Human Isogenic Organoid Models of Genetic Forms of Autism to Identify Convergent and Divergent Pathomechanisms in Autism

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PROJECT SUMMARY Autism spectrum disorder (ASD) is a clinically complex, heterogeneous condition affecting 1 in 44 children in the U.S. The identification of common etiologies across multiple forms of genetic and idiopathic forms of ASD will critically advance diagnostic biomarker discovery and therapeutic development. Dysregulation of cellular translation has emerged as a pathophysiological mechanism common to at least a subset of ASD forms. However, systematic investigation of the cellular mechanisms that converge onto the ASD phenotype has been hampered by a paucity of robust and reproducible human ASD cellular models and scalable experimental tools for cell-type resolved characterization at the level of translation. To address these bottlenecks and to directly address the role of translational dysregulation as a common feature in ASD, we have (1) used advanced genome engineering tools to generate an extensively validated, isogenic series of induced pluripotent stem cell (iPSC) lines modeling 15 syndromic forms of ASD caused by highly penetrant gene and genome variants, representing ~10% of the total ASD population (the largest such panel created to date, to our knowledge), (2) established a robust human iPSCs-derived cortical organoid model of brain development, and (3) developed ribo-STAMP, a method for translational profiling of individual cells in heterogeneous cell populations, which is the first and only method enabling translation to be measured at single- cell resolution. In this project, we identify common and divergent pathological mechanisms in genome- engineered isogenic stem cell based organoid models of ASD, using single-cell transcriptomic and translatomic approaches. We validate our findings using cellular and functional phenotypic assays and in patient-derived iPSC models. If successful, our study will identify common and unique translation-aware single-cell resolved gene expression signatures that predict cellular and functional outcomes. We anticipate that our datasets and insights into cell-type specific deficits in gene expression of genetic forms of autism will critically accelerate the development of a unified framework that enables molecular categorization of both genetic and idiopathic cases, facilitating the identification of biomarkers and the development of targeted therapies.