PheWAS-based clustering of Mendelian Randomisation instruments reveals distinct mechanism-specific causal effects between obesity and educational attainment

Abstract

Mendelian Randomisation (MR) estimates causal effects between risk factors and complex outcomes using genetic instruments. Pleiotropy, heritable confounders, and heterogeneous causal effects violate MR assumptions and can lead to biases. To alleviate these, we propose an approach employing a Phenome-Wide association Clustering of the MR instruments (PWC-MR) and apply this method to revisit the surprisingly large apparent causal effect of body mass index (BMI) on educational attainment (EDU): $$\widehat{\alpha }$$ α ̂ = −0.19 [−0.22, −0.16]. First, we cluster 324 BMI-associated genetic instruments based on their association with 407 traits in the UK Biobank, which yields six distinct groups. Subsequent cluster-specific MR reveals heterogeneous causal effect estimates on EDU. A cluster enriched for socio-economic indicators yields the largest BMI-on-EDU causal effect estimate ($$\widehat{\alpha }$$ α ̂ = −0.49 [−0.56, −0.42]) whereas a cluster enriched for body-mass specific traits provides a more likely estimate ($$\widehat{\alpha }$$ α ̂ = −0.09 [−0.13, −0.05]). Follow-up analyses confirms these findings: within-sibling MR ($$\widehat{\alpha }$$ α ̂ = −0.05 [−0.09, −0.01]); MR for childhood BMI on EDU ($$\widehat{\alpha }$$ α ̂ = −0.03 [−0.06, −0.002]); step-wise multivariable MR ($$\widehat{\alpha }$$ α ̂ = −0.05 [−0.07, −0.02]) where socio-economic indicators are jointly modelled. Here we show how the in-depth examination of the BMI-EDU causal relationship demonstrates the utility of our PWC-MR approach in revealing distinct pleiotropic pathways and confounder mechanisms.

Disentangling the effects of nicotine versus non-nicotine constituents of tobacco smoke on major depressive disorder: A multivariable Mendelian randomization study

“…Second, genetic variants linked to smoking heaviness are correlated with cognitive (e.g., years of education) [39,87] and physical traits (e.g., obesity) [39] which are associated with mental health and could be possible sources of pleiotropy. Whilst we employed methods to explore horizontal pleiotropy, future research could further explore the role of pleiotropic effects using MVMR to test the independent effects of tobacco smoking controlling for potential confounding factors, or novel PheWAS-based clustering of MR instruments [88]. Third, although multi-ancestry GWAS of smoking heaviness and major depression are available [89,90] the NMR GWAS was restricted to individuals of European ancestry and the MDD GWAS would not be stratified by smoking status, leading to violations of an assumption of MVMR is that all data included in the model are drawn from the same underlying population [30,44].…”