# Translational Technologies Core > **NIH NIH P50** · YALE UNIVERSITY · 2021 · $226,784 ## Abstract Translational Technologies Core PROJECT SUMMARY/ABSTRACT The Translational Technologies Core will support and provide expertise related to genetics and neuroimaging throughout the Center. It is well known that genetic factors are important in modulating risk of alcohol use disorder (AUD) and related traits. Genomewide association studies (GWAS) have identified multiple genetic risk loci for AUD, for problematic alcohol use, and for quantity-frequency measures such as AUDIT-C and drinks per week. Major function of the Genetics component will be to support microarray genotyping for each of the projects (including pilot projects) involving human subjects, for the purpose of identifying genotype/phenotype associations based on polygenic risk scores (PRS) of AUD and related traits. The Illumina Global Diversity Array (GDA) – also used by the “All of Us” research project, and with good coverage of all major US population groups and pharmacogenomic content, will be genotyped on all CTNA subjects. Most GWAS have focused on European-ancestry populations; we will also use the best available methodology to study non-European populations in a PRS context. 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 and transcriptomics of alcohol dependence. In turn, the Neuroimaging and Computational Neuroscience Component of the TTC will serve two key support goals across the Center: i) Neuroinformatics Acquisition and Harmonization Support: Building on the prior iteration of the Center, the TTC will provide a robust and centralized database for multi-modal neuroimaging, processing, integration and analytics. Specifically, all CTNA imaging data collection will be harmonized with the standardized imaging protocols developed by the Human Connectome Project (HCP). This will enable acquisition and analysis at dramatically enhanced spatial and temporal resolution across the entire Center, building programmatically on deep investments by the imaging community in these state-of-the-art data collection tools. Moreover, the TTC will feature an integration between the field-wide accepted XNAT (eXtensible Neuroimaging Archive Toolkit) database standard and the novel Yale-developed Quantitative Neuroimaging Environment & ToolboX (Qu|Nex) – a cutting-edge ‘turnkey’ container neuroimaging system built collaboratively with the HCP team. Notably, the. XNAT-Qu|Nex integration serves the framework for the ‘Connectome Coordinating Facility’, which we propose to deploy here for the entire Center. ii) Computational Neuroscience Support: The TTC will provide analytic support for the computational modeling and integration of innovative techniques for neuroimaging analysis using w... ## Key facts - **NIH application ID:** 10056550 - **Project number:** 2P50AA012870-21 - **Recipient organization:** YALE UNIVERSITY - **Principal Investigator:** JOEL GELERNTER - **Activity code:** P50 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $226,784 - **Award type:** 2 - **Project period:** 2001-06-04 → 2026-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10056550 ## Citation > US National Institutes of Health, RePORTER application 10056550, Translational Technologies Core (2P50AA012870-21). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10056550. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*