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: Olivier Keunen
Project Title: Predi-PET
Date: August 20, 2025 at 8:28 am
Request ID: D2536
Aim 1: Predict PET outcomes form multi protocol MRI by feature extraction
Aim 2: Correlate OASIS-3 MRI set to OASIS-3 longitudinal Tau (OASIS3-AV1451L)
Aim 3: Create a fountational model that can use multiple MRI protocols and predict multiple PET tracers signals
Aim 4: Generation of PET volumes from MRI and evaluate metrics (PNSR,SSIM, SUVr,…)
Investigator: Kaleigh Roberts
Project Title: Comparative Deep Learning Analysis of Familial and Sporadic Alzheimer’s Disease
Date: August 15, 2025 at 2:37 pm
Request ID: D2535
Aim 1: Develop a foundation model (merging with the other data generated by the Crary lab).
Aim 2: Use supervised convolutional neural networks (CNNs) to classify images based on disease group and genotype, using regions of interest enriched for known pathological features (e.g., amyloid plaques, neurofibrillary tangles).
Aim 3: Apply multiple instance learning (e.g., CLAM) to detect latent features that distinguish familial and sporadic AD without relying on annotations (unsupervised), and interpret attention maps to identify novel morphologic signals.
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Investigator: Giovanni Frisoni
Project Title: Evaluation of the Alzheimer’s Association Workgroup 2024 (AA-2024) diagnostic criteria staging matrix: Influence of APOE4 genotype on disease trajectory and longitudinal progression
Date: August 14, 2025 at 2:14 am
Request ID: D2534
Aim 1: Investigate how the APOE4 genotype influences the distribution across the AA-2024 staging matrix at baseline.
Aim 2: Examine longitudinal transitions within the matrix among different APOE4 groups, assessing individual progression through biological and clinical stages over follow-up periods.
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Investigator: Manuel Menéndez González
Project Title: Probabilistic Diagnosis of Neurodegenerative Diseases: Correlation Between Clinical Diagnoses and Neuropathological Confirmation
Date: August 7, 2025 at 6:51 am
Request ID: D2533
Aim 1: To validate a new clinical diagnostic paradigm based on a three-dimensional framework that integrates the clinical and biological complexity of neurodegenerative diseases (NDDs).
Aim 2: To develop a probabilistic inference model that integrates multiple variables to estimate, during life, the likelihood of various neurodegenerative disease (NDD) diagnoses, including the possibility of co-pathologies.
Aim 3: To compare the model’s estimations with post-mortem neuropathological findings, assessing its reliability, validity, and clinical utility.
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Investigator: Rafael Taeho Han
Project Title: CSF-Plasma Proteomic Profiling (SomaScan) to study Neuroinflammatory Diseases: Multiple Sclerosis, MOG Antibody Disease, and Neuromyelitis Optica
Date: August 4, 2025 at 1:09 am
Request ID: D2532
Aim 1: analysis of SomaScan proteomic data from paired cerebrospinal fluid (CSF) and plasma samples of patients with neuroinflammatory diseases, including Multiple Sclerosis (MS), Myelin Oligodendrocyte Glycoprotein (MOG) antibody disease, and Neuromyelitis Optica (NMO)
Aim 2: o strengthen the statistical power and validity of our analyses, we require additional healthy aging control data. A critical component of our study is to compare disease-associated proteomic profiles with those from healthy aging individuals as controls.
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Investigator: Shea Andrews
Project Title: Evaluating the association of Integrative Genetic and Clinical Risk Profiles with Age of Onset and ATN Biomarker Profiles in Autosomal Dominant Alzheimer’s Disease
Date: July 18, 2025 at 5:24 pm
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Aim 1: Quantify the combined and interactive effect of APOE genotype, AD-PRS, and CRS on age of symptom onset in ADAD mutation carriers. We hypothesize that higher cumulative genetic and clinical risk burden will predict earlier symptom onset, beyond the effects of monogenic mutations alone.
Aim 2: Characterize A/T/N biomarker trajectories associated with combined genetic and clinical risk profiles among ADAD mutation carriers using plasma, cerebrospinal fluid (CSF) and imaging data from DIAN participants.
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Investigator: Yizhou Yu
Project Title: Alzheimer’s Microbiome Atlas
Date: July 14, 2025 at 1:10 pm
Request ID: D2530
Aim 1: Investigating the human gut microbiome’s changes over the course of Alzheimer’s disease.
Aim 2: Exploring potential effects the gut may have on the progression of Alzheimer’s disease
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Investigator: Yiyi Hu
Project Title: Cross-Tracer Analysis of Amyloid-β PET Imaging Using PiB and AV-45
Date: July 14, 2025 at 7:33 am
Request ID: D2529
Aim 1: To compare amyloid burden across PET scans acquired with 11C-PiB and 18F-AV-45 using SUVR values and standardized Aβ positivity cutoffs.
Aim 2: To examine regional uptake patterns and variability in Aβ distribution across tracers in cognitively normal and impaired subjects.
Aim 3: To develop and validate an end-to-end deep learning model for Aβ status classification using raw PiB and AV-45 PET volumes.
Aim 4: To evaluate tracer harmonization strategies using SUVR and Centiloid scales for cross-tracer generalization and compatibility.
Investigator: Andrew J. Aschenbrenner
Project Title: Clarifying the role of mind wandering in Alzheimer disease
Date: July 9, 2025 at 11:49 am
Request ID: D2528
Aim 1: Determine if subjective and objective mind wandering metrics from the new tasks sensitive to amyloid burden cross-sectionally
Aim 2: Determine if the amyloid to mind wandering relationship depend upon clinical status (CDR 0 vs. CDR 0.5).
Aim 3: Determine if mind wandering moderates the relationship between amyloid and standard cognitive outcomes (e.g., the Knight Preclinical Alzheimer Disease Cognitive Composite (PACC)).
Aim 4: Determine if mind wandering correlates with other clinical outcomes.
Investigator: Lukai Zheng
Project Title: Uncovering distinct spatial-temporal trajectories of tau accumulation to predict disease progression and cognition decline in Alzheimer’s disease
Date: July 2, 2025 at 8:19 pm
Request ID: D2618
Aim 1: To determine whether tau-PET defined AD subtypes can predict longitudinal amyloid and tau accumulation, as well as cognition decline in individuals across the AD spectrum.
Aim 2: To test if there is a sex-specific effect of tau-PET defined subtypes on tau spreading and cognition decline.
Aim 3: To develop and evaluate a ML model that predicts longitudinal cognitive performance based on baseline multimodal data.
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