Woolf et al’s “GWAS by subtraction” is not useful for cross-generational Mendelian randomization studies

TL;DR

This paper argues that the 'GWAS by subtraction' method proposed by Woolf et al. is not suitable for studying causal relationships between parental traits and offspring outcomes.

Contribution

The paper identifies critical flaws in the 'GWAS by subtraction' method for cross-generational Mendelian randomization.

Findings

The method focuses on the wrong parameter for genome-wide association studies.

The estimator derived is inefficient and inappropriate for downstream MR studies.

Abstract

Mendelian randomization (MR) is an epidemiological method that can be used to strengthen causal inference regarding the relationship between a modifiable environmental exposure and a medically relevant trait and to estimate the magnitude of this relationship [1]. Recently, there has been considerable interest in using MR to examine potential causal relationships between parental phenotypes and outcomes amongst their offspring [2–4] (interestingly one of the earliest exemplars of MR was confirmation that antenatal maternal folate was protective against offspring neural tube defects [1]). In a recent issue of BMC Research Notes, Woolf, Sallis, Munafo and Gill (2023) [5] (abbreviated as WSMG from now on) present a method they call “GWAS by subtraction” (not to be confused with GWAS by subtraction via genomic SEM [6, 7]), to derive genome-wide summary statistics for paternal smoking and other “paternal phenotypes” with the goal that these estimates can then be used in downstream (including two sample) MR studies [8]. Whilst a potentially useful goal, WSMG (2023) focus on the wrong parameter of interest for useful genome-wide association studies (GWAS) and downstream cross-generational MR studies, and the estimator that they derive is neither efficient nor appropriate for such use.