.

The matched case-control design is widely used in genetic association studies to control potential confounding variables.A commonly used method for analyzing such data is the Mantel-Haenszel(MH)test which can be derived as the score test of a conditional logistic regression model and may not be powerful when the genetic model is mispecified.Trend test incorporating the underlying genetic model is known to be more powerful than the MH test.However,in the practice,the genetic model is usually unknown to the researchers.To circumvent this issue and to retain power of the trend test,MAX-type test that takes the maximum of the typical trend tests was proposed,which was shown to be robust efficient.Here another robust efficient method was proposed by incorporating information of deviation from Hardy-Weinberg equilibrium,which is referred to as the matched Hardy-Weinberg disequilibrium test(mHWD).Our method uses the trend test as the association test but the score of which is determined by the information from mHWD.In this sense,the proposed procedure is a data-driven trend test method.The critical values and p-values of the proposed test can be easily obtained using simple Monte-Carlo methods.Simulation studies show that the proposed test exhibits greater efficiency robustness than the existing tests across a class of scientifically plausible genetic models.The proposed method is illustrated by analyzing a real data set in sarcoidosis study.