This proposal is a competing renewal of our current research project. Neuropathological changes related to Alzheimer's Disease (AD) may begin 20 to 30 years before the onset of clinical symptoms in individuals at great risk. AD affects an estimated 4.5 million Americans and is expected to affect as many as 16 million Americans by 2050, as the baby boomers reach the age at which they are most at risk. It is of major concern to explore and develop new technologies for the early detection of AD in order to facilitate disease prevention, diagnosis, and effective treatment. The goal of this RO1 proposal is to develop an innovative imaging technology for the early detection of AD. We propose a new composite MRI Neuroimaging (MRN) Index, obtained by quantitatively combining two fMRI measurements: Functional Connectivity Index (FCI) and Regional Cerebral Blood Flow (rCBF)-Perfusion Deficits at the resting-state condition. To validate this Index as a marker, we first test whether it can cross-sectionally distinguish mild AD from cognitive normal (CN) subjects and distinguish mild AD from other types of non-AD dementia, such as frontotemporal dementia (FTD) and vascular dementia (VaD). Second, we test whether the MRN Index can retroactively predict mild cognitive impairment (MCI) subjects who converted to AD from those who did not. Third, we will determine the dynamic characteristics of the MRN Index in predicting the onset of AD dementia in MCI subjects during the longitudinal studies.

Public Health Relevance

This proposal is a competing renewal of our current research project. Neuropathological changes related to Alzheimer's Disease (AD) may begin 20 to 30 years before the onset of clinical symptoms in individuals at great risk. AD affects an estimated 4.5 million Americans and is expected to affect as many as 16 million Americans by 2050, as the baby boomers reach the age at which they are most at risk. It is of major concern to explore and develop new technologies for the early detection of AD in order to facilitate disease prevention, diagnosis, and effective treatment. The goal of this proposal is to develop an innovative imaging technology for the early detection of AD. We propose a new composite MRI Neuroimaging (MRN) Index, obtained by quantitatively combining two functional MRI measurements: Functional Connectivity Index (FCI) and Regional Cerebral Blood Flow (rCBF)-Perfusion Deficits at the resting-state condition. We will employ the MRN index to distinguish mild cognitive impaired subjects who are destined to develop AD from individuals evidencing the normal aging processes or converting to different types of dementia.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG020279-09
Application #
8217106
Study Section
Clinical Neuroscience and Neurodegeneration Study Section (CNN)
Program Officer
Hsiao, John
Project Start
2001-12-01
Project End
2014-01-31
Budget Start
2012-02-15
Budget End
2013-01-31
Support Year
9
Fiscal Year
2012
Total Cost
$296,515
Indirect Cost
$101,439
Name
Medical College of Wisconsin
Department
Biophysics
Type
Schools of Medicine
DUNS #
937639060
City
Milwaukee
State
WI
Country
United States
Zip Code
53226
Chen, Guangyu; Shu, Hao; Chen, Gang et al. (2016) Staging Alzheimer's Disease Risk by Sequencing Brain Function and Structure, Cerebrospinal Fluid, and Cognition Biomarkers. J Alzheimers Dis 54:983-993
Shu, Hao; Shi, Yongmei; Chen, Gang et al. (2016) Opposite Neural Trajectories of Apolipoprotein E ϵ4 and ϵ2 Alleles with Aging Associated with Different Risks of Alzheimer's Disease. Cereb Cortex 26:1421-9
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Xie, Chunming; Li, Wenjun; Chen, Gang et al. (2013) Late-life depression, mild cognitive impairment and hippocampal functional network architecture. Neuroimage Clin 3:311-20
Chen, Guangyu; Zhang, Hong-Ying; Xie, Chunming et al. (2013) Modular reorganization of brain resting state networks and its independent validation in Alzheimer's disease patients. Front Hum Neurosci 7:456

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