This Is an Alzheimer's Disease Core Center (ADCC) application from investigators at the University of Kansas (KU). Over the past five years the KU team has developed the infrastructure needed to host an ADCC. Longitudinally characterized Alzheimer's disease (AD) and age-matched control cohorts have been established and these cohorts have supported numerous research projects. Our research cohorts have been characterized neuropsychologically per Uniform Data Set (UDS) guidelines and neuroimaged at a research-dedicated neuroimaging Center. Every step has been planned in conjunction with expert statistical support and database management input. Carefully orchestrated outreach to the lay population and local healthcare professionals has facilitated subject recruitment, retention, and raised awareness of our AD research program throughout the Kansas City (KC) metro area, the 29th largest metro area in the USA. The KU ADCC consists of the five NIA-mandated ADCC cores, a Neuroimaging Core, and a Mitochondrial Genomics and Metabolism Core. This infrastructure helps us pursue our principal aim of effectively and comprehensively supporting AD and AD-related research at KU. To this end KU ADCC services have already invigorated KU's AD research portfolio and we currently maintain a diverse portfolio of supported research projects.
A second aim of the KU ADCC is to provide advanced services that enable and facilitate ground-breaking AD, AD-related, and brain aging metabolism research. Our expertise and the highly integrated, Inter-disciplinary services we provide will help the AD research field define how fitness, metabolism, and mitochondria independently and collectively influence progression and outcome in AD. We are confident that incorporating our expertise within the ADC system will prove both practical and valuable, strengthen the existing ADC system, and advance the AD research field.

Public Health Relevance

With the aging population, age-related disorders such as dementia are rising in prevalence at an unprecedented rate. Promoting and supporting clinical and translational research into neurodegenerative disorders may lead to important prevention and treatment strategies.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Center Core Grants (P30)
Project #
5P30AG035982-02
Application #
8316139
Study Section
Special Emphasis Panel (ZAG1-ZIJ-5 (M2))
Program Officer
Silverberg, Nina B
Project Start
2011-08-15
Project End
2016-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
2
Fiscal Year
2012
Total Cost
$1,270,948
Indirect Cost
$443,477
Name
University of Kansas
Department
Neurology
Type
Schools of Medicine
DUNS #
016060860
City
Kansas City
State
KS
Country
United States
Zip Code
66160
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
Gupte, Raeesa; Christian, Sarah; Keselman, Paul et al. (2018) Evaluation of taurine neuroprotection in aged rats with traumatic brain injury. Brain Imaging Behav :
Burns, Nicole C; Watts, Amber; Perales, Jaime et al. (2018) The Impact of Creative Arts in Alzheimer's Disease and Dementia Public Health Education. J Alzheimers Dis 63:457-463
Williams, Kristine; Blyler, Diane; Vidoni, Eric D et al. (2018) A randomized trial using telehealth technology to link caregivers with dementia care experts for in-home caregiving support: FamTechCare protocol. Res Nurs Health 41:219-227
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
Cirstea, Carmen M; Lee, Phil; Craciunas, Sorin C et al. (2018) Pre-therapy Neural State of Bilateral Motor and Premotor Cortices Predicts Therapy Gain After Subcortical Stroke: A Pilot Study. Am J Phys Med Rehabil 97:23-33
Alosco, Michael L; Sugarman, Michael A; Besser, Lilah M et al. (2018) A Clinicopathological Investigation of White Matter Hyperintensities and Alzheimer's Disease Neuropathology. J Alzheimers Dis 63:1347-1360

Showing the most recent 10 out of 333 publications