Knight ADRC Collection
The search for novel risk factors and genetic modifiers for Alzheimer disease relies on the access to accurate and deeply phenotyped datasets. The Memory and Aging Project (MAP) at the Knight-ADRC (Washington University in St. Louis) collects cognitive data, CSF and imaging longitudinally. This clinical information combined with deep molecular phenotyping (i.e. genetic, proteomics, transcriptomics, metabolomics and lipidomics among others) will lead to the identification of novel genetic modifiers, protective variants, molecular biomarkers and the novel targets. Participants were recruited by the Knight-ADRC at Washington University in St. Louis (MO). Knight-ADRC participants have to be at least 65 years old and have no memory problems or mild dementia at the time of enrollment.
The cohort consists of individuals who are non-Hispanic white from North America (95%) or African American (5%). Individuals carrying known mutations in the Mendelian genes for AD (APP, PSEN1, PSEN2) or Frontotemporal Dementia (GRN, MAPT, C9ORF72) were excluded. AD definition is based on a combination of both clinical and pathological information if available. Pathologic diagnosis will overrule clinical diagnosis. Autopsy information is provided if available, but is not a requirement for enrollment.
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|NG00035||GWAS of CSF tau levels identifies risk variants for AD||
|NG00049||CSF Summary Statistics- Cruchaga et al. (2013)||Summary Statistics|
|NG00050||GWAS of CLU, A potential endophenotype for Alzheimer's disease||GWAS
|NG00051||SORL1 coding variants and risk for AD||Targeted Genotyping
|NG00052||CLU, A potential endophenotype for AD: Summary Statistics- Deming et al. (2016)||Summary Statistics||NA||NA|
|NG00055||CSF Aβ/ptau Summary Statistics - Deming Y et al. (2017)||Summary Statistics||NA||NA|
|NG00067||Knight ADRC - WES||Whole Exome Sequencing||253/346||650|
|NG00083||Circular RNAs in Alzheimer Disease Brains - RNA-seq Data||Summary Statistics/RNA-Seq||NA||NA|
|NG00085||ExomeChip - WashU||GWAS||519 / 349||868|
|38 / 94||
|NG00089||CSF TREM2 Summary Statistics||Summary Statistics||NA||NA|
|NG00102||Genomic and multi-tissue proteomic integration for understanding the genetic architecture of neurological diseases||Individual-level data (proteomics + array-based genotype data after imputation) and summary statistics||CSF- 201/612
|NG00108||Profiling microglia expression profiles in AD using single-nuclei RNA-seq||Single Cell RNA Sequencing||44||44|
|NG00113||Metabolomic and lipidomic signatures in Alzheimer disease brains||Metabolomics||397/26||436|
|NG00114||DNA Methylation in Alzheimer disease brains||Methylation||383/35||431|
|NG00127||Knight ADRC GWAS||GWAS||2186 / 1783||4496|
|NG00128||COVID-19 Proteomics||Proteomics||332 / 150||482|
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.