Decomposition of phenotypic heterogeneity in autism reveals underlying genetic programs.

ABSTRACT: Unraveling the phenotypic and genetic complexity of autism is extremely challenging yet critical for understanding the biology, inheritance, trajectory and clinical manifestations of the many forms of the condition. Using a generative mixture modeling approach, we leverage broad phenotypic data from a large cohort with matched genetics to identify robust, clinically relevant classes of autism and their patterns of core, associated and co-occurring traits, which we further validate and replicate in an independent cohort. We demonstrate that phenotypic and clinical outcomes correspond to genetic and molecular programs of common, de novo and inherited variation and further characterize distinct pathways disrupted by the sets of mutations in each class. Remarkably, we discover that class-speci

SUBMITTER: Litman A 

PROVIDER: S-EPMC12283356 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature