Genetic Contributors to White Matter Microstructure in Aging and Alzheimers Disease

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PROJECT SUMMARY While reductions in medial temporal lobe (MTL) white matter tract microstructure have been suggested to have a central role in longitudinal cognitive decline in aging and Alzheimer’s disease (AD), it is unknown what genetic factors drive these reductions. The objective of this proposal is to use MTL white matter tract templates in conjunction with genome-wide analyses to identify the genetic drivers of white matter tract microstructure. This proposal will leverage several aging datasets, including the Alzheimer’s Disease Neuroimaging Initiative (n=525), Baltimore Longitudinal Study of Aging (n=295), Religious Orders Study/Memory and Aging Project/Minority Aging Research Study (n=414), Vanderbilt Memory & Aging Project (n=319), Wisconsin Alzheimer’s Disease Research Center (n=488), and Wisconsin Registry for Alzheimer’s Prevention (n=468) to conduct all analyses, totaling in 2,509 participants. Moreover, validation of all results will be conducted using data from a well-established lifespan study (UK Biobank (n=14,701)) and data from the AD Genetics Consortium. The central hypothesis is that MTL white matter tract microstructure is driven by genes and pathways related to myelination, axonal transport, and neuroinflammation in aging and AD. Based on this hypothesis, the primary aims of this proposal will take a multi-level approach to understand which genes and pathways lead to MTL white matter microstructure by using: (1) a candidate gene approach to determine with AD-risk genes are associated with MTL white matter microstructure, (2) a genome-wide approach to identify novel variants which contribute to MTL white matter microstructure and quantify genetic overlap with other traits, and (3) a genome-wide approach to identify how gene expression is associated with MTL white matter tract microstructure and localize signals to relevant biologic pathways. The complementary training plan will equip me with the skills necessary to transition to an independent career focused on imaging genetics by emphasizing the following training objectives: (a) expand expertise in computational genetics, (b) acquire a practical understanding of the pathophysiology and clinical manifestation of AD, and (c) enhance my skillset in data harmonization and big data analytical techniques. The mentoring team is made up of experts in each of these areas, and their training will be augmented through formal coursework, interdisciplinary training at the Vanderbilt Memory & Alzheimer’s Center, and cutting-edge computational and genomic resources available at the Vanderbilt University Medical Center. Together, these practical and intellectual resources provide the ideal training environment, and my primary mentor, Dr. Timothy Hohman, has a well-funded laboratory which will provide all the necessary resources for career transition. These resources will allow me to dedicate 100% protected effort as an Assistant Professor to focus on research and career development. This will ensure that I can competitively compete for independent funding (R01) over the course of the proposed award period.