The Data Management and Biostatistics Core (Data Core) performs data management and analysis for all six fellow cores (Administrative, Clinical, Neuropathology, Neuroimaging, Psychosocial, Education), and for individual researchers affiliated with the ADC. The Data Core maintains all data collected by the NYU ADC in a centralized database, transfers data to the National Alzheimer's Coordinating Center (NACC) to create a common database for all ADC's across the country, and offers consultation and hands-on help in experimental design and statistical analysis to all collaborating investigators in the NYU ADC. The rapid increase in the size, the type and the complexity of aging and dementia related data demands that the Data Core expand its functions in order to (1) facilitate information exchange via the Internet, and (2) introduce, apply and develop novel statistical methods for comprehensive data analysis. Data Core Specific Aims are: 1. Continue to provide our traditional data management and statistical consultation services which include managing and updating the centralized Center database, offering consultation on experimental design and statistical analysis, and maintaining close collaboration with the NACC in the implementation and utilization of the uniform data set (UDS) for all ADC's. 2. Further develop and maintain a secure Web-based database, conforming to the institutional standards set by NYU, for multi-user on-line information exchange within the Center and between Centers, NACC and other collaborators. We are upgrading our Visual FoxPro database server to a modern web-based health care management software (clinical database plus clinical management) ? Velos, sponsored by NYU. 3. Actively initiate, develop, participate in and direct statistical analyses within and between our fellow cores/centers. Data Core analysts (including student trainees) are assigned to fellow cores to increase mutual interactions and understanding, and foster close collaborations in the design of ADC related studies and the analysis of ADC data. Data Core leader conducts biweekly meetings with Core analysts and ADC researchers interested in collaborative analysis. We also actively participate in research paper writing. 4. Educate Center affiliated researchers on database utilization and related statistical analysis methods. This has been and will continuously be achieved through a comprehensive internet site with detailed education topics and on-line help as well as monthly statistics seminar. 5. Actively participate in as well as lead grant applications to further increase Data Core funding levels.

Public Health Relevance

Data Core is critical in the function of the entire ADC. We maintain the entire ADC database and ADC computer system. We offer statistical consultation, education and collaboration for ADC affiliated research projects. We provide timely feedback to each core in terms of data/sample collection to ensure quality, quantity and diversity of ADC data/samples. We are the link between our ADC and NACC on data exchange.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Center Core Grants (P30)
Project #
5P30AG008051-23
Application #
8468478
Study Section
Special Emphasis Panel (ZAG1-ZIJ-4)
Project Start
Project End
Budget Start
2012-05-15
Budget End
2013-04-30
Support Year
23
Fiscal Year
2012
Total Cost
$324,616
Indirect Cost
$115,049
Name
New York University
Department
Type
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016
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
de Leon, Mony J; Pirraglia, Elizabeth; Osorio, Ricardo S et al. (2018) The nonlinear relationship between cerebrospinal fluid A?42 and tau in preclinical Alzheimer's disease. PLoS One 13:e0191240
Lakshmanan, Karthik; Brown, Ryan; Madelin, Guillaume et al. (2018) An eight-channel sodium/proton coil for brain MRI at 3 T. NMR Biomed 31:
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
Herline, Krystal; Prelli, Frances; Mehta, Pankaj et al. (2018) Immunotherapy to improve cognition and reduce pathological species in an Alzheimer's disease mouse model. Alzheimers Res Ther 10:54
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

Showing the most recent 10 out of 604 publications