Sanan Venkatesh, Roman Kosoy, Zhenyi Wu, Marios Anyfantakis, Christian Dillard, Prashant N M, David Burstein, Deepika Mathur, Chris Chatzinakos, Bukola Ajanaku, Fotis Tsetsos, Biao Zeng, Sonali Gupta, Rachel Bercovitch, Aram Hong, Clara Casey, Marcela Alvia, Zhiping Shao, Stathis Argyriou, Karen Therrien, PsychAD Consortium, Tim Bigdeli, Pavan Auluck, David A Bennett, Stefano Marenco, Vahram Haroutunian, Kiran Girdhar, Jaroslav Bendl, Donghoon Lee, John F Fullard, Gabriel E Hoffman, Georgios Voloudakis, Panos Roussos
Common brain disorders impose a substantial health burden, but localizing their genetic risk in the brain remains challenging1. Although genome-wide association studies have identified numerous loci associated with neuropsychiatric and neurodegenerative disorders, many of these loci lie in non-coding regions that influence gene expression in specific cell types2-5. Traditional bulk brain transcriptomic analyses, which often focus on European ancestry cohorts, average over cellular diversity, obscuring genetic risk-related changes in gene expression. Here we use single-nucleus gene expression profiles from the dorsolateral prefrontal cortex in the multi-ancestry PsychAD cohort to develop transcriptomic imputation models of genetically regulated expression across major brain cell types. Applying these models to neuropsychiatric and neurodegenerative disorders reveals thousands of gene-trait associations that are undetectable in bulk tissue analyses and resolves many signals to discrete neuronal, glial and immune cell populations. Cross-ancestry analyses in the Million Veteran Program confirm these associations, reveal pleiotropic effects of cell-type-specific predicted expression and demonstrate that trait-related dysregulation is conserved across ancestries, enabling mapping of causal genes and pathways. Together, these findings provide a cell-type-resolved and ancestry-aware atlas of genetically regulated expression in the human prefrontal cortex and illustrate how single-nucleus transcriptomics can sharpen gene discovery and therapeutic target prioritization for complex brain disorders.