PROJECT SUMMARY Neurocognitive deficits represent a core component of several major neuropsychiatric disorders, including schizophrenia, affective disorders, autism spectrum disorders, and attention-deficit/hyperactivity disorder, and are not merely an epiphenomenon reflecting symptom severity, environmental deprivation, or medication side effects. The centrality of cognition to mental health is reflected in the RDoC matrix, in which “Cognitive Systems” is one of the six fundamental domains of investigation. Moreover, cognitive deficits are associated with poor functional outcomes, and are generally not well treated by existing psychotropic medications. Based on family studies and longitudinal observations, it has long been recognized that cognitive abnormalities are (to a significant degree) genetically mediated endophenotypes of serious mental illnesses. The Cognitive Genomics Consortium (COGENT), led by the PI of this application, has conducted a series of genome-wide association studies (GWAS) of cognitive phenotypes, which have confirmed the significant genetic overlap between cognitive performance and most forms of psychiatric illness at the molecular level. During five years of NIMH funding, this project has resulted in 13 publications, including the largest cognitive GWAS to date (N=373,617 yielding 241 significant loci) and the first large exome study identifying rare variants associated with cognitive performance in the general population. Moreover, we applied novel approaches to dissecting the pleiotropy observed between cognition and psychopathology, identifying “meta-loci” which are regions of the genome that underly specific patterns of pleiotropic overlap between phenotypes. This work has yielded new treatment targets, as well as biological insights on a dissociation between neurodevelopmental (prenatal) pathways vs adult synaptic processes underlying distinct forms of cognitive function and dysfunction. Over the next five years, we propose three main aims to extend our previous work, with an emphasis on biological interpretability and potential clinical applicability of results. First, we will add new, ethnically diverse cohorts for further cognitive GWAS and rare variant analysis, and we will seek to identify key subdomains of cognitive function for further downstream analysis. Second, we will incorporate these cognitive subdomains as well as newly available, large-scale neuroimaging genomics data in a novel set of analyses, derived from our “meta-loci” approach, to parse psychiatric phenotypes into biologically coherent subcomponents. Third, we will construct novel, biologically-informed polygenic risk scores (PRS) and test whether these have greater prognostic value as compared to conventional, genome-wide PRS based on single-trait GWAS. Thus, our plan leverages diverse large-scale genomics resources, and a range of expertise, to derive actionable information (novel treatment targets, biological mechanisms, and biomarkers) rela...