For elucidating the
Mendelian randomization (MR) is an epidemiological method that was developed to estimate the causal effect of environmental exposures on medically relevant outcomes.
The residual error terms for the birthweight of the individual and their offspring are represented by Structural equation model (SEM) used to estimate maternal and offspring genetic effects on birthweight.
However, a problem with this simple approach is that there is a paucity of cohorts worldwide with genome-wide association study (GWAS) data on both mothers and their offspring.
Additionally, loci influencing complex traits in the offspring are typically of small effect and, since maternal and offspring genotypes are highly correlated, power is often low to definitively partition genetic effects into maternal and offspring components.
We discuss how this partitioning could be used to facilitate large-scale two-sample MR studies of maternal exposures and offspring outcomes in different samples of individuals, maximizing sample size and obviating the requirement of individual-level genotyped mother–offspring pairs.
Within this context, we show how the recent identification of genetic loci that exert maternal effects on offspring birthweight exposures related to fetal growth on offspring outcomes using this method.
There is considerable interest in estimating the causal effect of a range of maternal environmental exposures on offspring health-related outcomes.