White matter integrity is critical to cognitive functions. Using diffusion-tensor imaging (DTI), it is now possible to directly assess the pattern and severity of white matter disruption in the early stages of dementia. This proposal considers the role of white matter tracts in AD and in subcortical vascular dementia (SVD). The hypotheses will examine whether: a) SVD initially disrupts frontal-subcortical loops, whereas in AD long cortical-cortical connections incur damage later and in addition to damage to the perforant pathway, b) fronto-occipital connectivity and thalamo-frontal connectivity correlate with MRI determined volumes of hippocampii, frontal cortical gray matter, and white matter hyperintensities (WMH), and c) fronto-occipital connectivity and thalamo-frontal connectivity correlate with severity of cognitive impairment (as assessed by global cognitive ability, memory, and executive function) using hippocampal volume and apoE as covariates. A cohort of 60 subjects divided into three groups, normal controls (NC), AD and SVD will be studied. The AD group will include persons with mild amnestic-type cognitive impairment (MCI) as well as probable AD. The SVD group will include persons with vascular cognitive impairment (VCI), as well as dementia meeting criteria for probable or possible VD (vascular dementia) or mixed AD/VD. Recruitment and follow-up of subjects and quantitative MRI will use resources from the ADRC Clinical and Imaging Cores, as well as the ischemic vascular dementia (IVD) Program Project Stet. Subjects will undergo MRI and neuropsychological testing at baseline and again after an interval of two years. Structural images will be segmented for volumetric analyses of selected regions. Diffusion weighted images will be converted into fractional anisotropy maps for DTI-Tractography. Connectivity will be quantified through metrics representing a normalized count of tracts between selected regions and the distribution of fractional anisotropy along these tracts.The connectivity metrics, volumetric analyses and neuropsychological scores will be used to test the hypotheses.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Specialized Center (P50)
Project #
5P50AG005142-24
Application #
7437352
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2007-04-01
Budget End
2008-03-31
Support Year
24
Fiscal Year
2007
Total Cost
$236,751
Indirect Cost
Name
University of Southern California
Department
Type
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Ramsey, Christine M; Gnjidic, Danijela; Agogo, George O et al. (2018) Longitudinal patterns of potentially inappropriate medication use following incident dementia diagnosis. Alzheimers Dement (N Y) 4:1-10
Sweeney, Melanie D; Kisler, Kassandra; Montagne, Axel et al. (2018) The role of brain vasculature in neurodegenerative disorders. Nat Neurosci 21:1318-1331
Nation, Daniel A (2018) Blood Pressure and Cerebral Blood Flow in Alzheimer Disease. Hypertension 72:68-69
Hadjichrysanthou, Christoforos; McRae-McKee, Kevin; Evans, Stephanie et al. (2018) Potential Factors Associated with Cognitive Improvement of Individuals Diagnosed with Mild Cognitive Impairment or Dementia in Longitudinal Studies. J Alzheimers Dis 66:587-600
Hanfelt, John J; Peng, Limin; Goldstein, Felicia C et al. (2018) Latent classes of mild cognitive impairment are associated with clinical outcomes and neuropathology: Analysis of data from the National Alzheimer's Coordinating Center. Neurobiol Dis 117:62-71
Burke, Shanna L; Hu, Tianyan; Fava, Nicole M et al. (2018) Sex differences in the development of mild cognitive impairment and probable Alzheimer's disease as predicted by hippocampal volume or white matter hyperintensities. J Women Aging :1-25
Wang, Qi; Guo, Lei; Thompson, Paul M et al. (2018) The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation1. J Alzheimers Dis 64:149-169
Wang, Tingyan; Qiu, Robin G; Yu, Ming (2018) Predictive Modeling of the Progression of Alzheimer's Disease with Recurrent Neural Networks. Sci Rep 8:9161
Agogo, George O; Ramsey, Christine M; Gnjidic, Danijela et al. (2018) Longitudinal associations between different dementia diagnoses and medication use jointly accounting for dropout. Int Psychogeriatr 30:1477-1487
Aydogan, Dogu Baran; Jacobs, Russell; Dulawa, Stephanie et al. (2018) When tractography meets tracer injections: a systematic study of trends and variation sources of diffusion-based connectivity. Brain Struct Funct 223:2841-2858

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