We hypothesize that Alzheimer's disease (AD) has a preclinical stage in which elevated levels of brain amyloid protein and accumulation of beta-amyloid deposits foreshadow the gradual onset of neuronal dysfunction, cell loss and dementia. While the exact role of amyloid in the initiation of brain damage is still unclear, clarifying the exact timing of amyloid deposition that precede AD would be extremely helpful in understanding the biological origins of AD and in designing appropriate interventions. Brain imaging provides a window into many of the hypothesized biochemical, functional and anatomic changes in AD. With Positron Emission Tomography (PET) using [11C]PIB it is possible to estimate the density of beta-amyloid plaques by imaging the PIB binding sites. With PET using [18F]FDG it is possible to estimate neuronal function from measures of metabolic activity. Finally, with magnetic resonance imaging (MRI) volume loss over time can be quantified in regional and global brain measures. It is our premise that by examining the temporal and spatial interrelationships between these three measures important insights will be gained in the pathophysiology of AD. The value of these imaging biomarkers are further enhanced by combining the data with CSF biomarkers and clinical and psychometric data. Towards these goals, the Imaging Core will provide two key support activities to the DIAN effort:
Aim 1 : Oversee the collection of all image data. This data includes MR scans for morphometrics, PET FDG scans for metabolism and PET PIB scans for imaging beta-amyloid plaques.
Aim 2 : Perform image processing and analysis to extract biologically relevant measures from the image data set. These measures include whole brain volume and cortical and subcortical regional measures of gray matter volume, relative glucose metabolism and PIB-derived estimates of beta-amyloid plaque deposition.
|Su, Yi; Flores, Shaney; Hornbeck, Russ C et al. (2018) Utilizing the Centiloid scale in cross-sectional and longitudinal PiB PET studies. Neuroimage Clin 19:406-416|
|Cruchaga, Carlos; Del-Aguila, Jorge L; Saef, Benjamin et al. (2018) Polygenic risk score of sporadic late-onset Alzheimer's disease reveals a shared architecture with the familial and early-onset forms. Alzheimers Dement 14:205-214|
|Kinnunen, Kirsi M; Cash, David M; Poole, Teresa et al. (2018) Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study. Alzheimers Dement 14:43-53|
|Lee, Seonjoo; Zimmerman, Molly E; Narkhede, Atul et al. (2018) White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer's disease. PLoS One 13:e0195838|
|Oxtoby, Neil P; Young, Alexandra L; Cash, David M et al. (2018) Data-driven models of dominantly-inherited Alzheimer's disease progression. Brain 141:1529-1544|
|Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500|
|Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank et al. (2018) Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer's disease. Brain 141:1186-1200|
|Li, Zeran; Del-Aguila, Jorge L; Dube, Umber et al. (2018) Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure. Genome Med 10:43|
|Wang, Guoqiao; Berry, Scott; Xiong, Chengjie et al. (2018) A novel cognitive disease progression model for clinical trials in autosomal-dominant Alzheimer's disease. Stat Med 37:3047-3055|
|Vlassenko, Andrei G; Gordon, Brian A; Goyal, Manu S et al. (2018) Aerobic glycolysis and tau deposition in preclinical Alzheimer's disease. Neurobiol Aging 67:95-98|
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