Structural imaging provides a means to visualize change in anatomy associated with cognitive decline (e.g., Project 3 """"""""Attention Profiles in Healthy Aging and Early Stage DAT"""""""") and also candidate surrogate markers for detection of early-stage DAT in combination with other biomarkers (e.g., Project 2 """"""""Antecedent biomarkers of AD in CSF""""""""). The goal of the Core E: Imaging is to collect, store, and disseminate imaging data for the use of the present program project investigations and also to facilitate the development of infrastructure to support future imaging projects. The following Specific Aims will be pursued: 1. Structural imaging data on demented and nondemented participants will be collected, in close coordination with Core B: Clinical, at two-year longitudinal intervals. The structural imaging battery will include (i) multiple acquisitions of high contrast MP-RAGE images, (ii)3D T2 images for assessment of white matter. These images will be used for measurement of cortical and subcortical atrophy and assessment of white matter integrity, (iii)diffusion tensor imaging to assess white matter microstructural integrity, and (iv)T2-SWI images. In addition, functional imaging data on demented and nondemented participants will be collected. The functional imaging data will be BOLD images during rest to assess functional connectivity. 2. Research neuroradiological assessment will be made by board-certified neuroradiologists on all structural image data sets. 3. Structural data sets will be archived in conjunction with Core C: Biostatistics and made available via a web-based interface to investigators to pursue research projects. 4. Quantitative structural assessment will be provided for correlating imaging data with project-specific data including (i) automated estimates of whole- brain atrophy, (ii) manual estimates of hippocampal, entorhinal, frontal, and other cortical volumes, (iii) automated estimates of cortical and subcortical volumes derived from Freesurfer software (Fischl et al., 2002;Fischl et al., 2004;Desikan et al., 2006), and (iv) automated assessment of white matter hyperintensities. Quantitative functional assessment will also be provided for correlating imaging data with project-specific data and will include estimates of the functional connectivity between seed regions such as the hippocampus and the precuneus. 5. Working closely with Core C: Biostatistics and Core A: Administration, data will be managed to integrate the Core's function with the scientific goals of the program project.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
5P01AG003991-30
Application #
8425013
Study Section
Special Emphasis Panel (ZAG1-ZIJ-4)
Project Start
Project End
2014-12-31
Budget Start
2013-01-01
Budget End
2013-12-31
Support Year
30
Fiscal Year
2013
Total Cost
$182,007
Indirect Cost
$62,266
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Liao, Fan; Li, Aimin; Xiong, Monica et al. (2018) Targeting of nonlipidated, aggregated apoE with antibodies inhibits amyloid accumulation. J Clin Invest 128:2144-2155
Jansen, Willemijn J; Ossenkoppele, Rik; Tijms, Betty M et al. (2018) Association of Cerebral Amyloid-? Aggregation With Cognitive Functioning in Persons Without Dementia. JAMA Psychiatry 75:84-95
Yan, Qi; Nho, Kwangsik; Del-Aguila, Jorge L et al. (2018) Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging. Mol Psychiatry :
Islam, Jyoti; Zhang, Yanqing (2018) Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks. Brain Inform 5:2
Strain, Jeremy F; Smith, Robert X; Beaumont, Helen et al. (2018) Loss of white matter integrity reflects tau accumulation in Alzheimer disease defined regions. Neurology 91:e313-e318
Roe, Catherine M; Ances, Beau M; Head, Denise et al. (2018) Incident cognitive impairment: longitudinal changes in molecular, structural and cognitive biomarkers. Brain 141:3233-3248
Ogren, Jennifer A; Tripathi, Raghav; Macey, Paul M et al. (2018) Regional cortical thickness changes accompanying generalized tonic-clonic seizures. Neuroimage Clin 20:205-215
Ihara, Ryoko; Vincent, Benjamin D; Baxter, Michael R et al. (2018) Relative neuron loss in hippocampal sclerosis of aging and Alzheimer's disease. Ann Neurol 84:741-753
Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872
Sutphen, Courtney L; McCue, Lena; Herries, Elizabeth M et al. (2018) Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer's disease. Alzheimers Dement 14:869-879

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