The chief function of the Neuropathology Core (NC) is to provide state of the art diagnostic services, to set up and maintain a collection of optimally prepared brain samples, and to supply samples for cutting edge research to investigators of the Center, affiliated Centers, and to outside neuroscientists conducting research into neurodegenerative diseases. Because humans are the only known species to naturally develop Alzheimer disease (AD) or related illnesses, the availability of carefully prepared postmortem samples is essential despite the existence of valuable transgenic animal models. Thus, human tissue-dependent studies require that the diagnostic categorization of samples of interest is as accurate as possible. This tissue must be made available quickly following the receipt of a request to enhance laboratory efficiency and productivities. Therefore, the specific aims of NC are: 1. To establish an accurate diagnosis on all brains obtained for the Center including clinico-pathological interpretations of the findings, which are recorded within two standardized reports;a) a text-based for clinicians and medical files, and b) a quantification-based report. The quantification-based report provides data to the Clinical Care / Data Management, and to the National Alzheimer's Coordinating Committee (NACC) in compliance with National Institute on Aging (NIA) requirements. Furthermore, it is used for identifying the samples in storage with variables matching those specified by requestors;2. To obtain brain samples for tissue-dependent fresh frozen studies with or without requirement of cellular morphology preservation, which are ready for immediate disbursement once categorized;and formalin fixed samples;3. To organize the collection of samples, maintain it safely, and select among the samples in storage the ones that best match the requirement of a specific study with subsequent distribution within five working days from the time the receipt of the request;4. To teach clinicians, trainees, and neuroscientists the neuropathology of the dementias, and to assist in correlating findings made in transgenic animal models with those usually occurring in the human brains;and 5. To cooperate with other Centers including the National Institute of Neurological Disorders and Stroke (NINDS) supported Udall Center.

Public Health Relevance

Defining the changes underlying dementias is prerequisite for knowing how to prevent them. Therefore, brains of individuals who died at different stage of the dementia, and recording the type, extend, and distribution of the changes must be achieved to optimize the specificity of samples defined for basic research including tissue-dependent investigations aiming at disclosing the causes of dementias.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Specialized Center (P50)
Project #
5P50AG008702-24
Application #
8574146
Study Section
Special Emphasis Panel (ZAG1-ZIJ-4)
Project Start
Project End
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
24
Fiscal Year
2013
Total Cost
$206,867
Indirect Cost
$77,592
Name
Columbia University (N.Y.)
Department
Type
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
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
Zhou, Zilu; Wang, Weixin; Wang, Li-San et al. (2018) Integrative DNA copy number detection and genotyping from sequencing and array-based platforms. Bioinformatics 34:2349-2355
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
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
Brent, Robert J (2018) Estimating the monetary benefits of medicare eligibility for reducing the symptoms of dementia. Appl Econ 50:6327-6340
Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872
Winawer, Melodie R; Griffin, Nicole G; Samanamud, Jorge et al. (2018) Somatic SLC35A2 variants in the brain are associated with intractable neocortical epilepsy. Ann Neurol 83:1133-1146

Showing the most recent 10 out of 640 publications