bioRxivGenomicsPreprint
Mapping the genetic architecture of human cortical expansion and its links to neuropsychiatric disorders
Matthew RosenblattiD, Marlee M. VandewouwiD, Henry Fox-JurkowitziD, Camille Michèle WilliamsiD, Yuanxin ZhongiD, Da ZhiiD, Yingzhe ZhangiD, Margaret L. WestwateriD, Armin RaznahaniD, Michael J. GandaliD, Tian GeiD, Dustin ScheinostiD, Jordan W. SmolleriD, Travis T. MallardiD
Abstract
Cortical expansion is a defining feature of human evolution and neurodevelopment, involving the tangential growth and gyrification of the cerebral cortex. Although disruptions to the expansion of the cortex are implicated in diverse brain-based disorders, the genetic architecture underlying this process remains undercharacterized. Here, we integrated GWAS data for five neuroanatomical phenotypes measured in up to 73,800 individuals to model a latent genomic factor capturing the shared genetic basis of cortical surface area, folding, curvature, gyrification, and intracranial volume. Using a multivariate framework, we mapped this pleiotropic architecture across biological scales, identifying novel effector genes, neural cell types, and developmental pathways involved in cortical expansion. Functional genomic evidence indicated that a diverse cellular ensemble contributes to the tangential growth and gyrification of the cortex during prenatal neurodevelopment, with progenitor cell lineages prominently involved. Regional analyses further revealed that genetic influences are spatially heterogeneous and organized along canonical anatomical, functional, and developmental gradients. Finally, cortical expansion exhibited substantial genetic overlap with neurodevelopmental, psychiatric, and neurological disorders, with shared genetic influences often concentrated in prefrontal cortical regions. Together, these findings map the genetic architecture of human cortical expansion and implicate it as a common etiological axis linking evolution, neurodevelopment, and health and disease.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 0
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