Abstract

The Statistics and Data Management Core is a dedicated group of statistical and database personnel whose expertise supports research in normal aging, Alzheimer's disease and related dementias at U.T. Southwestern (UTSW) and for national (National Alzheimer's Coordinating Center) and state efforts (Texas Alzheimer's Research Consortium).
The Specific Aims of the Statistics and Data Management Core are: (1). Provide statistical and data management support for investigators, fellows and graduate students doing research in normal aging, Alzheimer's disease and related dementias as well as training for those researchers in the design and analysis of clinical studies. Participate in study development, analyses, posters and manuscripts. ( 2). Statistics and data base support. Statisticians with biomarker analysis expertise will provide analyses using state of the art techniques. Analyses of imaging data will involve collaboration with our colleagues in the Clinical Core using specialized techniques they have developed. (3). Participate in national and state efforts related to normal aging, Alzheimer's disease and related dementias. We submit our subject data to NACC on a regular and timely basis. Our Core continues to provide leadership at the national level: Joe Webster served on an advisory committee in the early years and Joan Reisch was selected as a member of the first Data Advisory Board for NACC. Currently Dr. Linda Hynan serves on the NACC Publications committee (2009-2011);Dr. Reisch participates in the semi-annual meetings of ADC directors.

Public Health Relevance

The development of successful therapies for Alzheimer's disease (AD) will require a thorough understanding of the pathologic mechanisms that contribute to neurodegeneration. Data from epidemiologic and observational studies indicates that vascular and inflammatory pathology contributes to AD. The goal of the UTSW ADC is to identify biomarkers of vascular and inflammatory pathology that will be useful for selection of participants in clinical trials.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Center Core Grants (P30)
Project #
5P30AG012300-18
Application #
8382574
Study Section
Special Emphasis Panel (ZAG1-ZIJ-5)
Project Start
Project End
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
18
Fiscal Year
2012
Total Cost
$213,211
Indirect Cost
$91,603

  Institution

Name
University of Texas Sw Medical Center Dallas
Department
Type
DUNS #
800771545
City
Dallas
State
TX
Country
United States
Zip Code
75390

  Publications

Ramsey, Christine M; Gnjidic, Danijela; Agogo, George O et al. (2018) Longitudinal patterns of potentially inappropriate medication use following incident dementia diagnosis. Alzheimers Dement (N Y) 4:1-10
Hadjichrysanthou, Christoforos; McRae-McKee, Kevin; Evans, Stephanie et al. (2018) Potential Factors Associated with Cognitive Improvement of Individuals Diagnosed with Mild Cognitive Impairment or Dementia in Longitudinal Studies. J Alzheimers Dis 66:587-600
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
Stallings, Nancy R; O'Neal, Melissa A; Hu, Jie et al. (2018) Pin1 mediates A?42-induced dendritic spine loss. Sci Signal 11:
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
Ding, Kan; Tarumi, Takashi; Zhu, David C et al. (2018) Cardiorespiratory Fitness and White Matter Neuronal Fiber Integrity in Mild Cognitive Impairment. J Alzheimers Dis 61:729-739
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

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