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The search for novel risk factors for Alzheimer disease relies on access to accurate and deeply phenotyped datasets. The Memory and Aging Project at the Knight-ADRC (Knight ADRC-MAP) collects plasma, CSF, fibroblast, neuroimaging clinical and cognition data longitudinally and autopsied brain samples. We are using multi-tissue (brain, CSF and plasma) multi-omic data (genetics, epigenomics, transcriptomics, proteomics and metabolomics) to identify novel risk and protective variants, create new prediction models and identify drug targets. Knight-ADRC participants have to be at least 45 years old and have no memory problems or mild dementia at the time of enrollment. There is no age at onset criteria for this cohort. Cases had to have a CDR >=0.5 whereas controls had to have a CDR=0 at last assessment. AD definition is based on a combination of both clinical and pathological information if available. Pathologic diagnosis will overrule clinical diagnosis. Participants are Non-Hispanic white from North America (82.47%) and African American (13.3%). Autopsy information was provided if available, but it is not a requirement for enrollment. Samples have been obtained from over 5,510 participants, including 2,426 AD cases, 148 FTD, 88 DLB and 2,156 cognitive normal healthy individuals. In addition, there is autopsy material from over 1,182 participants, 474 with fresh frozen parietal tissue.
We have banked more than 8,000 DNA samples form 5,220 unique participants and 1,973 blood RNA from 1,172 unique participants.
Plasma was collected from over 3,798 participants, and 1,650 have longitudinal plasma. We have logged over 8,000 plasma draws during the course of this study. CSF samples was obtained from 1,231 unique participants, and amyloid and tau imaging was obtained from 1,058 unique participants in a longitudinal manner. In addition, we have collected 164 PBMCs and 51 CSF cell pellets from this participant cohort. Fibroblasts were obtained from 207 participants including 16 TREM2 carriers, 27 with different APOE genotypes, 11 African American and 20 with extreme polygenic risk scores. IPSC are available for 22 of these fibroblasts.
Deep molecular profiling has been generated in this study, through the NeuroGenomics and Informatics Center at Washington University (https://neurogenomics.wustl.edu/). GWAS is available for 4,799 participants, and next generation sequence data (NGS) for 2,466 participants, 1,050 whole exome sequencing (WES) and 1,322 whole genome sequence (WGS) data. For 453 brain samples genetics (WGS), methylation (Illumina 880K), transcriptomics (bulk RNA-seq), proteomics (Somalogic 1.3K), metabolomics and lipidomics (Metabolon HD4) has been generated. CSF samples have proteomics (Somalogic 7K) and metabolomics (Metabolon HD4). A total of 3,000 cross-sectional plasma samples have proteomics (Somalogic 7K), metabolomics (Metabolon HD4), RNA-seq and methylation data.
Additional information about Knight ADRC datasets available through NIAGADS/DSS can be found on the Knight ADRC Collection page: https://www.niagads.org/knight-adrc-collection
Sample Summary per Data Type
|Sample Set||Accession||Data Type||Number of Samples|
|KnightADRC GWAS||fsa000033||NG00127.v1||GWAS and phenotype data|
View the File Manifest for a full list of files released in this dataset.
The data being submitted is from participants from the Knight-ADRC MAP study. Genotyping for 4495 participants were generated through 10 different genotyping arrays (Infinium CoreExome-24, Infinium Neuro Consortium Array, Infinium Global Screening Array-24, Infinium OmniExpress-24, Illumina Human660W-Quad, Human610-Quad, Illumina Omni1-Quad, Affy UK Biobank Axiom, Infinium OmniExpressExome-8, and Illumina Human1M-Duo). In particular, 1955 AD cases (57% Females, 56% APOE4+, average age 74), 839 ADRD participants (51% females, 34% APOE4+, average age 63), and 1699 cognitively healthy participants (60% Females, 31% APOE4+, average age 74) individuals are being submitted. Approximately 85% of the samples are self-defined as “White”, and 10% are self-defined as “African-American”.
|Sample Set||Accession||Number of Subjects|
|KnightADRC GWAS||snd10036||n = 4500|
|Consent Level||Number of Subjects|
Visit the Data Use Limitations page for definitions of the consent levels above.
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 NG00127.
For investigators using KnightADRC (sa000008) data:
This work was supported by grants from the National Institutes of Health (R01AG044546, P01AG003991, RF1AG053303, R01AG058501, U01AG058922, RF1AG058501 and R01AG057777). The recruitment and clinical characterization of research participants at Washington University were supported by NIH P50 AG05681, P01 AG03991, and P01 AG026276. This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
We thank the contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible. This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
For use of the ADSP-PHC harmonized phenotypes deposited within dataset, ng00067, use the following statement:
The Memory and Aging Project at the Knight-ADRC (Knight-ADRC), supported by NIH grants R01AG064614, R01AG044546, RF1AG053303, RF1AG058501, U01AG058922 and R01AG064877 to Carlos Cruchaga. The recruitment and clinical characterization of research participants at Washington University was supported by NIH grants P30AG066444, P01AG03991, and P01AG026276. Data collection and sharing for this project was supported by NIH grants RF1AG054080, P30AG066462, R01AG064614 and U01AG052410. 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.
Yang, 2021, Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders. PMID: 34239129 DOI: 10.1038/s41593-021-00886-6;
Ali, 2021, Leveraging large multi-center cohorts of Alzheimer Disease endophenotypes to understand the role of Klotho heterozygosity on disease risk; accepted for publication in PLoS One
Olive, 2020, Examination of the Effect of Rare Variants in TREM2, ABI3, and PLCG2 in LOAD Through Multiple Phenotypes. PMID: 32894242 DOI: 10.3233/JAD-200019;