Genetic associations of dimensional autistic phenotypes

Since there is a large variation in the symptoms shown by persons affected with ASD, analyzing genetics data using a case-control design is not straightforward. To avoid the difficult problem of defining heterogeneous groups, we used four different methods to compute a latent representation of a merged set of three psychometric tests. Computing the genetic contribution of each representation using a subset of participants with genetic data, we showed that factor analysis as well as variable autoencoders separates information contained in psychometric tests into genetically distinct phenotypic domains. Using the individual-level loadings of the domains as quantitative phenotypes in genome-wide association studies we detected statistically significant genetic associations in the domain related to insistence on routine, as well as suggestive genetic signals in other domains. We hope that these results can suggest possible domain-specific interventions in the future.