Multivariate genomic architecture of cortical thickness and surface area at multiple levels of analysis.

ABSTRACT: 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 acros

SUBMITTER: Grotzinger AD 

PROVIDER: S-EPMC9941500 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature