Session #5: Big Data and Genetic Liability to Neuropsychiatric Disease

Common neuropsychiatric illnesses, such as schizophrenia, bipolar disorder and Alzheimer’s disease, carry considerable morbidity, mortality, and personal and societal cost. While recent large-scale genetic association studies have identified numerous risk loci, the mechanisms through which they contribute to disease remain largely unknown. By applying single cell molecular approaches to the affected tissue (in this case, the human brain), we can uncover novel cellular subpopulations that are associated with disease. In parallel, cell type-specific molecular studies allow us to characterize the effect of genetic variation on the 3-dimensional configuration of the genome and on the complex mechanisms that regulate gene expression in those cells relevant to disease. All these brain-specific multi-scale data are leveraged to interpret the genetic architecture of neuropsychiatric illnesses in large-scale biobank datasets