Mediation models have been employed in the study of brain disorders to detect the underlying mechanisms between genetic variants and diagnostic outcomes implicitly mediated by intermediate imaging biomarkers. However, the statistical power is influenced by the modest effects of individual genetic variants on both diagnostic and imaging phenotypes and the limited sample sizes ofimaging genetic cohorts. In this study, we propose a polygenic mediation analysis that comprises a polygenic risk score (PRS) to aggregate genetic effects ofa set ofcandidate variants and then explore the implicit effect ofimaging phenotypes between the PRS and disease status. We applied our proposed method to an amyloid imaging genetic study of Alzheimer's disease (AD), identified multiple imaging mediators linking PRS with AD, and further demonstrated the promise of the PRS on mediator detection over individual variants alone
