Summary
This methodological paper proposes IGX2, an adaptation of the meta-analytic I2 statistic, to quantify violations of the NO Measurement Error assumption in two-sample Mendelian randomization using MR-Egger regression. Through simulations and real data application, the authors demonstrate that MR-Egger causal estimates are biased towards the null when this assumption is violated, with dilution proportional to the strength of violation. The paper evaluates simulation extrapolation as a corrective approach and demonstrates its utility in mitigating bias.
UK applicability
This is a statistical methods paper with broad applicability to genetic epidemiology research conducted in the United Kingdom and internationally. UK researchers using summary-level genetic data for causal inference would benefit from adopting the IGX2 metric to assess and potentially correct for measurement error bias in their analyses.
Key measures
IGX2 statistic, F-statistic, causal effect estimates, type I error rates, bias in MR-Egger regression, pleiotropy test performance
Outcomes reported
The study evaluated the suitability of the I2-statistic adaptation (IGX2) for quantifying violations of the NO Measurement Error assumption in Mendelian randomization analyses, and assessed the performance of simulation extrapolation as a corrective method.
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