The Knight ADRC has supported many investigators at Washington University and at other institutions over the years. We wish to avoid the situation where two investigators study the same research question to avoid duplication of effort and potential conflict. To determine if your topic has already been studied with our resources, please search our database. If you find that your topic or a related topic has been submitted, you may wish to contact the investigator to inquire about their findings to determine how you might proceed. You may wish to collaborate or modify your request to avoid overlap. The results below reflect requests made since online requests have been accepted. As such, not all fields will have data as certain information, such as aims, were not collected until recently. If an entry has been assigned an ID number (e.g. T1004), the full request has been submitted and is either approved, disapproved or in process. If an entry has no ID number, then it represents a submission that has not yet been reviewed. Search terms are applied across an entire requests application including variables not displayed below. A more specific, detailed search may yield better results depending upon your needs.
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Investigator: Yen Ying Lim
Project Title: Proposal for Access to the Adult Children Study (ACS) Database to investigate the effect of BDNF Val66Met on memory function, hippocampal volume, Aβ and tau across the lifespan
Date: December 21, 2021 at 5:18 pm
Request ID: D1713
Aim 1: Examine the effect of BDNF Val66Met on memory, hippocampal volume, and tau across the lifespan by modelling age as a time-continuous variable
Aim 2: In a subset of individuals who have undergone biomarker assessment for Aβ, examine the interactive effects of Aβ and BDNF Val66Met on memory, hippocampal volume and tau across the lifespan
Aim 3: Determine whether there is a gene-dose effect of BDNF Val66Met on memory, hippocampal volume and tau in cognitively normal older adults cross-sectionally and prospectively.
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Investigator: Tammie Benzinger, M.D. Ph.D.
Project Title: Development of a multi-modality deep convolutional neural network feature extraction algorithm for prediction of longitudinal biomarker evolution in Alzheimer�s disease.
Date: December 21, 2021 at 5:18 pm
Request ID: D1714
Aim 1: Develop and implement an in-lab processing pipeline for using deep neural networks for analysis of cross-sectional and longitudinal MRI, PET, clinical, and psychometric data, with both single and multi-modality implementations.
Aim 2: Replicate findings from previous studies showing successful cross-sectional disease-state classification of subjects using single modality (volumetric MRI) and multi-modality data in the DIAN, Knight ADRC, ADNI reprocessed, and AIBL reprocessed (when available) cohorts.
Aim 3: Utilize the developed platform for deeper exploration of the dynamics of Alzheimer�s biomarkers between ADAD and LOAD cohorts.
Aim 4: Explore the utility of deep neural networks for examining longitudinal relationships between biomarkers and disease progression.
Investigator: Jianguo Sun
Project Title: Identifification and Prediction of Longutudinal Biomarkers and Survival Events for Aging and Alzheimer’s disease
Date: December 21, 2021 at 5:18 pm
Request ID: D1708
Aim 1: Develop new and novel statistical models and procedures for identifying longitudinal biomarkers that are related to aging or Alzheimer’s disease and can be used to predict the onset of the disease or its related symptoms.
Aim 2: Specific Aim 2: Aim 2: Develop new and novel statistical models and procedures for joint analysis of longitudinal biomarkers and survival events or symptoms related to aging or Alzheimer’s disease that can take into account the possible existence of informative examination scheme and/or dropout.
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Investigator: Thomas Liebmann
Project Title: Validation of quantitative virtual microscopy as a novel tool for early detection of neurodegeneration and Alzheimer’s disease from magnetic resonance imaging data
Date: December 21, 2021 at 5:18 pm
Request ID: D1707
Aim 1: Establish diagnosis accuracy on confirmed Alzheimer’s disease patient MRI scans using quantitative virtual microscopy
Aim 2: Establish early detection accuracy for discriminating pre-symptomatic degeneration from non-degenerating healthy individuals using quantitative virtual microscopy analysis on MRI scans
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Investigator: Anne Fagan
Project Title: Roche Elecsys automated CSF assay for Ab42, tau and ptau181
Date: December 21, 2021 at 5:18 pm
Request ID: D1706
Aim 1: Evaluate the correspondence between CSF Elecsys data and amyloid PET
Aim 2: Evaluate the ability of CSF Elecsys data to predict cognitive decline
Aim 3: Evaluate the ability of CSF Elecsys data to discriminate clinical groups
Aim 4: Evaluate the analytical performance between Elecsys and INNOTEST CSF data
Investigator: Catherine roe
Project Title: Preliminary data for Mike Wiener project on behalf of JCM
Date: December 21, 2021 at 5:18 pm
Request ID: D1705
Aim 1: To compare ability of AD8 and CDR to predict AD dementia
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Investigator: Jee-young Han
Project Title: Clinical outcomes and its predictors in CDR 0.5, uncertain dementia
Date: December 21, 2021 at 5:18 pm
Request ID: D1704
Aim 1: To define and differentiate clinical characteristics of CDR 0.5, uncertain dementia
Aim 2: To demonstrate the clinical outcomes of CDR 0.5, uncertain dementia
Aim 3: To determine predictors of progression of CDR 0.5, uncertain dementia to AD
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Investigator: Arnaud Charil
Project Title: Potential usage of diffusion basis spectrum imaging (DBSI) to assess white matter inflammation in Alzheimer�s disease
Date: December 21, 2021 at 5:18 pm
Request ID: D1703
Aim 1: Generate a normative profile (across brain regions/tracts and subjects) of DBSI parameters, suitable for expressing (defining) �abnormal� levels of these parameters
Aim 2: Explore the profile of abnormalities in the different DBSI parameters in more advanced NIA-AA stage individuals
Aim 3: Refine potential analysis strategies for application to clinical trials
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Investigator: Sergey Shcherbinin
Project Title: Potential usage of PET-based perfusion measurements as candidates neurodegeneration biomarkers
Date: December 21, 2021 at 5:18 pm
Request ID: D1702
Aim 1: Analyze dynamic PET images obtained using different radiotracers
Aim 2: Optimize time window to measure perfusion using PET tracers
Aim 3: Perform cross-sectional and longitudinal comparison between perfusion measures and other biomarkers/scores
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Investigator: Samantha Allison
Project Title: Relationship between proton pump inhibitors and risk of dementia, cognition, brain structure, and Alzheimer disease biomarkers
Date: December 21, 2021 at 5:18 pm
Request ID: D1701
Aim 1: Examine the relationship between proton pump inhibitors and both risk of dementia and longitudinal change in cognition.
Aim 2: Examine the relationship between proton pump inhibitors and biological markers of Alzheimer disease (e.g., regional based brain volumes obtained via structural MRI, amyloid PET, and CSF biomarkers).
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