Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome

By F. Greco M, Cosetta Minelli, Nuala Sheehan, J. Thompson. Statistics in Medicine, 2015

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In Genetics

Citations in the corpus

Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator (2016, methodology): “Heterogeneity between estimates can be quantified by Cochran’s Q statistic: Q = ∑ j Q j = ∑ j w ′j (β̂j – β̂) 2, where we take β̂ to be the IVW estimate (Greco et al., 2015).”
A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization (2017, methodology): “As suggested by Del Greco et al [16], the data can be scrutinised to assess this assumption by calculating Cochran’s Q statistic with respect to the L IV estimates as follows: Q = L∑ j=1 ( Γ̂j 𝜎Yj − 𝛽IVW𝛾j 𝜎Yj )2 = L∑ j=1 wj(𝛽j − 𝛽IVW)2.”
Meta‐analysis and Mendelian randomization: A review (2019, methodology): “which is identical to the Sargan overidentification test used in econometrics.(15) If Q detects substantial heterogeneity among the causal estimates, which cannot be explained by sampling variation alone, then an extension to the basic model is required.”
Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption (2017, methodology): “horizontal pleiotropy (under the assumption that this is the only source of heterogeneity between s other than chance).(15) All simulations and analyses were performed using R 3.”
Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression (2018, positive): “Del Greco et al.(10) first proposed the use of Cochran’s Q to detect pleiotropy in a MR context.”
Evaluating the potential role of pleiotropy in Mendelian randomization studies (2018, background): “between studies is Cochran’s Q statistic (49), and it can also be applied in the MR context (50,51).”
Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians (2018, background): “67 68 If these test statistics are large (yielding correspondingly small P values), the estimated causal effects of the risk factor may vary across the population or between variants.”
Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods (2015, methodology): “An overidentification test can be performed by considering the ratio estimates from each IV individually and performing a heterogeneity test, such as Cochran’s Q test [49].”