The Administration Core acts to ensure that the research and programmatic goals of the Adult Children Study program project grant (ACS PPG) are met. The administrative leadership consists of the Director (Morris) and the Executive Director (Buckles). They are assisted by the Executive Committee that includes these individuals, leaders of Cores and Projects, and other senior faculty. The Administration Core supports, monitors, and coordinates the activities of all components of the ACS PPG. It will annually convene an External Advisory Committee to review activities and progress.
The specific aims are to: 1. Coordinate and integrate the Cores and Projects and provide administrative and budgetary support and oversight, ensuring appropriate utilization of funds 2. Monitor the effectiveness of the PPG toward achieving the stated goals 3. Arrange for periodic external review and advice concerning PPG goals and progress 4. Coordinate and oversee data integration with Washington University Center for Biomedical Informatics to develop, maintain, and monitor an integrated database

Public Health Relevance

The Administration Core ensures that goals of the Adult Children Study (ACS) are met, including identifying the earliest brain changes of AD, determining the evolution of these changes overtime, and assessing their predictive power for the eventual development of symptomatic AD. With the assistance of an External Advisory Committee and an Executive Committee including the leaders of the Projects and Cores, the Administration Core supports, monitors, and coordinates the activities of all components of the ACS.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Program Projects (P01)
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Special Emphasis Panel (ZAG1-ZIJ-4)
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Washington University
Saint Louis
United States
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Chen, Ling; Sun, Jianguo; Xiong, Chengjie (2016) A multiple imputation approach to the analysis of clustered interval-censored failure time data with the additive hazards model. Comput Stat Data Anal 103:242-249
Staley, Lyndsay A; Ebbert, Mark T W; Parker, Sheradyn et al. (2016) Genome-wide association study of prolactin levels in blood plasma and cerebrospinal fluid. BMC Genomics 17 Suppl 3:436
Staley, Lyndsay A; Ebbert, Mark T W; Bunker, Daniel et al. (2016) Variants in ACPP are associated with cerebrospinal fluid Prostatic Acid Phosphatase levels. BMC Genomics 17 Suppl 3:439
Ingber, Adam P; Hassenstab, Jason; Fagan, Anne M et al. (2016) Cerebrospinal Fluid Biomarkers and Reserve Variables as Predictors of Future ""Non-Cognitive"" Outcomes of Alzheimer's Disease. J Alzheimers Dis 52:1055-64
Gordon, Brian A; Blazey, Tyler; Su, Yi et al. (2016) Longitudinal β-Amyloid Deposition and Hippocampal Volume in Preclinical Alzheimer Disease and Suspected Non-Alzheimer Disease Pathophysiology. JAMA Neurol 73:1192-1200
Babulal, Ganesh M; Ghoshal, Nupur; Head, Denise et al. (2016) Mood Changes in Cognitively Normal Older Adults are Linked to Alzheimer Disease Biomarker Levels. Am J Geriatr Psychiatry 24:1095-1104
Jack Jr, Clifford R; Knopman, David S; Chételat, Gaël et al. (2016) Suspected non-Alzheimer disease pathophysiology--concept and controversy. Nat Rev Neurol 12:117-24
Ebbert, Mark T W; Staley, Lyndsay A; Parker, Joshua et al. (2016) Variants in CCL16 are associated with blood plasma and cerebrospinal fluid CCL16 protein levels. BMC Genomics 17 Suppl 3:437
Lucey, Brendan P; Mcleland, Jennifer S; Toedebusch, Cristina D et al. (2016) Comparison of a single-channel EEG sleep study to polysomnography. J Sleep Res 25:625-635
Cummings, Jeffrey; Aisen, Paul S; DuBois, Bruno et al. (2016) Drug development in Alzheimer's disease: the path to 2025. Alzheimers Res Ther 8:39

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