Avoiding bias from weak instruments in Mendelian randomization studies
Avoiding bias from weak instruments in Mendelian randomization studies
复制标题
DOI：
10.1093/ije/dyr036
复制
发表时间：
2011-06-01
影响因子：
7.7
通讯作者：
Thompson, Simon G.
中科院分区：
文献类型：
--
作者：
Burgess, Stephen;Thompson, Simon G.
背景孟德尔随机化被用于通过使用遗传变异作为工具变量（IV）来测试和估计表型对结果的因果效应的大小。IV分析的相关性估计值偏向于表型和结局之间的混杂、观察性相关性。偏倚的大小取决于IV和表型之间关系强度的F统计量。我们寻求制定孟德尔随机化研究设计和分析指南，以最大限度地减少偏差。方法对模拟和真实的数据进行IV分析，以调查研究规模、仪器数量和选择以及分析方法对偏差的影响。结果随着预期F统计量的减少，偏差会增加，并且可以通过使用遗传关联的简约模型（即不过度参数化）和通过调整测量的协变量来减少。使用单个研究的数据，由于仪器选择不当，对数转换的C反应蛋白对纤维蛋白原（μ mol/l）的单位增加的因果估计值从-0.005（P = 0.99）增加至0.792（P = 0.00003）。此外，当在特定研究中观察到的F统计量大于预期时，因果估计更偏向于观察关联，其标准误差更小。因果估计和标准误差之间的这种相关性为孟德尔随机化研究的荟萃分析引入了第二个偏倚来源。通过使用个体水平的数据和合并跨研究的遗传效应，可以减轻荟萃分析中的偏倚。结论弱工具偏倚对于孟德尔随机化研究的设计和分析具有重要的实际意义。事后选择的工具，遗传模型或数据的基础上测量的F-统计量可能会加剧偏见。特别是，通常引用的经验法则F > 10避免IV分析中的偏倚是误导性的。
Background Mendelian randomization is used to test and estimate the magnitude of a causal effect of a phenotype on an outcome by using genetic variants as instrumental variables (IVs). Estimates of association from IV analysis are biased in the direction of the confounded, observational association between phenotype and outcome. The magnitude of the bias depends on the F-statistic for the strength of relationship between IVs and phenotype. We seek to develop guidelines for the design and analysis of Mendelian randomization studies to minimize bias.Methods IV analysis was performed on simulated and real data to investigate the effect on bias of size of study, number and choice of instruments and method of analysis.Results Bias is shown to increase as the expected F-statistic decreases, and can be reduced by using parsimonious models of genetic association (i.e. not over-parameterized) and by adjusting for measured covariates. Using data from a single study, the causal estimate of a unit increase in log-transformed C-reactive protein on fibrinogen (mu mol/l) is shown to increase from -0.005 (P = 0.99) to 0.792 (P = 0.00003) due to injudicious choice of instrument. Moreover, when the observed F-statistic is larger than expected in a particular study, the causal estimate is more biased towards the observational association and its standard error is smaller. This correlation between causal estimate and standard error introduces a second source of bias into meta-analysis of Mendelian randomization studies. Bias can be alleviated in meta-analyses by using individual level data and by pooling genetic effects across studies.Conclusions Weak instrument bias is of practical importance for the design and analysis of Mendelian randomization studies. Post hoc choice of instruments, genetic models or data based on measured F-statistics can exacerbate bias. In particular, the commonly cited rule of thumb that F > 10 avoids bias in IV analysis is misleading.