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Description
Autism and ADHD frequently co-occur and share genetic architecture, but it remains unclear how shared versus condition-specific liability maps onto neuroanatomical variation. We integrated GWAS summary statistics for autism, ADHD, and both combined (neurodevelopmental diversity, NDD) with cortical gene-expression data from the Allen Human Brain Atlas to derive genetically informed cortical liability patterns. Structural MRI data were obtained from three cohorts (AIMS-2-Trials, NeuroIMAGE, BrainMap; N=1360; ages 6–30). Cortical thickness was extracted using FreeSurfer, and vertex-wise models identified condition-related cortical patterns. Gene-level associations were computed with MAGMA, and a genetic algorithm identified subsets of genes whose cortical expression profiles best predicted neuroanatomical variability. Genetically predicted liability patterns significantly matched their respective imaging phenotypes (autism: rspatial=-0.56; ADHD: rspatial=0.45; NDD: rspatial=-0.52; all pperm<0.001). Gene sets showed minimal overlap, and liability patterns did not predict the other condition’s cortical phenotype, supporting partially separable neurobiological pathways for autism and ADHD despite shared genetic liability.