Publication
Identification of common genetic risk variants for autism spectrum disorder.
Grove Jakob, Ripke Stephan, Als Thomas D, Mattheisen Manuel, Walters Raymond K, Won Hyejung, Pallesen Jonatan, Agerbo Esben, Andreassen Ole A, Anney Richard, Awashti Swapnil, Belliveau Rich, Bettella Francesco, Buxbaum Joseph D, Bybjerg-Grauholm Jonas, Bækvad-Hansen Marie, Cerrato Felecia, Chambert Kimberly, Christensen Jane H, Churchhouse Claire, Dellenvall Karin, Demontis Ditte, De Rubeis Silvia, Devlin Bernie, Djurovic Srdjan, Dumont Ashley L, Goldstein Jacqueline I, Hansen Christine S, Hauberg Mads Engel, Hollegaard Mads V, Hope Sigrun, Howrigan Daniel P, Huang Hailiang, Hultman Christina M, Klei Lambertus, Maller Julian, Martin Joanna, Martin Alicia R, Moran Jennifer L, Nyegaard Mette, Nærland Terje, Palmer Duncan S, Palotie Aarno, Pedersen Carsten Bøcker, Pedersen Marianne Giørtz, dPoterba Timothy, Poulsen Jesper Buchhave, Pourcain Beate St, Qvist Per, Rehnström Karola, Reichenberg Abraham, Reichert Jennifer, Robinson Elise B, Roeder Kathryn, Roussos Panos, Saemundsen Evald, Sandin Sven, Satterstrom F Kyle, Davey Smith George, Stefansson Hreinn, Steinberg Stacy, Stevens Christine R, Sullivan Patrick F, Turley Patrick, Walters G Bragi, Xu Xinyi, Autism Spectrum Disorder Working Group of the Psychiatric Genomics Consortium, BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 23andMe Research Team, Stefansson Kari, Geschwind Daniel H, Nordentoft Merete, Hougaard David M, Werge Thomas, Mors Ole, Mortensen Preben Bo, Neale Benjamin M, Daly Mark J, Børglum Anders D
# Autism Spectrum Disorder Genetic Risk Variants
This genome-wide association study identified common genetic variants contributing to autism spectrum disorder (ASD) susceptibility through meta-analysis of 18,381 ASD cases and 27,969 controls, primarily leveraging a Danish population resource. The analysis discovered five genome-wide-significant loci associated with ASD and seven additional shared loci also implicated in schizophrenia, major depression, and educational attainment, reflecting overlapping genetic architectures across these traits.
The study examined polygenic heterogeneity across ASD subtypes, revealing both quantitative and qualitative variation in genetic architecture. Biological insights from the findings emphasized the importance of neuronal function and corticogenesis in ASD pathogenesis. The results demonstrate that large-scale GWAS approaches substantially increase the power to detect genetic risk variants for ASD, a highly heritable neurodevelopmental condition diagnosed in over 1% of children, and provide a foundation for understanding the complex genetic basis of this heterogeneous disorder.
Abstract
Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.