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: Teodoro Bottiglieri
Project Title: Methionine and methylation cycle metabolites in dementia.
Date: [153]
Request ID: D1625
Aim 1: To determine and compare metabolites related to methionine metabolism and methylation in plasma and CSF from a cohort of subjects who cognitively normal and with mild dementia of the Alzheimer�s type.
Aim 2: To determine the relationship between metabolites related to homocysteine metabolism and methylation with other biomarkers of Alzheimer�s disease (i.e.ApoE genotype, beta-amyloid 1-40 and 1-42, Tau and p-Tau) in plasma and CSF.
Aim 3: To determine if metabolites of the methionine cycle and methylation are correlated with and predictive of changes in dementia clinical scores and brain imaging data in subjects enrolled in the �Longitudinal studies of healthy aging and dementia�.
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Investigator: Jason Hassenstab
Project Title: Characterization of Cognitive Aging in a Robust Sample of Healthy Older Adults
Date: [153]
Request ID: D1624
Aim 1: Detemine the contribution of normal aging on cognitive trajectories in biomarker positive cognitively normal adults compared to biomarker negative older adults.
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Investigator: Isabelle Bos
Project Title: The relationship between dementia risk factors and AD biomarkers in preclinical AD
Date: [153]
Request ID: D1623
Aim 1: To investigate the prevalence of vascular risk factors in different groups of cognitively normal individuals, classified according to their biomarker profile.
Aim 2: To examine the influence of risk factors on cognitive decline.
Aim 3: To explore the interplay between risk factors in their association with AD biomarkers.
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Investigator: Jee-young Han
Project Title: 2. Characteristics of atypical AD and use of amyloid markers
Date: [153]
Request ID: D1622
Aim 1: To demonstrate prevalence of amyloid biomarkers in atypical dementia (non-AD dementia(uncertain or mixed) and AD with unusual features)
Aim 2: To determine the utility of amyloid biomarkers in diagnosing atypical AD in atypical dementia
Aim 3: To characterize atypical dementia in MAP cohort
Aim 4: To determine rate of cognitive decline in atypical AD dementia and non-AD dementia
Investigator: Dmitriy A. Yablonskiy
Project Title: Quantitative Evaluation of Changes in the AD brain Using Advanced MRI
Date: [153]
Request ID: D1621
Aim 1: To develop a readily available, non-invasive quantitative in vivo MRI-based biomarker that can serve as a surrogate for amyloid-β accumulation in the brain
Aim 2: To establish specific quantitative and spatial patterns of GEPCI metrics abnormalities that would distinguish between normal brain, preclinical AD, and very mild AD
Aim 3: To establish the effect of early AD-related brain tissue damage (defined by GEPCI surrogate biomarkers) on cognitive performance and to test the hypothesis that the GEPCI metrics and/or changes in GEPCI metrics can be predictors of the disease progression
Aim 4: To validate GEPCI measurements against direct neuropathology
Investigator: Anne Fagan Niven
Project Title: Lumipusle exploratory inquiry for autopsy/ CSF data
Date: [153]
Request ID: D1620
Aim 1: To determine the feasibility (as measured by cohort size and potential for statistical significance) of a collaboration with Fujirebio that would explore correspondence of positive AD autopsy and previously collected CSF analytes (Abeta, tau and ptau181).
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Investigator: Michael Cole
Project Title: Examining changes in functional network structure
Date: [153]
Request ID: D1619
Aim 1: Examine changes in functional fMRI networks during task and resting state
Aim 2: Relate differences in network structure to Alzheimer biomarkers
Aim 3: Calculate changes in network structure in two different resting state scans
Aim 4: Use differences in longitudinal resting state structure to predict longitudinal cognition
Investigator: David Holtzman
Project Title: Rate of dementia progression in TREM2 variant carriers with neuropathologically confirmed AD
Date: [153]
Request ID: D1618
Aim 1: Do variants in the TREM2 gene that are associated with an increased risk of developing Alzheimer disease affect the clinical course of the disease?
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Investigator: Auriel Willette
Project Title: Mapping the Genetic Architecture of the Default Mode Network
Date: [153]
Request ID: D1617
Aim 1: Conduct GWAS analyses to identify novel single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with altered resting state functional connectivity and grey matter in DMN structures
Aim 2: Perform targeted gene set-based association analysis with a priori defined functional mutants, to determine influences on DMN function and structure
Aim 3: Establish relationships between DMN functional connectivity and memory
Aim 4: Establish relationships between novel variants and biomarkers of metabolism
Investigator: John Morris
Project Title:
Date: [153]
Request ID: D1616
Aim 1: Determine the relative burden of tauopathy in archicortical and neocortical areas in ADAD and LOAD using unbiased stereologic methods.
Aim 2: Determine the contribution of different lesions (neuropil threads, dystrophic neurites, and neurofibrillary tangles) to the overall tau burden in neocortical and archicortical regions.
Aim 3: Determine the relationship between the clinical phenotypes of LOAD and ADAD and spatial patterns of tauopathy.
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