Assay and Data Generation Center (ADGC) for the Model of iPSC-derived Neurons for NPD (MiNND)

Project Summary/Abstract In the past decade, the scientific community has witnessed accelerated genetic discoveries for neurodevelopmental and psychiatric disorders (NPD) such as schizophrenia (SZ), autism spectrum disorder (ASD), bipolar disorder, and major depression. Genome-wide association studies (GWAS) and whole-exome sequencing (WES) have identified a mounting number of NPD risk genes. However, translating these exciting genetic discoveries into clinically actionable biology has been impeded by our limited knowledge of gene function and related disease mechanisms. A bottleneck in the field is that most biological characterization has focused on very few NPD genes, which have not necessarily been selected for study based on pathophysiological importance. Furthermore, genes are often studied one at a time, hindering the pace of our understanding of disease mechanisms. We propose an alternative strategy: large-scale, unbiased, parallel study of NPD genes in disease-relevant model systems, in response to the RFA-MH-22-111 (Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes-SSPsyGene). We propose to establish the Assay and Data Generation Center (ADGC) for the Model of induced pluripotent stem cell (iPSC)-derived Neurons for NPD (MiNND), where we will implement and optimize novel scalable and systematic assays for interrogating the molecular and neurobiological functions of up to 200 NPD risk genes. Teaming up with the SSPsyGene Consortium and leveraging our team’s respective expertise in stem cell biology, functional genomics, neuroscience, and functional analysis, our MiNND-ADGC will generate loss-of-function (LoF) iPSC human neural models, and perform high-content morphometric and single-cell transcriptomic (scRNA-seq) analyses of NPD LoF alleles. We will also assay synaptic functions using optical sensors in a high-throughput fashion and carry out multimodal PatchSeq analyses and modeling to predict neuronal properties from scRNA-seq data. Finally, working with the SSPsyGene Consortium, we will conduct data integration, curation, and dissemination to the research community and public for further analysis. Our MiNND-ADGC will build a valuable resource and integrated knowledge base that will provide a fertile foundation for future studies of disease mechanisms. The data from studying the selected NPD risk genes on multiple genetic backgrounds, including the understudied African American iPSC lines, will enable robust inferences of potential cross-disorder and cross-population biological convergence and divergence relevant to NPD.