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: Behnaz Jafari
Project Title: Enhancing Alzheimer’s Disease Detection: Fusion of EEG and fMRI Data Using Artificial Neural Networks
Date: [153]
Request ID: D2416
Aim 1: To develop a graph neural network encoder using non-linear Granger causality methods to model effective connectivity in fMRI data, focusing on individual brain regions in both healthy controls and individuals with Alzheimer’s disease.
Aim 2: To construct a recurrent neural network (RNN), such as Long Short-Term Memory (LSTM), encoder for EEG data across different frequency bands, for brain regions, targeting both healthy controls and Alzheimer’s disease cases.
Aim 3: To create a neural network-based decoder framework to integrate features extracted from MEG/EEG and fMRI time series data, leveraging the outputs from the RNN and GNN encoders, respectively.
Aim 4: To apply the developed framework to a datasets obtained from healthy controls and individuals diagnosed with Alzheimer’s disease for comprehensive analysis and validation
Investigator: Robert Schmidt
Project Title: Atlas with annotated neuropathology images
Date: [153]
Request ID: D2417
Aim 1: Free resource to the scientific community
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Investigator: Xue Gao
Project Title: Brain aging signatures in the plasma proteome track health and disease
Date: [153]
Request ID: D2418
Aim 1: Identify Proteomic Biomarkers: To identify and characterize plasma proteomic biomarkers that are specifically associated with brain aging, using high-throughput proteomics technologies such as mass spectrometry.
Aim 2: Correlate Biomarkers with Clinical Outcomes: To establish correlations between identified proteomic biomarkers and clinical outcomes related to cognitive decline and other age-related neurological diseases.
Aim 3: Develop Predictive Models: To develop and validate predictive models that use changes in the plasma proteome to forecast the onset and progression of cognitive impairment and neurodegenerative conditions in elderly populations.
Aim 4: Assess Intervention Efficacy: To evaluate the effectiveness of dietary and pharmacological interventions in modulating identified proteomic biomarkers and altering the trajectory of brain aging and associated cognitive decline.
Investigator: Le Shi
Project Title: Associations of Sleep Patterns with Biomarkers in Dementia
Date: [153]
Request ID: D2419
Aim 1: To determine the association of sleep regularity with PET, CSF and plasma biomarkers in AD.
Aim 2: To determine the association of sleep wave activity with PET, CSF and plasma biomarkers in AD.
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Investigator: Tammie Benzinger
Project Title: Comparative Analysis of FreeSurfer Version 5.3 vs 7
Date: [153]
Request ID: D2420
Aim 1: We aim to compare MR volumetric, thickness, and surface areas data for each region generated from FreeSurfer-5.3 and 7. We hypothesize that the global MR measures will be significantly different between software versions whilst regional values may be similar in only certain structures.
Aim 2: We aim to evaluate whether FreeSurfer version significantly influences the outputs of other modalities, such as amyloid and tau PET. We hypothesize that the FreeSurfer output from both versions will produce similar results in other imaging modalities.
Aim 3: We aim to quantify the reasons for failure in each FreeSurfer version. We hypothesize that FreeSurfer version 5.3 under-represents the segmentation in the brain, whereas FreeSurfer version 7 over-represents the segmentation in the brain.
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Investigator: Peter Millar
Project Title: Comparing atypical tau PET patterns to clinical samples
Date: [153]
Request ID: D2421
Aim 1: Compare spatial patterns of tau PET between data-driven subgroups identified in the Knight ADRC and a clinical sample of atypical AD patients from the MDC
Aim 2: Test data-driven classification of tau PET in atypical AD patients
Aim 3: Test group differences between tau PET defined subgroups in demographic characteristics, cognitive performance, genetic AD risk factors, network connectivity, and biofluid- and imaging-based AD biomarkers (where available).
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Investigator: John Morris
Project Title: Evaluating the Accuracy and Validity of Telephone-Derived Clinical Dementia Rating (CDR) Scores Compared to In-Person CDR Assessments for Alzheimer’s Disease (AD) in Knight ADRC MAP Participants
Date: [153]
Request ID: D2422
Aim 1: Evaluate the Concordance Between Telephone-Derived and In-Person CDR Scores
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Investigator: John Morris
Project Title: Sex differences in Tau Tracers in Alzheimers Disease
Date: [153]
Request ID: D2337 amendment
Aim 1: Main effect of sex on Tau-PET and on MTBR-tau243. Split this by participants who are Aβ negative and positive. This aim is replicating prior effects that have been shown in Tau-PET and extending it into MTBR-tau 243.
Aim 2: Does relationship between Tau-PET and MTBR-tau243 vary by a function of sex and Aβ status. Aβ can be examined as a continuous variable or as a binary variable of Aβ status of 0 and 1.
Aim 3: Examine the influence of APOE and if this varies as a function of sex. We plan to test if APOE genotype interacts with the aims outlined in aim 1 and 2.
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Investigator: Farzaneh Rahmani
Project Title: Utilizing CT Neck Composition Metrics to Predict Dementia Onset in Healthy Older Adults
Date: [153]
Request ID: D2423
Aim 1: Investigate the predictive value of neck CT composition metrics; including adipose and skeletal muscle quantifications; for conversion to mild cognitive impairment or dementia
Aim 2: Examine the mediating role of amyloid status in the relationship between neck CT composition metrics and dementia conversion.
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Investigator: David Holtzman
Project Title: Evaluation of Subjective Cognitive Decline in Person Who Experience Discrimination
Date: [153]
Request ID: D2424
Aim 1: We want to understand the relationship between subjective cognitive decline (SCD) in Memory and Aging participants who experience social determinants of health
Aim 2: We plan to evaluate SCD as the primary outcome variable and other covariates such as clinical cognitive health, stress level, and discrimination experiences
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