This mentored career development grant application proposes a training program to integrate Dr. Fardo's previous research in biostatistics and statistical genetics into investigations of aging disorders including highly prevalent neurodegenerative diseases. His long-term career goal is to develop an independent research program focusing on the advancement of statistical methodologies to understand the genetics underlying complex diseases, with an emphasis on diseases of brain aging. This will be achieved through acquiring knowledge in the area of brain diseases of aging through formal coursework and mentored experiences;training in the management, analysis and interpretation of associated research data;comprehensive examination of the large-scale genetic data used in aging studies and the areas where novel, cutting-edge biostatistical methodologies could improve analyses;application, refinement and development of statistical genetic approaches to the analysis of this large-scale genetic data;and the continuation of training in the responsible conduct of research. Dr. Fardo's research training will involve an enthusiastic team of cross- disciplinary researchers with a strong research track record. An overall goal of this K25 application is to capitalize on the clinical and neuropathologic data available from large, multicenter-derived databases to identify single nucleotide polymorphisms (SNPs) associated with specific neuropathologic endophenotypes. Most research investigating the genetic predisposition of age-related complex diseases has been conceptualized with a model directly comparing those with or without a disease, for example, with or without Alzheimer's disease (AD). However, this disease/non-disease approach is inefficient and not appropriate for investigating the genetic risk factors for so-called mixed pathologies which are the norm in advanced age. The proposed research program will interrogate genetic associations with neuropathologic features of a large cohort of autopsied brains. This will be done by utilizing data collected from large, NIH-funded resources. Neuropathology data and genome-wide genetic data will be merged from these resources, and genetic associations for mixed-pathology dementias and neuropathologic features will be comprehensively tested. This work will result in new methods to analyze mixed-pathology dementias and neuropathologic features as well as the exploration of associated genetic risk factors and gene-environment interactions.
Understanding better the biological mechanisms that underlie complex diseases of brain aging can aid in the ability to diagnose disease early, track disease progression, and identify drug targets for treatment. The genetic knowledge to be garnered from this proposal is critical to discover and refine risk factors and the associated biological mechanisms of diseases of brain aging.
|Nelson, Peter T; Trojanowski, John Q; Abner, Erin L et al. (2016) ""New Old Pathologies"": AD, PART, and Cerebral Age-Related TDP-43 With Sclerosis (CARTS). J Neuropathol Exp Neurol 75:482-98|
|Katsumata, Yuriko; Fardo, David W (2016) On combining family- and population-based sequencing data. BMC Proc 10:175-179|
|Kryscio, R J; Abner, E L; Jicha, G A et al. (2016) Self-Reported Memory Complaints: A Comparison of Demented and Unimpaired Outcomes. J Prev Alzheimers Dis 3:13-19|
|Ighodaro, Eseosa T; Abner, Erin L; Fardo, David W et al. (2016) Risk factors and global cognitive status related to brain arteriolosclerosis in elderly individuals. J Cereb Blood Flow Metab :|
|Monsell, Sarah E; Mock, Charles; Fardo, David W et al. (2016) Genetic Comparison of Symptomatic and Asymptomatic Persons With Alzheimer Disease Neuropathology. Alzheimer Dis Assoc Disord :|
|Wang, Chi; Liu, Jinpeng; Fardo, David W (2016) Causal effect estimation in sequencing studies: a Bayesian method to account for confounder adjustment uncertainty. BMC Proc 10:411-415|
|Mez, Jesse; Mukherjee, Shubhabrata; Thornton, Timothy et al. (2016) The executive prominent/memory prominent spectrum in Alzheimer's disease is highly heritable. Neurobiol Aging 41:115-21|
|Nelson, Peter T; Katsumata, Yuriko; Nho, Kwangsik et al. (2016) Genomics and CSF analyses implicate thyroid hormone in hippocampal sclerosis of aging. Acta Neuropathol 132:841-858|
|Kryscio, R J; Abner, E L; Nelson, P T et al. (2016) The Effect of Vascular Neuropathology on Late-life Cognition: Results from the SMART Project. J Prev Alzheimers Dis 3:85-91|
|Ellingson, Sally R; Fardo, David W (2016) Automated quality control for genome wide association studies. F1000Res 5:1889|
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