Search Existing Data Requests

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: Jonathan Kipnis

Project Title: Contribution of blood- vs skull-derived immune cells to Alzheimer’s disease – Brase et al study

Date: June 13, 2025 at 2:14 pm

Request ID:

Aim 1: Analyze snRNAseq data from Knight ADRC samples from the dataset published in Brase, et al. Single-nucleus RNA-sequencing of autosomal dominant Alzheimer disease and risk variant carriers (https://doi.org/10.1038/s41467-023-37437-5) to compare against a mouse derived gene s

Aim 2:

Aim 3:

Aim 4:


Investigator: Cruchaga

Project Title: Identification of cortical and blood circular RNA in Alzheimer’s Disease

Date: June 12, 2025 at 8:13 pm

Request ID:

Aim 1: 1. To benchmark the blood circRNA models in predicting AD compared to MS tau analytes in CSF and plasma.

Aim 2:

Aim 3:

Aim 4:


Investigator: Anna-Lena Schubert

Project Title: Monitoring Cognition in the Wild

Date: June 11, 2025 at 8:22 am

Request ID:

Aim 1: This project aims to evaluate the psychometric properties and temporal dynamics of smartphone-based cognitive assessments in older adults, using data from Project 4 of the Health Aging and Senile Dementia (HASD) study.

Aim 2: First, it seeks to inform design parameters for future longitudinal ecological momentary assessment (EMA) studies.

Aim 3: Second, it aims to investigate idiographic dynamics in cognitive functioning.

Aim 4:


Investigator: Eric McDade

Project Title: Proteostasis markers in Alzheimer disease biomarker and clinical progression

Date: June 5, 2025 at 5:19 pm

Request ID: D2523

Aim 1: 1. To explore CSF levels of proteasome related peptides across the AD biomarker progression (Core 1 (-)/Core 2 (-), Core 1 (+)/Core 2 (-), Core 1 (+)/Core 2 (+)).

Aim 2: 2. Evaluate the association of proteasome related peptides with biomarkers of soluble and aggregated forms of amyloid ß and tau, neurodegeneration and microglia.

Aim 3: 3. Assess the ability of UPS vs autophagy-lysosome peptides in predicting longitudinal tau-PET, neurodegeneration and clinical progression.

Aim 4:


Investigator: Philip B. Verghese

Project Title: Establishing Concordance Between the PrecivityAD2™ Blood Test and FDA-Approved CSF Biomarkers to Support Regulatory Submission for AD Diagnosis

Date: June 1, 2025 at 8:31 am

Request ID: D2522

Aim 1: To evaluate the concordance between the PrecivityAD2™ blood test and FDA-cleared Lumipulse CSF β-Amyloid 1-42/1-40 ratio test in individuals with cognitive impairment.

Aim 2:

Aim 3:

Aim 4:


Investigator: Private Funding for Teal Omics

Project Title: Expanding Organ- and Cell-Specific Aging Models to Understand Aging in Health and Diseases

Date: May 28, 2025 at 2:58 pm

Request ID: D2521

Aim 1: Extend aging models to more organs and cell types than initially published

Aim 2: Study how proteome-based organ- and cell-specific aging measures are influenced by health status

Aim 3:

Aim 4:


Investigator: Xiaoping Gu

Project Title: Validation of YWHAG as a Novel Biomarker for Perioperative Neurocognitive Disorders Using Knight-ADRC Plasma Proteomics Data

Date: May 21, 2025 at 11:27 pm

Request ID: D2520

Aim 1: To validate the association between YWHAG protein levels and cognitive impairment using Knight-ADRC plasma proteomic data.

Aim 2: To compare the expression patterns of YWHAG in perioperative cognitive impairment and Alzheimer’s disease cohorts.

Aim 3: To explore the correlation of YWHAG with clinical cognitive scores and other established biomarkers.

Aim 4: To identify potential interacting pathways involving YWHAG that contribute to neurodegeneration.


Investigator: Gabriel Linares

Project Title: Biomarkers for synapse protection in Alzheimer disease

Date: May 13, 2025 at 9:47 am

Request ID: D2519

Aim 1: Evaluate levels of Ryk in biofluids from AD patients to determine if increased Ryk expression correlates with disease severity

Aim 2: Examine the association between Ryk expression and downstream AD pathologies

Aim 3:

Aim 4:


Investigator: Qing Wang

Project Title: Tracking AD Pathology Dynamics Using Multimodal Imaging and Proteomics

Date: May 8, 2025 at 12:07 pm

Request ID: D2518

Aim 1: Characterize the spatiotemporal dynamics among neuroinflammation, amyloid, and tau pathology through integrated imaging and proteomic profiling in AD.

Aim 2: Evaluate the combined effects of neuroinflammation, amyloid, tau, and proteomic markers on cognitive function using ML-based predictive modeling.

Aim 3:

Aim 4:


Investigator: Patrick Luckett

Project Title: Developing a Composite Brain Health Biomarker Using Resting-State fMRI and Multimodal Clinical Data

Date: May 8, 2025 at 8:44 am

Request ID: D2517

Aim 1: Develop a composite brain health score integrating clinical and neurobiological biomarkers.

Aim 2: Train deep learning models to predict the composite brain health score from resting-state functional connectivity

Aim 3: Identify functional connectivity features and brain regions most predictive of the composite score and examine their relationship to clinical measures

Aim 4: