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: Dr. Randall Bateman
Project Title: Determining Changes in Cerebrospinal Fluid (CSF) Protein Composition as Humans Age to Search for Factors Contributing to Cognitive Health in Older Individuals
Date: August 25, 2022 at 1:17 pm
Request ID: D2218
Aim 1: Define a set of proteins in cerebrospinal fluid that vary with normal human aging.
Aim 2: Use machine learning to generate predictive models of clinical assessment scores based on proteins in the CSF that vary with age.
Aim 3: Use differential expression analysis to determine abundance differences in age related proteins in the CSF between young cognitively normal individuals, aged cognitively normal individuals, and aged pathogenic individuals.
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Investigator: BERISLAV V ZLOKOVIC
Project Title: Vascular Contributions to Dementia and Genetic Risk Factors for Alzheimer disease
Date: August 23, 2022 at 2:01 pm
Request ID: S1701
Aim 1: Evaluate longitudinally biomarkers of BBB breakdown (i.e., sPDGFRβ, CypA-MMP9 pathway, Qalb, fibrinogen) by serial CSF analysis in relation to serial Aβ and tau AD biomarker (CSF, PET) changes and cognitive decline.
Aim 2: Evaluate longitudinally BBB permeability by serial DCE-MRI measurements in relation to CSF biomarkers of BBB breakdown, Aβ and tau AD biomarker (CSF, PET) changes and cognitive decline.
Aim 3: Examine longitudinally BBB breakdown by serial DCE-MRI measurements in relation to serial CBF pCASL-MRI measurements, Aβ and tau AD biomarker (CSF, PET) changes and cognitive decline.
Aim 4: Evaluate regional BBB integrity (DCE-MRI) in relation to change in structural and functional connectivity and cognitive decline over time.
Investigator: Ganesh Babulal
Project Title: Daily Cognitive Performance and Variability in Predicting Naturalistic Driving Behavior
Date: August 23, 2022 at 11:29 am
Request ID: D2217
Aim 1: To determine if mean level differences in cognition or variability in daily cognitive performance, as measured with the Ambulatory Research in Cognition (ARC) study, mediate differences in driving behavior associated with amyloid pathology.
Aim 2: Examine whether daily cognitive performance on ARC correlates with driving behavior on the same day
Aim 3: Evaluate whether changes in driving behavior are associated with differences in cognition (mean performance and variability) measured with ARC
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Investigator: Marta Stojanovic
Project Title: The relationship between attentional control and PET-Tau
Date: August 16, 2022 at 5:14 pm
Request ID: D2216
Aim 1: Examine whether measures of attentional control predict tau deposition estimated via PET-Tau
Aim 2: Investigate whether APOE status moderates the relationship between attentional control and PET-Tau
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Investigator: Katie Saund
Project Title: Influence of AD risk variants in TREM2 on the CSF, brain, and plasma proteomes
Date: August 10, 2022 at 1:58 pm
Request ID: D2215
Aim 1: Build predictive models of TREM2 mutational status based on brain, CSF, and plasma proteomics
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Investigator: Dr. Rik Ossenkoppele
Project Title: Connectivity as a universal predictor of tau spreading in atypical AD
Date: August 10, 2022 at 4:27 am
Request ID: D2214
Aim 1: Collect and harmonize large-scale multicenter tau-PET and post-mortem data of atypical AD variants
Aim 2: Test whether higher inter-regional connectivity is associated with higher covariance in tau pathology across atypical AD variants
Aim 3: Examine whether connectivity of tau epicenters predicts AD-variant specific tau spreading sequences
Aim 4: Validate subject-specific prediction of tau spreading using longitudinal tau-PET data in atypical AD
Investigator: Tao Sun
Project Title: Tau-PET change along with Alzheimer’s disease: from a topology perspective
Date: August 3, 2022 at 1:20 am
Request ID: D2213
Aim 1: Investigate the longitudinal change of tau deposition from network perspective
Aim 2: Identify related biomarkers for early AD detection in prodromal stage
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Investigator: Tony Wyss-Coray
Project Title: ADRC Collaboration: Wyss-Coray Lab and Cruchaga Lab
Date: July 25, 2022 at 1:18 pm
Request ID: D2212
Aim 1: Validation of Organ-Specific Aging Signatures in Neurodegenerative Disease
Aim 2: Assessing CSF:Plasma Protein Ratios in Aging and Neurodegenerative Disease
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Investigator: Colin Masters
Project Title: Prof. Schindler Neurology Paper Validation using ADOPIC
Date: July 18, 2022 at 11:05 pm
Request ID: D2211
Aim 1: Validate the time at which Amyloid begins to accumulate in the brain using Prof Schindler’s method as described in her Nerorology paper using CapAIBL generated Centilid values.
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Investigator: Catherine Kaczorowski
Project Title: Systems Genetics Analysis of Alzheimer’s Disease-Related Sleep Loss and the Transition to Dementia
Date: June 27, 2022 at 4:10 pm
Request ID: D2210
Aim 1: Identify genes and molecular networks associated with sleep loss in new mouse models of human AD.
Aim 2: Translate genes and molecular networks underlying variation in sleep loss in human AD cohorts.
Aim 3: Validate genetic factors associated with AD-related sleep dysfunction and determine their impact on memory in powerful AD models.
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