Identification of common genetic risk variants for autism spectrum 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 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture, we find 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.

Autism spectrum disorder polygenic scores are associated with every day executive function in children admitted for clinical assessment

“…Furthermore, it is important to be aware of potential factors that can influence the PGSs. In Grove et al's ASD sample it is likely that some of the participants might have had comorbid ADHD [Grove et al, ], and the ADHD risk score calculated by Demontis et al might be more specific to ADHD [Demontis et al, ]. However, it is likely that there is some overlap between all the different phenotypes, especially at P ‐values as high as 0.1.…”

“…The current sample was part of the national BUPGEN network and was recruited between 2013 and 2018. For a detailed description of the recruitment procedure see Grove et al supplementary material [Grove et al, ]. Inclusion criteria were ASD‐related difficulties and suspected ASD diagnosis, independent of final ASD diagnosis.…”

“…In the linear regression, we used the groups Low, Moderate and High PGSs. The discovery samples our PGS are based on consisted of 18,381 ASD cases and 27,969 controls for the ASD PGS [Grove et al, ], 20,183 ADHD cases and 35,191 controls for the ADHD PGS [Demontis et al, ] and 269,867 cases for the INT PGS [Savage et al, ].…”

The p factor: genetic analyses support a general dimension of psychopathology in childhood and adolescence

“…We also obtained the first PC from polygenic scores for psychiatric disorders (polygenic p). We used publicly available genome‐wide association summary statistics for eight major psychiatric traits: autism spectrum disorder (Grove et al., ), major depressive disorder (MDD; Wray et al., ), bipolar disorder (BIP), schizophrenia (SCZ; Pardiñas et al., ), attention deficit hyperactivity disorder (ADHD; Demontis et al., ), obsessive–compulsive disorder (OCD; International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF‐GC) and OCD Collaborative Genetics Association Studies (OCGAS), ), anorexia nervosa (AN; Duncan et al., ) and posttraumatic stress disorder (PTSD; Duncan et al., ). For each psychiatric disorder, polygenic scores for each TEDS participant were created in LDpred (Vilhjálmsson et al., ), assuming a fraction of causal markers of 1 (analysis steps were similar to Selzam et al., ).…”

Mapping causal pathways from genetics to neuropsychiatric disorders using genome‐wide imaging genetics: Current status and future directions

“…Despite the behavioral definitions of neuropsychiatric disorders and their phenotypic heterogeneity, genetic search has already identified many risk loci by compiling data from tens of thousands of individuals . This somewhat obviates the proposed use of endophenotypes as a tool for identifying genetic risk loci for neuropsychiatric illness with higher power (Use 1, above).…”