Schizophrenia and bipolar disorder, referred to together as the ?major psychoses,? are both devastating illnesses that strike young adults just as they are approaching their full potential, often resulting in a lifetime of chronic and severe disability. While distinct clinical entities, postmortem brain studies show high overlap and common genetic factors and familial co-segregation suggest strong overlap at the molecular level and potentially shared mechanisms. Here, we seek to directly dissect their common and distinct molecular basis by systematic profiling, dissection, computational integration, and experimental validation of their transcriptional, epigenomic, and genetic signatures across individuals, brain regions, and cell types. We use genetic, epigenomic, and transcriptional profiles, generating a total of ~1.2 million genome-wide maps at the single-cell (sc) level using scRNA-seq and scATAC-seq across 576 post-mortem brain samples from the McLean hospital psychiatric and normal cohorts. We analyze the resulting datasets in the context of genetic variation from whole-genome sequencing, and phenotypic variation from rich longitudinal profiling and cognitive evaluations, enabling us to discover genes, control regions, pathways, cell types, and brain regions playing causal roles in mentlal disorders, and how they vary across age, sex, and traits. We validate our predictions using a new high- throughput experimental dissection pipeline based on programmable CRISPR-based genomic, epigenomic, and transcriptomic dissection. The resulting datasets will help guide the search for new therapeutics, by providing detailed therapeutic targets, and the specific conditions where they are predicted to act.
Schizophrenia and bipolar disorder, referred to together as the ?major psychoses,? are both devastating illnesses that strike young adults just as they are approaching their full potential, often resulting in a lifetime of chronic and severe disability. While distinct clinical entities, postmortem brain studies show high overlap and common genetic factors and familial co-segregation suggest strong overlap at the molecular level and potentially shared mechanisms. Here, we seek to directly dissect their common and distinct molecular basis by systematic profiling, dissection, computational integration, and experimental validation of their transcriptional, epigenomic, and genetic signatures across individuals, brain regions, and cell types, using a panoply of state- of-the-art technologies, including single-cell profiling, systems-level computational integration, causality inference and mediation analysis, and high-throughput experimental dissection with a new programmable CRISPR-based genomic, epigenomic, and transcriptomic dissection system that we have developed.
