Multivariate genomic architecture of cortical thickness and surface area at multiple levels of analysis. Journal Article uri icon



  • Recent work in imaging genetics suggests high levels of genetic overlap within cortical regions for cortical thickness (CT) and surface area (SA). We model this multivariate system of genetic relationships by applying Genomic Structural Equation Modeling (Genomic SEM) and parsimoniously define five genomic brain factors underlying both CT and SA along with a general factor capturing genetic overlap across all brain regions. We validate these factors by demonstrating the generalizability of the model to a semi-independent sample and show that the factors align with biologically and functionally relevant parcellations of the cortex. We apply Stratified Genomic SEM 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. Finally, we examine genetic associations with psychiatric and cognitive correlates, finding that broad aspects of cognitive function are associated with a general factor for SA and that psychiatric associations are null. These analyses provide key insights into the multivariate genomic architecture of two critical features of the cerebral cortex.

publication date

  • February 20, 2023

has restriction

  • gold

Date in CU Experts

  • August 30, 2023 12:07 PM

Full Author List

  • Grotzinger AD; Mallard TT; Liu Z; Seidlitz J; Ge T; Smoller JW

author count

  • 6

Other Profiles

Electronic International Standard Serial Number (EISSN)

  • 2041-1723

Additional Document Info

start page

  • 946


  • 14


  • 1