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: Jennifer Yokoyama
Project Title: Comparative Analysis of Genetic Variants Associated with Interferon Response in Alzheimer’s Disease Using the OASIS Dataset
Date: January 13, 2025 at 2:57 pm
Request ID: D2505
Aim 1: Explore immunogenetic mechanisms of Alzheimer’s disease using clinical progression data and neuroimaging
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Investigator: N/A
Project Title: Prognosis of AD using AI
Date: January 13, 2025 at 3:30 am
Request ID: D2504
Aim 1: Prognosis of AD using deep learning based on AI
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Investigator: Ganna Blazhenets, Renaud La Joie
Project Title: Reproducibility of Centiloid Values in Real-World Amyloid PET Data
Date: January 8, 2025 at 1:59 pm
Request ID: D2503
Aim 1: Centiloid framework is now broadly used to harmonize amyloid-PET quantification and allow direct comparison across cohorts. Combining more than 30 heterogeneous cohorts, we aim to evaluate the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds
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Investigator: John C. Morris
Project Title: Longitudinal analysis of gut microbiome dynamics in Alzheimer Disease
Date: January 3, 2025 at 3:12 pm
Request ID: D2502
Aim 1: Characterize gut taxonomic composition and diversity in adults at different stages of AD
Aim 2: Characterize longitudinal changes in GM taxonomic composition, functional potential, and activity in adults at different stages of AD
Aim 3: : Correlate AD-associated GM taxa, function and activity with AD biomarker and host inflammation measures and test whether longitudinal GM dynamics improves prediction of AD status
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Investigator: Shinjini Kundu
Project Title: Biological Signatures of Tau
Date: December 23, 2024 at 11:48 pm
Request ID: D2501
Aim 1: Identifying MRI and Proteomic Stages Associated with Tau-PET
Aim 2: Predicting Time to Dementia Using Multimodal Data
Aim 3: Applying Machine Learning to Multimodal Analysis
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Investigator: Jamie Ford
Project Title: Longitudinal Changes in Medial Temporal Lobe Functional Connectivity and Localised Tau Burden Among Older Adults
Date: December 18, 2024 at 10:47 am
Request ID: D2449
Aim 1: To explore whether longitudinal static and dynamic functional connectivity changes occur within sub-regions of the medial temporal lobe.
Aim 2: To measure whether these changes are associated with localised medial temporal lobe tau burden.
Aim 3: To determine whether medial temporal lobe functional connectivity and/or medial temporal lobe tau burden is associated with cognitive performance, and whether these relationships are modulated by cortical amyloid status and/or cognitive status.
Aim 4: (Supplementary) To explore participants’ Braak staging profiles, as to determine whether some participants do not adhere to the typical Braak staging spatial spread patterns of tau.
Investigator: Steven Greenberg MD
Project Title: Washington University—University of Texas Southwestern VCID Consortium Site (WU-UTSW VCID) for the Mark VCID II Consortium
Date: December 12, 2024 at 2:28 pm
Request ID: D2447
Aim 1: Recruit and longitudinally follow a diverse cohort of participants at risk for VCID.
Aim 2: Longitudinally acquire and reproducibly measure fluid-based biomarkers for this VCID cohort.
Aim 3: Longitudinally acquire and reproducibly process MRI-based biomarkers for the VCID cohort.
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Investigator: Jianping Jia
Project Title: Characterizing Ethnic Differences in CSF Biomarkers for Alzheimer’s Disease
Date: December 11, 2024 at 9:41 pm
Request ID: D2448
Aim 1: To characterize ethnic differences in CSF biomarker profiles (Aβ42, Aβ42/Aβ40, tau, p-tau) across Asian, White, and Black populations.
Aim 2: To establish standardized methods for harmonizing CSF biomarker data across different ethnic groups, analytical platforms, and laboratories.
Aim 3: To establish unified, cross-ethnic cutoff values for CSF AD biomarkers by integrating data from both populations.
Aim 4: To create and validate multimodal prediction models that integrate ethnicity-specific CSF biomarker profiles with other AD-related measures for more accurate diagnosis across diverse populations.
Investigator: Ruijin Lu
Project Title: Multi-scale air pollution exposure and its interaction with sleep on Alzheimer’s disease
Date: December 4, 2024 at 11:56 am
Request ID: D2446
Aim 1: Short-term (daily or weekly), mid-term (1-month) and long-term (1-year, 5-year and 10-year) residence-level air pollution exposures are associated with sleep parameters (e.g., sleep duration, efficiency and NREM sleep durations) under a non-parametric independence rank test framework.
Aim 2: to assess the role of air pollution exposure in the effects of sleep on AD amyloid biomarkers and cognitive assessments.
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Investigator: Sheng Chih Jin
Project Title: Identifying Genomic & Proteomic Signatures of Idiopathic Peripheral Neuropathy
Date: November 22, 2024 at 1:10 pm
Request ID: D2445
Aim 1: Characterize the proteomic landscape of iPN to identify blood plasma proteins capable of differentiating neuropathic samples from healthy controls
Aim 2: Define the underlying molecular mechanisms of iPN using an integrative analysis of genomic and proteomic data
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