Subgroup Mediation Analysis

ABSTRACT Imaging genetics–based mediation analysis provides a powerful approach to understanding gene–brain–cognition pathways. However, despite recent progress, several challenges involving group‐level and subject‐level heterogeneity remain largely unaddressed. In this article, we develop a new model and the associated methodology for imaging genetics–based subgroup mediation analysis. Our key idea is to equip a system of structural equation models with conditional Gaussian graphical models, and we allow both the mean and precision matrix to vary based on individual covariates, which in turn define a set of latent clusters. As a result, our model can simultaneously identify gene–brain–cognition pathways, uncover brain connectivity network structures, handle high‐dimensional multivariate mediators and incorporate both group‐level and subject‐level heterogeneity. We carry out simulations to demonstrate the efficacy of our proposed method and further illustrate the method with an image genetics study of Alzheimer's disease.