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Comparative Study
. 2011 Jun;40(3):740-52.
doi: 10.1093/ije/dyq151. Epub 2010 Sep 2.

Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants

Brandon L Pierce  1 , Habibul Ahsan, Tyler J Vanderweele
Affiliations
Comparative Study

Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants

Brandon L Pierce et al. Int J Epidemiol. 2011 Jun.

Abstract

Background: Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored.

Methods: We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic.

Results: Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure.

Conclusions: The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.

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Figures

Figure 1
Figure 1
Causal diagram for a Mendelian randomization study using (a) a single instrumental variable, (b) multiple, independent instrumental variables (c) a single combined instrumental variable and (d) a major gene and polygene instrumental variables
Figure 2
Figure 2
Relationship between F and R2 for varying sample sizes and number of instrumental variables. The F thresholds from Stock et al., are shown as horizontal lines
See this image and copyright information in PMC

Comment in

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