Genome-wide polygenic scoring is a popular method to test for associations between genetic liability and specific phenotypes (Barr et al., 2020; Duncan et al., 2019; Martin et al., 2019), and characterize environmental mediators through which that liability is realized (Domingue et al., 2020; Pasman et al., 2019; Uher & Zwicker, 2017). Oftentimes in polygenic association analyses, covariates are entered into the model to evaluate whether an association with the polygenic risk scores (PRS) of interest is robust to potential confounders; however, the effects of PRS may be biased by the inclusion of heritable covariates when the covariate is influenced by unmeasured confounding variables (Akimova et al., 2021). This bias is generally referred to as collider bias. For example, the estimated effect of a polygenic score for alcohol consumption may be biased in a model that also includes educational attainment as a covariate if the polygenic score for alcohol consumption is correlated with educational attainment. Previous work demonstrates that alcohol consumption is genetically correlated with educational attainment (Sanchez-Roige et al., 2019; Walters et al., 2018; Zhou et al., 2020). Furthermore, educational
