Overview
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Description
This dataset is part of a genome-wide association study investigating the role of Clusterin (CLU – Endophenotype for AD) in Alzheimer’s Disease. It includes imputed genotype data with 6,015,512 SNPs, using the 1000 Genomes Project data (June 2011 release) CEU (build 37) as a reference for the 673 participants included in the study.
The files provided within this dataset includes the genotypes for 50 out of 400 ADRC individuals, and, together with data from 283 ADNI subjects, accounts for the total of 673 subjects involved in the study. Data for the ADNI subjects can be requested from adni.loni.usc.edu, while the remaining 350 ADRC subjects can be obtained by applying for the NG00035 dataset.
Additional data in the Knight ADRC Collection can be accessed through https://www.niagads.org/knight-adrc-collection.
This dataset was originally published on the NIAGADS archive site and was moved to DSS on 02/03/2025.
Sample Summary per Data Type
| Sample Set | Accession | Data Type | Number of Samples |
|---|---|---|---|
| Knight ADRC GWAS of CLU | snd10112 | GWAS-Imputation | 50 |
Available Filesets
| Name | Accession | Latest Release | Description |
|---|---|---|---|
| Knight GWAS of CLU: 1000 Genome imputation and phenotypes | fsa000122 | NG00050.v1 | 1000 Genome GWAS, imputation and phenotypes |
View the File Manifest for a full list of files released in this dataset.
Data Dictionary Files
Sample information
Genome-wide association studies have associated clusterin (CLU) variants with Alzheimer's disease (AD). However, the role of CLU on AD pathogenesis is not totally understood. We used cerebrospinal fluid (CSF) and plasma CLU levels as endophenotypes for genetic studies to understand the role of CLU in AD. CSF, but not plasma, CLU levels were significantly associated with AD status and CSF tau/amyloid-beta ratio, and highly correlated with CSF apolipoprotein E (APOE) levels. Several loci showed almost genome-wide significant associations including LINC00917 (p = 3.98 × 10(-7)) and interleukin 6 (IL6, p = 9.94 × 10(-6), in the entire data set and in the APOE ε4- individuals p = 7.40 × 10(-8)). Gene ontology analyses suggest that CSF CLU levels may be associated with wound healing and immune response which supports previous functional studies that demonstrated an association between CLU and IL6. CLU may play a role in AD by influencing immune system changes that have been observed in AD or by disrupting healing after neurodegeneration.
| Sample Set | Accession Number | Number of Subjects | Number of Samples |
|---|---|---|---|
| Knight ADRC GWAS of CLU | snd10112 | 50 | 50 |
Related Studies
- 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,…
Cohorts
Consent Levels
| Available Subject Data | Consent Level | Number of Subjects |
|---|---|---|
| Genotypes | DS-ADRD-IRB-PUB | 43 |
| Genotypes | GRU-IRB-PUB | 7 |
| Phenotypes | DS-ADRD-IRB-PUB | 388 |
| Phenotypes | GRU-IRB-PUB | 12 |
Visit the Data Use Limitations page for definitions of the consent levels above.
Acknowledgement
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 NG00050.
For investigators using Charles F. and Joanne Knight Alzheimer’s Disease Research Center (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.
See below for additional dataset specific acknowledgments:
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.
For use of ng00050 and ng00052, use the following statement:
This work was supported by Pfizer and grants from the National Institutes of Health (R01-AG044546, P01-AG003991), and the Alzheimer's Association (NIRG-11–200110). This research was conducted while Carlos Cruchaga was a recipient of a New Investigator Award in Alzheimer's disease from the American Federation for Aging Research. Carlos Cruchaga is a recipient of a BrightFocus Foundation Alzheimer's Disease Research Grant (A2013359S). The recruitment and clinical characterization of research participants at Washington University were supported by NIHP50 AG05681, P01 AG03991, and P01 AG026276. Some of the samples used in this study were genotyped by the ADGC and GERAD. ADGC is supported by grants from the NIH (#U01AG032984) and GERAD from the Wellcome Trust (GR082604MA) and the Medical Research Council (G0300429). Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen Idec; Bristol-Myers Squibb Company; Eisai; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC; Johnson & Johnson Pharmaceutical Research & Development LLC; Medpace; Merck; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Rev December 5, 2013 Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.
Related Publications
Deming, Y., et al. A Potential Endophenotype For Alzheimer’s Disease: Cerebrospinal Fluid Clusterin. Neurobiol Aging 2016 Jan. doi: 10.1016/j.neurobiolaging.2015.09.009 PubMed link
Approved Users
- Investigator:Konermann, SilvanaInstitution:Arc instituteProject Title:Modeling Alzheimer’s disease risk and associated molecular phenotypesDate of Approval:August 8, 2025Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:The objective of the proposed research is to determine the relationship between Alzheimer’s disease (AD) genetic risk and associated molecular phenotypes. Genotype data will be used to compute a polygenic risk score (PRS) for disease-affected and control (non-disease-affected) participants. Statistical regression and mediation analyses will be used to model variation of molecular phenotypes with respect to PRS and, where available, pathology stage or cognitive impairment. Molecular phenotypes to be analyzed include bulk/single-cell/single-nucleus transcriptome, epigenome, proteome, metabolome, lipidome, amyloid, and tau. Molecular phenotypes of participants, including controls, will be matched with molecular phenotypes of in vitro cellular models, informing the design of in vitro perturbation experiments that recapitulate the genetic drivers of AD risk.Non-Technical Research Use Statement:Our goal is to determine the relationship between human genetic profiles associated with Alzheimer’s disease (AD) risk and specific measurable characteristics of human cells. Using multiple statistical analysis methods, we will build quantitative models that describe how those characteristics vary as a function of AD genetic risk. The models we build will help us design in vitro cellular systems that reflect different levels of AD risk, enabling experiments that inform new strategies for treating or preventing AD.
- Investigator:Seshadri, SudhaInstitution:Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TXProject Title:Therapeutic target discovery in ADSP data via comprehensive whole-genome analysis incorporating ethnic diversity and systems approachesDate of Approval:August 12, 2025Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:Objective: Utilize ADSP data sets to identify genes & specific genetic variants that confer risk for or protection from Alzheimer disease. Aim 1: Using combined WGS/WES across the ADSP Discovery, Disc-Ext, and FUS Phases, including single nucleotide variants, small insertion/deletions, and structural variants. We will: Aim 1a. Perform whole genome single variant and rare variant case/control association analyses of AD using ADSP and other available data; Aim 1b. Target protective variant identification via association analysis using selected controls within the ADSP data and performing meta analysis across association results based on selected controls from non-ADSP data sets. Aim 1c. Perform endophenotype analyses including cognitive function measures, hippocampal volume and circulation beta-amyloid ADSP data in subjects for which these measures are available. Meta analysis will be conducted across ADSP and non-ADSP analysis results. Aim 2: To leverage ethnically-diverse and admixed populations to identify AD variants we will: Aim 2a. Estimate and account for global and local ancestry in all analyses; Aim 2b. Perform admixture mapping in samples of admixed ancestry; and Aim 2c. Perform ethnicity-specific and trans-ethnic meta-analyses. Aim 3: To identify putative therapeutic targets through functional characterization of genes and networks via bioinformatics, integrative ‘omics analyses. We will: Aim 3a. Annotate variants with their functional consequences using bioinformatic tools and publicly available “omics” data. Aim 3b. Prioritize results, group variants with shared function, and identify key genes functionally related to AD via weighted association analyses and network approaches. Analyses will be performed in coordination with the following PIs. Coordination will involve sharing expertise, analysis plans or analysis results. No individual level data will be shared across institutions. Philip De Jager, Columbia University; Eric Boerwinkle & Myriam Fornage, U of Texas Health Science Center, Houston; Sudha Seshadri, U of Texas, San Antonio; Ellen Wijsman, U of Washington. William Salerno, Baylor College of MedicineNon-Technical Research Use Statement:This proposal seeks to analyze existing genetic sequencing data generated as part of the Alzheimer’s Disease Sequencing Project (ADSP) including the ADSP Follow-up Study (FUS) with the goal of identifying genes and specific changes within those genes that either confer risk for Alzheimer’s Disease or provide protection from Alzheimer’s Disease. Analytic challenges include analysis of whole genome sequencing data, appropriately accounting for population structure across European ancestry, Hispanic, and African American participants, and interpreting results in the context of other genomic data available.
Total number of samples: 50
- 232 (4.0%)
- 242 (4.0%)
- 3324 (48.0%)
- 3419 (38.0%)
- 443 (6.0%)
| Dementia | ||
|---|---|---|
| Control | 30 | 60.0% |
| Case | 20 | 40.0% |