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Description

The goal of WU350 cohort is to address the many complexities of the COVID-19 pandemic. Among the 332 COVID-19 cases, ~90% were symptomatic patients, 93.7% were hospitalized, 46.7% with ICU admission, 24.7% on ventilation, and 19.0% died due to COVID-19 (82 ventilated and 63 died; 44 of the deceased had been ventilated prior to death). COVID-19 patients were 59 years old on average, 58.7% men and 67.8% of African American ancestry.

A total of 150 age-, sex-, and race-matched non-COVID-19 samples were used as controls. Controls samples were collected from the Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight-ADRC), at Washington University in St. Louis. The Knight-ADRC is one of 30 ADRCs funded by NIH. The goal of this collaborative research effort is to advance AD research with the ultimate goal of treatment or prevention of AD.

From the 482 individuals, peripheral blood was collected, and plasma was isolated by centrifuge and stored at -80⁰C. The proteomic data in plasma was measured using SomaScan v4.1 7K, a multiplexed, single-stranded DNA aptamer-based platform from SomaLogic (Boulder, CO). Instead of physical units, the readout in relative fluorescent units (RFU) was used to report the protein concentration targeted by 7,055 modified aptamers.

Additional information can be found on the websites:
https://neurogenomics.wustl.edu/
https://covid.proteomics.wustl.edu/

Sample Summary per Data Type

Sample SetAccessionData TypeNumber of Samples
Knight ADRC & WU350snd10038Proteomics482

Available Filesets

FilesetAccessionLatest ReleaseDescription
COVID19 - Proteomic and Phenotypic Datafsa000034NG00128.v1Proteomic and Phenotypic Data

View the File Manifest for a full list of files released in this dataset.

COVID-19 cases (N=350) who presented with respiratory illness symptoms and had a physician-ordered positive SARS-CoV-2 test performed at the Barnes Jewish Hospital between 26 March 2020 and 28 August 2020 (Washington University 350 (WU350) cohort). Knight-ADRC cohort collects cognitive data, plasma, CSF and imaging to study the risk factors for Alzheimer’s disease. 150 age, sex and race matched Knight-ADRC cohort participants were used as COVID-19 Controls.

Sample SetAccessionNumber of Subjects
Knight ADRC & WU350snd10038482
Consent LevelNumber of Subjects
DS-ADRD-IRB-PUB482

Visit the Data Use Limitations page for definitions of the consent levels above.

Total number of approved DARs: 2
  • Investigator:
    Cruchaga, Carlos
    Institution:
    Washington University School of Medicine
    Project Title:
    The Familial Alzheimer Sequencing (FASe) Project
    Date of Approval:
    March 28, 2023
    Request status:
    Approved
    Research use statements:
    Show statements
    Technical Research Use Statement:
    The goal of this study is to identify new genes and mutations that cause or increase risk for Alzheimer disease (AD), as well as protective factors. Individuals and families were selected from the Knight-ADRC (Washington University) and the NIA-LOAD study. Only families with at least three first-degree affected individuals were included. Families with pathogenic variants in the known AD or FTD genes, or in which APOE4 segregated with disease were excluded. At least two cases and one control were selected per family. Cases had an age at onset (AAO) after 65 yo and controls had a larger age at last assessment than the latest AAO within the family. Whole exome (WES) and whole genome sequencing (WGS) was generated for 1,235 individuals (285 families) that together with data from our collaborators and the ADSP family-based cohort (3,449 individuals and 757 families) will provide enough statistical power to identify new genes for AD. Dr. Tanzi (Harvard Medical School) will provide WGS from 400 families from the NIMH Alzheimer disease genetics initiative study. We will perform single variant and gene-based analyses to identify genes and variants that increase risk for disease in AD families. Single variant analysis will consist of a combination of association and segregation analyses. We will run family-based gene-based methods to identify genes that show and overall enrichment of variants in AD cases. We will also look for protective and modifier variants. To do this we will identify families loaded with AD cases, that also include individuals with a high burden of known risk variants but that do not develop the disease (escapees). We will use the sequence data and the family structure to identify variants that segregate with the escapee phenotype. The most promising variants and genes will be replicated in independent datasets (ADSP case-control, ADNI, Knight-ADRC, NIA-LOAD ). We will perform single variant and gene-based analyses to replicate the initial findings, and survival analysis to replicate the protective variants. We will select the most promising variants/genes for functional studies
    Non-Technical Research Use Statement:
    Family-based approaches led to the identification of disease-causing Alzheimer’s Disease (AD) variants in the genes encoding APP, PSEN1 and PSEN2. The identification of these genes led to the A?-cascade hypothesis and to the development of drugs that target this pathway. Recently, we have identified rare coding variants in TREM2, ABCA7, PLD3 and SORL1 with large effect sizes for risk for AD, confirming that rare coding variants play a role in the etiology of AD. In this proposal, we will identify rare risk and protective alleles using sequence data from families densely affected by AD. We hypothesize that these families are enriched for genetic risk factors. We already have sequence data from 695 families (2,462 individuals), that combined with the ADSP and the NIMH dataset will lead to a dataset of more than 1,042 families (4,684 individuals). Our preliminary results support the flexibility of this approach and strongly suggest that protective and risk variants with large effect size will be found, which will lead to a better understanding of the biology of the disease.
  • Investigator:
    Greicius, Michael
    Institution:
    Stanford University School of Medicine
    Project Title:
    Examining Genetic Associations in Neurodegenerative Diseases
    Date of Approval:
    May 22, 2023
    Request status:
    Approved
    Research use statements:
    Show statements
    Technical Research Use Statement:
    We are studying the effects of rare (minor allele frequency < 5%) genetic variants on the risk of developing late-onset Alzheimer’s Disease (AD). We are interested in variants that have a protective effect in subjects who are at an increased genetic risk, or variants that lead to multiple dementias. Our aim is to identify any genetic variants that are present in the “case” group but not the “AD control” groups for both types of variants. The raw data we receive will be annotated to identify SNP locations and frequencies using existing databases such as 1,000 Genomes. We will filter the data based on genetic models such as compounded heterozygosity, recessive and dominant models to identify different types of variants.
    Non-Technical Research Use Statement:
    Current genetic understanding of Alzheimer’s Disease (AD) does not fully explain its heritability. The APOE4 allele is a well-established risk factor for the development of Alzheimer’s Disease (AD). However, some individuals who carry APOE4 remain cognitively healthy until advanced ages. Additionally, the cause of mixed dementia pathology development in individuals remains largely unexplained. We aim to identify genetic factors associated with these “protected” and mixed pathology phenotypes.

Acknowledgment statement for any data distributed by NIAGADS:

Data for this study were prepared, archived, and distributed by the National Institute on Aging Alzheimer’s Disease Data Storage Site (NIAGADS) at the University of Pennsylvania (U24-AG041689), funded by the National Institute on Aging.

Use the study-specific acknowledgement statements below (as applicable):

For investigators using any data from this dataset:

Please cite/reference the use of NIAGADS data by including the accession NG00128.

For investigators using KnightADRC & WU350 (sa000026) data:

Funding: This work was supported by grants from the National Institutes of Health (R01AG044546 (CC), P01AG003991(CC, JCM), RF1AG053303 (CC), RF1AG058501 (CC), U01AG058922 (CC), and R01AG057777 (OH)), and the Chuck Zuckerberg Initiative (CZI).
The recruitment and clinical characterization of research participants at Washington University were supported by NIH P30AG066444 (JCM), P01AG03991(JCM), and P01AG026276(JCM). O.H. is an Archer Foundation Research Scientist.
This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/)and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
This study utilized samples obtained from the Washington University School of Medicine’s COVID-19 biorepository, which is supported by: the Barnes-Jewish Hospital Foundation; the Siteman Cancer Center grant P30 CA091842 from the National Cancer Institute of the National Institutes of Health; and the Washington University Institute of Clinical and Translational Sciences grant UL1TR002345 from the National Center for Advancing Translational Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the view of the NIH.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways. iScience. 2022.