Abstract
Background When a randomized experimental study is not possible, Mendelian randomization studies use genetic variants or polygenic scores as instrumental variables to control for gene-environment correlation while estimating the association between an exposure and outcome. Polygenic scores have become increasingly potent predictors of their respective phenotypes, satisfying the relevance criteria of an instrumental variable. Evidence for pleiotropy, however, casts doubt on whether the exclusion criteria of an instrumental variable is likely to hold for polygenic scores of complex phenotypes, and a number of methods have been developed to adjust for pleiotropy in Mendelian randomization studies.
Method Using multiple polygenic scores and path analysis we implement an extension of genetic instrumental variable regression, genetic path analysis, and use it to test whether educational attainment is associated with two health-related outcomes in adulthood, body mass index and smoking initiation, while estimating and controlling for both gene-environment correlations and pleiotropy.
Results Genetic path analysis provides compelling evidence for a complex set of gene-environment transactions that undergird the relations between educational attainment and health-related outcomes in adulthood. Importantly, results are consistent with education having a protective effect on body mass index and smoking initiation, even after controlling for gene-environment correlations and pleiotropy.
Conclusions The proposed method is capable of addressing the exclusion criteria for a sound instrumental variable and, consequently, has the potential to help advance Mendelian randomization studies of complex phenotypes.
Footnotes
All in-text citations and references were changed from APA-style to Vancouver-style formatting. Figure 1 was revised for greater clarity. Table 2 was created to report the effects of exogenous covariates on focal study variables. Estimated odds ratios from logistic regressions are biased when the dependent variable is common, like smoking initiation in the current study. Therefore, pathways to smoking initiation were estimated as Poisson regressions with robust standard errors, which provides an unbiased estimate of risk ratios and associated confidence intervals for common outcomes. Results have been revised accordingly (i.e. risk ratios from robust Poisson regressions are reported, instead of odds ratios from logit regressions).
