POLYGENIC RISK CONVERGES ON CELL-TYPE–SPECIFIC AND DEVELOPMENTAL REGULATORY PROGRAMS IN AUTISM

Genetic studies have identified both common and rare variants contributing to autism spectrum disorder (ASD), yet the mechanisms linking polygenic risk to cell-type–specific and developmental dysfunction remain incompletely defined. Here, we leverage large-scale, multi-ancestry genetic data integrated with functional genomic resources from GENESIS to resolve the regulatory architecture underlying ASD risk across cell types and developmental trajectories. We performed transcriptome-wide association studies (TWAS) across single-nucleus brain datasets, coupled with fine-mapping and colocalization to prioritize candidate causal genes and regulatory elements. Integration with cell-type–resolved expression and epigenomic QTL maps enabled the identification of genetically regulated expression changes across neuronal and glial populations. To capture developmental dynamics, we further incorporated pseudotime-inferred QTLs and early brain expression–regulatory (E–P) relationships, linking genetic effects to stage-specific regulatory programs during human cortical development. TWAS signals showed robust enrichment in excitatory neuronal subclasses, particularly cortical projection neurons, with additional contributions from inhibitory neurons and oligodendrocyte lineage cells. These effects were consistent across single-nucleus models and supported by colocalization with regulatory variants. Importantly, ASD-associated loci demonstrated significant overlap with pseudotime-resolved developmental QTLs, indicating that genetic risk preferentially acts through temporally dynamic regulatory mechanisms. Integration with early developmental E–P maps further highlighted enhancer–promoter interactions active during neurogenesis and early circuit formation. Several loci demonstrated convergent regulation across datasets, identifying shared gene regulatory programs underlying ASD risk. Representative loci, including KIZ, illustrate how common variation drives modest but coordinated changes in expression across specific neuronal populations and developmental windows, consistent with enrichment in neuronal enhancer activity. Cross-disorder analyses revealed substantial overlap with schizophrenia and related neuropsychiatric traits, while also identifying ASD-enriched regulatory signatures. These findings provide a unified framework linking polygenic variation to cell-type–specific and temporally resolved regulatory mechanisms in ASD and demonstrate how multi-ancestry TWAS integrated with developmental functional genomics refines causal inference and biological interpretation of psychiatric disease risk.