Structural MR and amyloid PET imaging have been proposed by the National Institute on Aging as methods to subdivide preclinical Alzheimer Disease (AD) into discrete stages of (1) amyloidosis, followed by (2) amyloidosis plus neurodegeneration, both of which precede (3) subtle cognitive decline, followed by the clinical progression to mild cognitive impairment (MCI) and AD dementia. The HASD Imaging Core will provide MR and PET support to the HASD Projects to test how these proposed stages relate to the transition for normal to impaired cognitive performance (Project 1), sleep disturbance (Project 2), and genetic analyses (Project 3). The following Specific Aims will be pursued: I. Combined PET-MR scanning for brain structure, function, and amyloid pathology. For the entire combined HASD and ADRC cohorts, we will perform brain MRI and florbetapir F18 (AV45) amyloid imaging every three years (200 participants/year). II. Provide data processing for these imaging tests, to include (2a) matched regional volumes, thicknesses, and quantitative PET analyses, (2b) quantitative individual longitudinal participant reports compared normative values generated by the cohort, and (2c) grouped regional reports based on classifications derived from the Projects and Cores. III. Generate an online accessible resource containing source imaging (DICOM), processed imaging, and clinical and biomarker characterization to facilitate data sharing outside of our institution, including contributions to the private-public partnership developed by JC Morris, HASD PI, and T. Benzinger, HASD Imaging Core Leader, with Avid/Lilly. This partnership allows funding for longitudinal MR and amyloid PET imaging for the entire cohort.
Core E: Imaging Project Narrative As instructed by the funding opportunity announcement for this application (PAR-13-329), only the Overall component contains a project narrative. Cores and projects were instructed not to include this section.
|Adel, Tameem; Cohen, Taco; Caan, Matthan et al. (2017) 3D scattering transforms for disease classification in neuroimaging. Neuroimage Clin 14:506-517|
|Schindler, Suzanne E; Jasielec, Mateusz S; Weng, Hua et al. (2017) Neuropsychological measures that detect early impairment and decline in preclinical Alzheimer disease. Neurobiol Aging 56:25-32|
|Zhao, Yue; Raichle, Marcus E; Wen, Jie et al. (2017) In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging. Neuroimage 148:296-304|
|Su, Yi; Vlassenko, Andrei G; Couture, Lars E et al. (2017) Quantitative hemodynamic PET imaging using image-derived arterial input function and a PET/MR hybrid scanner. J Cereb Blood Flow Metab 37:1435-1446|
|Deming, Yuetiva; Li, Zeran; Kapoor, Manav et al. (2017) Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers. Acta Neuropathol 133:839-856|
|Day, Gregory S; Lim, Tae Sung; Hassenstab, Jason et al. (2017) Differentiating cognitive impairment due to corticobasal degeneration and Alzheimer disease. Neurology 88:1273-1281|
|Monsell, Sarah E; Mock, Charles; Fardo, David W et al. (2017) Genetic Comparison of Symptomatic and Asymptomatic Persons With Alzheimer Disease Neuropathology. Alzheimer Dis Assoc Disord 31:232-238|
|Mez, Jesse; Chung, Jaeyoon; Jun, Gyungah et al. (2017) Two novel loci, COBL and SLC10A2, for Alzheimer's disease in African Americans. Alzheimers Dement 13:119-129|
|Khajehnejad, Moein; Saatlou, Forough Habibollahi; Mohammadzade, Hoda (2017) Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning. Brain Sci 7:|
|Holth, Jerrah; Patel, Tirth; Holtzman, David M (2017) Sleep in Alzheimer's Disease - Beyond Amyloid. Neurobiol Sleep Circadian Rhythms 2:4-14|
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