Translational Technologies Core Joel Gelernter, M.D. & Alan Anticevic, Ph.D. Abstract The Translational Technologies Core will support and provide expertise related to genetics and neuroimaging through the Center. It is well known that genetic factors are important in modulating risk of alcohol dependence (AD) and related traits. Several alcohol dependence risk loci are now known, and specific candidate genes have been identified as potentially important for the component projects in the center. Major function of the Genetics component will be to support genotyping for each of the projects (including pilot projects) involving human subjects, for the purpose of identifying genotype/phenotype correlations. A microarray containing ~250k genomewide tagging SNPs, ~250k exomic putatively functional SNPs, and 50k of added SNP content relevant to psychiatric traits (the Illumina PGC array) will be genotyped on all CTNA subjects. The goals of the clinical components of the Center require study of ethnically heterogeneous populations, but study of stratified samples that differ in allele frequency and phenotype for candidate loci of interest can create artifactual association. We will therefore apply methods to measure and statistically correct for the effects of population stratification. Genetics component investigators will advise Center investigators on issues related to genetics studies. We will also bring to bear a rich dataset of GWASed subjects with alcohol and other substance dependencies that can be used to test hypothesis related to Center findings and goals; and we will continue pilot work in related topics of interest, e.g., epigenetics of alcohol dependence. In turn, emerging evidence implicates glutamateric neural alterations affecting structure and function across reward-related cortico-striatal- thalamic-cortical pathways (CSTC) and higher-order prefrontal cortex (PFC) control circuits in AD. However, the neural network level deficits that may arise as a function of AD or its genetic risk is profoundly lacking, limiting our understanding of its neurobiology and developments of better treatments. To address this gap in knowledge, the overarching aim of the Neuroimaging component of the Core is to leverage advances in functional and structural neuroimaging made possible by the Human Connectome Project, to permit acquisition and analysis at dramatically enhanced spatial and temporal resolution across the entire Center. The Neuroimaging component will utilize analytic advances in our Center to accomplish network-driven and hypothesis-grounded examination of multi-modal structural and functional network connectivity focused on reward-related CSTC and PFC circuits, as well as fully data-driven methods. We aim to characterize neural network disruptions in AD in relation to: i) drinking levels, ii) familial risk; iii) treatment response; and iv) individual differences in clinical phenotypes – concurrently capitalizing on the synergistic recruitmen...