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.
Search Terms:
Investigator: Ahmad Imam
Project Title: A Mixed Distributed Deep Learning Approach for Blood Sample-Based Early Detection of Alzheimer’s Disease
Date: March 17, 2023
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Aim 1: AI-based model for early detection of Dementia.
Aim 2: AI-base model to observe multiple internal and external factor that might contribute in the development of Dementia
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Investigator: John Morris
Project Title: Predicting continuous PET values with pTau isoforms (extension to include MTBR)
Date: February 23, 2023
Request ID: D2308
Aim 1: Test whether CSF pTau isoforms and/or MTBR can predict regional amyloid burden
Aim 2: Test whether CSF pTau isoforms and/or MTBR can predict regional tau burden
Aim 3: Assess the relative predictive ranges of each CSF pTau isoform and MTBR value for cortical amyloid burden and tauopathy
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Investigator: Paul Brewster
Project Title: Evaluating practice effects with burst cognitive testing and standard cognitive measures
Date: February 15, 2023
Request ID: D2307
Aim 1: The primary aim of this research is to evaluate whether individual differences in performance variability and practice effects on mobile phone-based burst cognitive testing predict Alzheimer disease (AD) biomarkers independently of performance level.
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Investigator: Joana B. Pereira
Project Title: Predicting Tau Pathology and Brain Atrophy with Deep Learning
Date: February 8, 2023
Request ID: D2306
Aim 1: Impute tau-PET images
Aim 2: Impute T1-weighted images
Aim 3: Perform cross-modal imputations
Aim 4: Assess relationship between imputations with diagnosis, cognitive scores and other imaging modality measures
Investigator: Sarah Hartz
Project Title: Prediction of AD development and progression using AD8
Date: January 17, 2023
Request ID: D2305
Aim 1: Confirm that the ability of the AD8 to discriminate between CDR=0 and CDR=0.5 does not vary by gender, race, or other demographics
Aim 2: Modify 5-year AD risk prediction models to be based on AD8 rather than CDR
Aim 3: Develop 5-year AD symptom progression model based on AD8
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Investigator: Andrew Aschenbrenner
Project Title: Comparing the sensitivity of different attentional control tasks and outcomes in preclinical Alzheimer disease
Date: January 12, 2023
Request ID: D2304
Aim 1: Compare three different attentional control tasks and 7+ outcomes to determine which task and outcome is most sensitive to preclinical AD
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Investigator: John Morris
Project Title: Evaluating tau microtubule binding region (MTBR) and tau phosphorylation as indicators of tau PET burden and spreading
Date: January 10, 2023
Request ID: D2303
Aim 1: Test whether CSF MTBR-tau and tau phosphorylation more closely relate to estimates of tau PET burden or spatial spread
Aim 2: Test whether CSF MTBR-tau and tau phosphorylation increase with advanced tau staging based on spatial patterns of tau PET
Aim 3: Test whether CSF MTBR-tau and tau phosphorylation relate to network-based indicators of tau PET spreading
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Investigator: Guorong Wu
Project Title: Uncovering Propagation Mechanism of Tau Aggregates by Neural Transport Equation
Date: January 5, 2023
Request ID: D2302
Aim 1: Developing machine learning approch to uncover the spreading pathway of tau aggregates.
Aim 2: Evaluate the prediction accuracy and replicability on exising public datasets
Aim 3: Explore the population sub-stratification on AD/ADRD cohorts
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Investigator: John Morris
Project Title: Predicting continuous PET values with pTau isoforms
Date: January 4, 2023
Request ID: D2301
Aim 1: Test whether CSF pTau isoforms can predict regional amyloid burden
Aim 2: Test whether CSF pTau isoforms can predict regional tau burden
Aim 3: Assess the relative predictive ranges of each CSF pTau isoform for cortical amyloid burden and tauopathy
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Investigator: Gemma Salvadó
Project Title: Validation of a CSF biomarker-based staging model
Date: December 5, 2022
Request ID: D2221
Aim 1: To test whether there is a unique ordering on the abnormality of different CSF tau fragments
Aim 2: To assess the ordering of abnormality of several CSF tau fragments
Aim 3: To assess whether this ordering is associated with other relevant AD-related measures
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