Multivariate genomic architecture of cortical thickness and surface area at multiple levels of analysis
Recent work in imaging genetics suggests high levels of genetic overlap within cortical regions for cortical thickness (CT) and surface area (SA). In this manuscript by CGM investigators Jordan Smoller and Tian Ge, Genomic Structural Equation Modeling (Genomic SEM) was used to model this multivariate system of genetic relationships by applying and parsimoniously defining five genomic brain factors underlying both CT and SA along with a general factor capturing genetic overlap across all brain regions. Importantly, these factors were found to align with biologically and functionally relevant parcellations of the cortex. Stratified Genomic SEM was then used to identify specific categories of genes (e.g., neuronal cell types) that are disproportionately associated with pleiotropy across specific subclusters of brain regions, as indexed by the genomic factors. These powerful analyses provide key insights into the multivariate genomic architecture of two critical features of the cerebral cortex.