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: Simon Cox
Project Title: Predicting future dementia risk in asymptomatic 70-year-olds: a 17-year multimodal follow-up study.
Date: August 23, 2024 at 5:19 am
Request ID: D2434
Aim 1: To employ the summary data (a results table of coefficient) supporting a figure published by the Knight team (https://doi.org/10.1016/j.ebiom.2024.105080) to undestand the spatial similarities between ptau and cortical morhpometry of prospective dementia risk in the Lothian Birth Cohort 1936
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Investigator: Gregory Klein
Project Title: Copathologies in AD
Date: August 22, 2024 at 5:00 am
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Aim 1: Our aim is to reproduce the results from the Tosun et al. paper 2023, and to use the data to train a multi-labels classifier for copathologies in AD.
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Investigator: Alvin G. Thomas
Project Title: Genomics and Proteomics of Cognitive Resilience to AD
Date: August 21, 2024 at 3:05 pm
Request ID: D2433
Aim 1: Develop a theory-consistent measure of cognitive resilience using Knight ADRC psychometrics, brain imaging, and fluid biomarkers.
Aim 2: Identify plasma and cerebrospinal fluid (CSF) biomarkers associated with cognitive resilience using high-sensitivity proteomic measures obtained by the Alamar platform.
Aim 3: Perform cross-tissue proteomic analyses to elucidate the biology of cognitive resilience.
Aim 4: Identify genomic loci associated with cognitive resilience through genome-wide association study and proteogenomic analysis.
Investigator: Yiping Qian
Project Title: Predict the conversion from SCD to MCI using CSF and plasma biomarkers
Date: August 15, 2024 at 9:23 am
Request ID: D2432
Aim 1: This study aims to develop a machine learning model to predict the conversion to MCI within ten years in patients with SCD using clinical data of cerebrospinal fluid (CSF) biomarkers, plasma biomarkers, neuropsychological test scores, and demographic data.
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Investigator: Gregory Klein
Project Title: Copathologies in AD
Date: August 15, 2024 at 3:45 am
Request ID: D2431
Aim 1: We aim to reproduce the results from the paper from Tosun et Al 2023: building a multilabel classifier for copathologies in AD. We were instructed by Dr Tammie Bensinger to apply for this data through the portal.
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Investigator: Ellen Grober
Project Title: The Free and Cued Selective Reminding Consortium
Date: August 12, 2024 at 1:29 pm
Request ID: D2430
Aim 1: To assess the cross-sectional relationship and the predictive validity of SOMI stage for clinical outcomes in longitudinal observational studies.
Aim 2: To examine the association of SOMI stage with baseline load of fluid and imaging biomarkers and longitudinal change in AD-biomarkers.
Aim 3: To replicate the temporal unfolding of memory and executive function in a large and diverse cohort.
Aim 4: To determine whether longitudinal change in memory or executive function measures is differentially associated with amyloid vs. tau biomarkers.
Investigator: You Cheng
Project Title: Association of CSF AD biomarker and brain MRI signatures
Date: August 9, 2024 at 4:42 am
Request ID: D2429
Aim 1: Investigate the association of CSF AD biomarker and brain volumes
Aim 2: Investigate sex differences in the association of CSF AD biomarker and brain volumes
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Investigator: Peter Millar
Project Title: Comparing MRI and proteomic signatures of healthy aging
Date: July 24, 2024 at 7:06 pm
Request ID: D2428
Aim 1: Test associations between model-predicted age estimates based on MRI (structural & resting-state functional connectivity), CSF proteomic measurements, and plasma organ age brain clocks.
Aim 2: Determine if proteins identified in the CSF proteomics aging model are associated with accelerated or decelerated aging in the MRI and plasma organ age brain clock aging models.
Aim 3: Determine if neuroimaging features identified in the MRI aging models are associated with accelerated or decelerated aging in the proteomic aging and plasma organ age brain clock aging models.
Aim 4: Compare MRI, CSF proteomic, and plasma organ age brain clock age estimates in detecting preclinical and symptomatic Alzheimer disease (AD).
Investigator: Michael Ewers
Project Title: Analysis of proteomic signatures of MFG-E8 and medin amyloid in patients with Alzheimer’s disease
Date: July 21, 2024 at 1:57 am
Request ID: D2427
Aim 1: To test the association between MFG-E8 levels and neuroimaging markers of CAA
Aim 2: To test modulating factors of biofluid MFG-E8 levels in AD including APOE e4 genotype and vascular risk factors.
Aim 3: To determine the proteomic network and levels of medin associated with alterations in MFG-E8.
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Investigator: Brian Gordon
Project Title: Evaluation of perivascular spaces and other markers of glymphatic function in sporadic Alzheimer’s Disease
Date: July 17, 2024 at 10:24 am
Request ID: D2426
Aim 1: Apply methods that are hypothesized to non-invasively measure glymphatic clearance. We primarily aim to look at enlarged PVS, but will also include low b-value DTI, DTI-ALPs, PET-tracer clearance, gGM-CSF-coupling, diffusion based IVIM, and ASL. This will give insight to which approaches best captur
Aim 2: Determine if there is a relationship between PVS, secondary imaging measures described in Aim 1, and unique biofluid measures of protein turnover. These will include SILK and Aβ40 measures.
Aim 3: Using a proteomic approach, evaluate if certain proteins are associated with enlarged PVS and glymphatic clearance.
Aim 4: Relate PVS, and our secondary imaging measures, to modifiable risk factors of AD. These will include sleep, obesity (BMI, height/weight), exercise, and cardiovascular health among other lifestyle factors. We also intend to look at sex differences in glymphatic clearance.