The major goals of this Alzheimer's Disease Neuroimaging Initiative (ADNI) are to: 1) Develop improved methods, which will lead to uniform standards for acquiring longitudinal, multi-site Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) data on patients with Alzheimer's disease (AD), mild cognitive impairment (MCI), and elderly controls. 2) Acquire a generally accessible data repository, which describes longitudinal changes in brain structure and metabolism. In parallel, acquire clinical, cognitive and biomarker data for validation of imaging surrogates. 3) Determine those methods which provide maximum power to determine treatment effects in trials involving these patient groups. A team of investigators with considerable experience in AD clinical trials, MRI, PET, biomarkers and informatics has been assembled. Study design is in response to the Request For Applications (RFA). The first six months of the project will be devoted to establishing uniform MRI and PET acquisition techniques at all of the 40-45 participating sites, followed by initiation of subject recruitment. Improved methods for MRI and PET quantification will be assessed and implemented if useful. All subjects will have clinical/cognitive assessments and 1.5 T structural MRI every 6 months for 2-3 years. Approximately 50% of subjects will also have 18fluorodeoxyglucose (FDG) PET scans at the same time intervals and 25% of subjects (who do not also have PET) will have MRI at 3 Tesla. AD subjects (n=200) will be studied at 0, 6, 12, 18, and 24 months. MCI subjects at high risk for conversion to AD (n= 400) will be studied at 0, 6, 12, 18, 24, 30, and 36 months. Age matched controls (n=200) will be studied at 0, 6, 12, and 24 months. All MRI and PET scans will be rapidly assessed for quality by the MRI and PET components of the Neuroimaging Center so that subjects may be rescanned if necessary. All clinical data will be collected, monitored, and stored by the Clinical Center at the AD Cooperative Studies program at the University of California San Diego (UCSD). The University of Pennsylvania (UPenn) will collect biomarker samples. All raw and processed image data will be archived at The Laboratory of Neuroimaging (LONI) at the University of California Los Angeles (UCLA). Pilot studies will evaluate different image processing methods to measure brain regions of interest. All data will be monitored and analyzed by project statisticians, and data base queries will be performed on request. All clinical, cognitive, imaging, and biomarker databases will be linked and all raw, processed, and statistically analyzed data will be fully and rapidly accessible to the public through the Internet. The results of this study will be extremely useful for design of future AD and MCI trials.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01AG024904-01S2
Application #
7099219
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Buckholtz, Neil
Project Start
2004-09-30
Project End
2009-08-31
Budget Start
2005-08-01
Budget End
2005-08-31
Support Year
1
Fiscal Year
2005
Total Cost
$2,000,000
Indirect Cost
Name
Northern California Institute Research & Education
Department
Type
DUNS #
613338789
City
San Francisco
State
CA
Country
United States
Zip Code
94121
Ben Bouallègue, Fayçal; Mariano-Goulart, Denis; Payoux, Pierre et al. (2018) Joint Assessment of Quantitative 18F-Florbetapir and 18F-FDG Regional Uptake Using Baseline Data from the ADNI. J Alzheimers Dis 62:399-408
Ishida, Takaaki; Tokuda, Keita; Hisaka, Akihiro et al. (2018) A Novel Method to Estimate Long-Term Chronological Changes From Fragmented Observations in Disease Progression. Clin Pharmacol Ther :
Amaral, Robert S C; Park, Min Tae M; Devenyi, Gabriel A et al. (2018) Manual segmentation of the fornix, fimbria, and alveus on high-resolution 3T MRI: Application via fully-automated mapping of the human memory circuit white and grey matter in healthy and pathological aging. Neuroimage 170:132-150
Li, Wei; Risacher, Shannon L; Gao, Sujuan et al. (2018) Type 2 diabetes mellitus and cerebrospinal fluid Alzheimer's disease biomarker amyloid ?1-42 in Alzheimer's Disease Neuroimaging Initiative participants. Alzheimers Dement (Amst) 10:94-98
Rane, Swati; Donahue, Manus J; Claassen, Daniel O (2018) Amnestic mild cognitive impairment individuals with dissimilar pathologic origins show common regional vulnerability in the default mode network. Alzheimers Dement (Amst) 10:717-725
Sohn, Dongwha; Shpanskaya, Katie; Lucas, Joseph E et al. (2018) Sex Differences in Cognitive Decline in Subjects with High Likelihood of Mild Cognitive Impairment due to Alzheimer's disease. Sci Rep 8:7490
Miller, Jason E; Shivakumar, Manu K; Lee, Younghee et al. (2018) Rare variants in the splicing regulatory elements of EXOC3L4 are associated with brain glucose metabolism in Alzheimer's disease. BMC Med Genomics 11:76
Buckley, Rachel F; Mormino, Elizabeth C; Amariglio, Rebecca E et al. (2018) Sex, amyloid, and APOE ?4 and risk of cognitive decline in preclinical Alzheimer's disease: Findings from three well-characterized cohorts. Alzheimers Dement 14:1193-1203
Ower, Alison K; Hadjichrysanthou, Christoforos; Gras, Luuk et al. (2018) Temporal association patterns and dynamics of amyloid-? and tau in Alzheimer's disease. Eur J Epidemiol 33:657-666
Properzi, Michael J; Buckley, Rachel F; Chhatwal, Jasmeer P et al. (2018) Nonlinear Distributional Mapping (NoDiM) for harmonization across amyloid-PET radiotracers. Neuroimage 186:446-454

Showing the most recent 10 out of 1666 publications