Factorial Mendelian randomization: using genetic variants to assess interactions

Abstract

BackgroundFactorial Mendelian randomization is the use of genetic variants to answer questions about interactions. Although the approach has been used in applied investigations, little methodological advice is available on how to design or perform a factorial Mendelian randomization analysis. Previous analyses have employed a 2 x 2 approach, using dichotomized genetic scores to divide the population into 4 subgroups as in a factorial randomized trial. MethodsWe describe two distinct contexts for factorial Mendelian randomization: investigating interactions between risk factors, and investigating interactions between pharmacological interventions on risk factors. We propose two-stage least squares methods using all available genetic variants and their interactions as instrumental variables, and using continuous genetic scores as instrumental variables rather than dichotomized scores. We illustrate our methods using data from UK Biobank to investigate the interaction between body mass index and alcohol consumption on systolic blood pressure. ResultsSimulated and real data show that efficiency is maximized using the full set of interactions between genetic variants as instruments. In the applied example, between four- and ten-fold improvement in efficiency is demonstrated over the 2 x 2 approach. Analyses using continuous genetic scores are more efficient than those using dichotomized scores. Efficiency is improved by finding genetic variants that divide the population at a natural break in the distribution of the risk factor, or else divide the population into more equal sized groups. ConclusionsPrevious factorial Mendelian randomization analyses may have been under-powered. Efficiency can be improved by using all genetic variants and their interactions as instrumental variables, rather than the 2 x 2 approach. Key messagesO_LIFactorial Mendelian randomization is an extension of the Mendelian randomization paradigm to answer questions about interactions. C_LIO_LIThere are two contexts in which factorial Mendelian randomization can be used: for investigating interactions between risk factors, and interactions between pharmacological interventions on risk factors. C_LIO_LIWhile most applications of factorial Mendelian randomization have dichotomized the population as in a 2 x 2 factorial randomized trial, this approach is generally inefficient for detecting statistical interactions. C_LIO_LIIn the first context, efficiency is maximized by including all genetic variants and their cross-terms as instrumental variables for the two risk factors and their product term. C_LIO_LIIn the second context, efficiency is maximized by using continuous genetic scores rather than dichotomized scores. C_LI