CORE C: ABSTRACT This ADRC has comprehensive and demanding translational research objectives, for which the Data Management and Statistics (DMS) core must be able to efficiently collect, validate, integrate, and derive meaning from a complex array of data. Key questions about diagnosis, clinical features, natural history, interactions between genotype and phenotype, clinico-pathological relationships, and connections between structural and functional brain changes and neurobehavioral disturbances can only be addressed with sophisticated and comprehensive data structures, and with the support of a cohesive team of expert statistical personnel. Thus, the DMS Core for this ADRC has a particular mandate to support and facilitate our researchers'ability to link the complex, multilevel data we collect, and to approach that data with the sophisticated and appropriate recommendations for research design and analytic methods. In the next phase of this ADRC, we will incorporate new innovations to the DMS that will enable our researchers to better identify and integrate multilevel data collected through the ADRC, while enabling us to link ADRC data with other resources at UCSF. Historically, the UCSF Memory and Aging Center (MAC) has shown national leadership in developing data management systems that integrate a wealth of information from a variety of sources in order to better understand the etiology and treatment of dementia syndromes and promote translational research. The core mandate of this DMS is to ensure that: (1) the measurement of behavioral, cognitive, neurological, imaging and genetic information is supported by scientifically sound techniques that result in a consistent classification of information (i.e., results are reliable and reproducible);(2) that the observed phenomena are accurately recorded and reflected in the database;(3) that the database is secure, preventing unauthorized changes;(4) that analytical data sets are easily accessible to collaborating investigators within and beyond the ADRC;and (5) that meaningful patterns in the data are identified using appropriate and efficient research design and statistical methods. We plan to augment these core functions by elaborating our representation of multiple levels of neurological information in order to improve our ability to model complex patterns and associations in our patients. We have also enhanced our plan for delivery of statistical consultation and have added biostatistical personnel. These improvements will build upon the solid foundation that we have established, and ensure that we will continue to provide the program structure required for the highest level of data collection, management, quality control, and timely NACC data submission.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Specialized Center (P50)
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Special Emphasis Panel (ZAG1-ZIJ-4 (J1))
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University of California San Francisco
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