Mendelian randomization in health research: Using appropriate genetic variants and avoiding biased estimates
说明若研究者根据自身数据中遗传变异与暴露的关联来选择变异，会导致孟德尔随机化结果出现虚假因果，并讨论了暴露测量不准时的估计偏倚，对烟草研究有具体参考。
Mendelian randomization methods, which use genetic variants as instrumental variables for exposures of interest to overcome problems of confounding and reverse causality, are becoming widespread for assessing causal relationships in epidemiological studies. The main purpose of this paper is to demonstrate how results can be biased if researchers select genetic variants on the basis of their association with the exposure in their own dataset, as often happens in candidate gene analyses. This can lead to estimates that indicate apparent "causal" relationships, despite there being no true effect of the exposure. In addition, we discuss the potential bias in estimates of magnitudes of effect from Mendelian randomization analyses when the measured exposure is a poor proxy for the true underlying exposure. We illustrate these points with specific reference to tobacco research.