Identification of transcriptional changes associated with syndromic forms of autism
Autism spectrum disorders (ASDs) are highly heritable neuropsychiatric conditions. However, the genetic etiology is greatly heterogeneous. No single genetic cause responsible for the majority of ASD cases has been identified so far. Given the genetic heterogeneity, the process through which diverse genetic factors lead to shared phenotypes in ASD remains unclear, and it is critical to understanding the ASD pathophysiology. As previous studies have implied the convergence of pathways in ASD at the transcriptomic level, in this dissertation, we conducted genome-wide expression analysis by using cell lines derived from various syndromic ASD conditions in an attempt to identify potentially common expression alterations in all or a subset of those ASD conditions, and to elucidate the convergent pathway(s) involved in ASD pathogenesis.
We analyzed expression profiles of patient-specific neurons derived from induced pluripotent stem cells (iPSCs) from patients with three different monogenic ASD mutations: 22q13.3 deletion, 22q11.2 deletion, and Timothy syndrome (TS). By comparing the ASD mutations with controls, respectively, our analysis revealed substantial gene expression changes in each of these mutations. Some of the identified expression changes could be generalized to neurons and postmortem brains from idiopathic autistic patients.
In addition to the iPSC sample cohort, we also analyzed expression profiles of lymphoblast cell line (LCLs) from 5 different syndromic forms of ASD. Significant overlapping expression features were identified among these ASD forms, and a set of them recapitulated the expression features we identified using iPSC-derived neurons. To our knowledge, this is the first time that significant shared transcriptional features have been identified in ASD between brain-related cell types and peripherally derived cell lines, providing strong support for the usefulness of LCLs in exploring ASD pathogenesis. In addition to the similarities, our analysis also highlighted the diversity in gene expression across different ASD mutations, which may explain how each ASD forms are modulated given their phenotypic heterogeneity. Overall, our findings highlight the specificity and convergence of ASD at the transcriptional level, suggesting promising directions for future research.