ABSTRACT White matter (WM) circuitry is the basis for neuronal communication in the human brain and exhibits robust abnormalities in all major psychiatric, neurological, and developmental conditions. The ENIGMA consortium has already performed the largest, most well-powered coordinated studies of WM microstructural variability within and across several major mental disorders and illnesses. We have already discovered common patterns of deficits in our most highly powered, and internationally representative studies of severe mental illnesses to date, including schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). The overlap in the patterns of microstructural variation in these disorders also correlate with the overlap in genetic risk suggested by large scale GWAS. These emerging findings within the ENIGMA consortium motivate a highly-powered, rigorous, and in-depth study of disease and genetic effects on WM tracts and circuits implicated in severe mental illnesses. Here we launch an initiative that unites leaders in the fields of neuroimaging harmonization and analysis, diffusion connectivity, psychiatry, psychiatric genetics, statistical genetics, neuroimaging genetics, workflow automation, and AI and distributed data science. Our proposed work will extend the collaborative study of mapping brain-imaging biomarkers and the variability that drives underlying vulnerability to risk of mental illness. All our findings will be made publicly available, as in all prior ENIGMA studies. Here we extend methods for the public distribution and dissemination of findings through NeuroDISK - an ontologically integrated, user- friendly platform, for user-driven sub-analyses based on cohort level meta-data. This innovative framework enables continuous data integration and updating of findings. In our Specific Aims, our multidisciplinary and highly productive team of investigators will: 1) perform a global coordinated GWAS of microstructure metrics in over 100,000 individuals of all ages scanned with diffusion MRI in a discovery and replication framework; 2) distribute a novel AI-driven protocol to extract and quality control the midsagittal corpus callosum metrics from the more commonly collected, T1-weighted structural MRIs, to map and harmonize developmental trajectories of callosal maturation and degeneration across the lifespan; we will accommodate MRI data of research and clinical quality, and identifying genetic architecture for callosal thickness, area, and curvature; 3) constructing an integrated ENIGMA-DSI Studio pipeline offering high-throughput tractography and fiber analytic methods on the DSI-Studio software to identify structural dysconnectivity in ENIGMA working groups on SCZ, BD, MDD; 4) distribute and disseminate publicly available, containerized tractography and fiber analytic protocols with image acquisition specific considerations, and means for continuous data integration and analyses in our novel NeuroDISK framewor...