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: John Morris
Project Title: Sex differences in Alzheimers Disease
Date: October 27, 2023 at 9:30 am
Request ID: D2337
Aim 1: Are women at an increased risk of developing AD?
Aim 2: Determine sex-specific differences in the clinical manifestations of AD symptomatology as a function of pathology.
Aim 3: Determine if the relationship between AD biology, particularly tau as measured by PET, and cognition varies by sex.
Aim 4: Do men and women show differences in amyloid, tau, and cognition as a function of sex and APOE status? Are there additional factors that might vary by sex?
Investigator: Oskar Hansson
Project Title: Combining plasma phospho-tau217 and Aβ42/40 to detect early development of amyloid pathology in early Alzheimer’s disease
Date: October 26, 2023 at 10:47 am
Request ID: D2336
Aim 1: To establish if a combination of p-tau217 and Aβ42/40 performs better than p-tau217 by itself or Aβ42/40 by itself when (1) identifying CU individuals and patients with MCI who have abnormal brain Aβ burden and (2) predicting change in brain Aβ burden over time.
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Investigator: Anne Cross
Project Title: Alzheimer disease pathology in multiple sclerosis
Date: October 24, 2023 at 5:17 pm
Request ID: D2335
Aim 1: Determine if the rate of AD are reduced in patients with multiple sclerosis
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Investigator: Andrew Aschenbrenner
Project Title: Clarifying the role of personality in moderating the risk of developing Alzheimer disease
Date: October 19, 2023 at 12:32 pm
Request ID: D2334
Aim 1: Determine the direction of casuality between personality traits and AD pathology
Aim 2: Evaulate lifestyle factors as potential mediators of the personality-pathology relationship
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Investigator: Pr Olivier GODEFROY
Project Title: Amyloidopathy and poststroke cognitive impairment: Individual-based meta-analysis
Date: October 13, 2023 at 11:22 am
Request ID: D2333
Aim 1: to determine the prevalence of amyloid PET positivity in poststroke (PS) patients
Aim 2: to determine the general, cognitive and stroke characteristics of PS patients according to amyloid PET status (cross-sectional)
Aim 3: to determine the general and cognitive outcome of PS patients according to amyloid PET status (follow-up study)
Aim 4: to provide a model of the relationships between cognitive status and imaging characteristics (lesion location, volume, atrophy…)according to amyloid PET status (follow-up study)
Investigator: Jason Ulrich
Project Title: APOE Risk and Novel Inflammatory Fluid Biomarkers for Predicting AD
Date: October 6, 2023 at 1:29 pm
Request ID: D2332
Aim 1: Characterization of the relationships between inflammatory proteins that vary by APOE genotype in preclinical AD.
Aim 2: Characterization of the relationships between inflammatory proteins that vary by APOE genotype in symptomatic AD.
Aim 3: Assess predictive performance of CSF inflammatory markers for CDR conversion in amyloid-positive individuals.
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Investigator: Daniel C. Alexander
Project Title: A coupled-mechanisms probabilistic inference framework for neurodegenerative disease progression
Date: September 28, 2023 at 9:02 am
Request ID: D2331
Aim 1: Use the longitudinal tau PET data from OASIS3-Longitudinal Tau dataset to validate our proposed coupled mechanisms modelling framework for the network related propagation of neurodegeneration trained on ADNI.
Aim 2: Explore more complex mechanisms of how neurodegeneration progresses along brain connectivity
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Investigator: Brian Gordon
Project Title: Comparing spatial patterns of age, neurodegeneration, and development: is Alzheimer Disease a developmental disorder?
Date: September 27, 2023 at 4:39 pm
Request ID: D2330
Aim 1: Determine spatial patterns of cortical expansion and thinning in both aging and development
Aim 2: Elucidate spatial patterns of functional connectivity (FC) development and degeneration
Aim 3: Compare spatial patterns of development and degeneration to other biological properties
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Investigator: Ganesh Chand
Project Title: Linking Alzheimer’s disease imaging markers with behavior and genetics via machine learning
Date: September 27, 2023 at 10:25 am
Request ID: D2329
Aim 1: Develop machine learning modeling methods to study multivariate relationships of regional amyloid PET, tau PET, and MRI with behavioral phenotypes in MCI/AD and controls
Aim 2: Investigate the regional heterogeneity mechanisms of amyloid PET, tau PET, and MRI in MCI/AD relative to controls
Aim 3: Investigate the relationships of amyloid PET, tau PET, and MRI heterogeneity signatures with behavioral and genetic measures at baseline and longitudinal follow-ups
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Investigator: John C. Morris
Project Title: Understanding the effects of Alzheimer’s Disease on the gut microbiome (GM)
Date: August 31, 2023 at 2:38 pm
Request ID: D2328
Aim 1: Obtain species-level taxonomic and functional GM profiles and MAGs from fecal samples
Aim 2: Longitudinally track GM taxonomy, function, and activity in adults at different stages of AD and identify host factors associated with these dynamics
Aim 3: Identify GM features and interactions associated with AD and test whether temporal data improves prediction of AD status
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