Increases in cohort sizes of genome-wide association studies (GWAS) in combination with the development of exome-sequencing approaches have led to increased locus and gene discovery, respectively, in schizophrenia. However, translating these genetic findings into specific and actionable molecular disease mechanisms remains a vexing bottleneck for biological insights and therapeutic discovery. To understand how genetic risk variants in schizophrenia converge onto functional pathways, we will investigate the protein-protein interaction networks of proteins encoded by genes strongly associated with schizophrenia in human neurons. Using iPSC-derived human cortical neurons, we will perform immunoprecipitations (IPs) followed by liquid chromatography tandem mass spectrometry (LC-MS/MS), and identify known complexes as well as novel interactions of schizophrenia-linked proteins. We will orthogonally validate our biochemical IP data using proximity-dependent labeling (BioID) to create multiple independent and synergistic datasets that together will point to new high-confidence pathway insights into schizophrenia. In addition, for a subset of the most interesting proteins, we will make detailed explorations of the structure of proteins they form a complex with using cryogenic electron microscopy (cryo-EM). The latter will reveal structural relationships and identify domains in schizophrenia proteins that are impacted by genetic variation, potentially resulting in modified or impaired interactions at the protein level. We have deep expertise in developing analytical and quality control (QC) computational platforms and we will evolve these methods to integrate experimental proteomics datasets with existing and emerging large-scale genetic data to model new pathway relationships in schizophrenia. We propose to widely share the proteomics datasets, computational applications, cell lines, and analytical tools and reagents generated in this study with the wider scientific community. Our work will identify new pathway relationships between schizophrenia-linked proteins and inform human brain biology with therapeutic relevance in these debilitating diseases. In addition, we will develop tools, reagent libraries and analytical web platforms that can be widely used by the community to study psychiatric diseases.
To understand why someone develops schizophrenia we need to understand the specific processes unique to the human brain that give rise to disease. Here, a team of researchers from different fields ? stem cell biology, human genetics, proteomics, and computer science ? join forces to create novel and collaborative approaches to work on this important question. Our group will investigate how different genes act on networks in brain cells to predispose to schizophrenia.