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Description

This GWAS dataset, ADC2, is the second set of ADC genotyped subjects used by the Alzheimer’s Disease Genetics Consortium (ADGC) to identify genes associated with an increased risk of developing Alzheimer’s disease. Provided here, are the PLINK genotype files that have undergone ADGC quality control procedures, imputation files (.bgen format) run through the TOPMED r2 pipeline, as well as basic phenotypes as provided by the Alzheimer’s Disease Sequencing Project Phenotype Harmonization Consortium (ADSP-PHC) derived from data provided by the National Alzheimer’s Coordinating Center (NACC). Additional phenotypic data are available for request through NACC. The ADSP-PHC has harmonized additional domains for the NACC participants and for more information about available data and where to request access, visit the ADSP data page (ng00067).

Sample Summary per Data Type

Sample SetAccessionData TypeNumber of Samples
ADGC ADC Round 2snd10059Genotyping SNP Array925

Available Filesets

NameAccessionLatest ReleaseDescription
ADGC ADC Round 2: GWAS, TOPMed Imputation, Phenotype filesfsa000074NG00023.v1GWAS, TOPMed Imputation, Phenotype files

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

The ADC2 sample set was genotyped by the Center for Applied Genomics at the Children's Hospital of Philadelphia using the Illumina Infinium HD Human660W-Quad (Human660W-Quad_v1_A) beadchip which captures genotype data on 657,366 genomic SNPs. The standard Alzheimer's Disease Genetics Consortium (ADGC) quality control pipeline (Naj et al. 2011) was applied to this GWAS dataset.

Sample SetAccession NumberNumber of Subjects
ADGC ADC Round 2snd10059925
Consent LevelNumber of Subjects
DS-ADRD-IRB-PUB136
DS-ADRDAGE-IRB-PUB91
DS-ND-IRB-PUB35
DS-ND-IRB-PUB-NPU25
DS-NEURO-IRB-PUB-NPU48
GRU-IRB-PUB485
GRU-IRB-PUB-NPU29
HMB-IRB-PUB72
HMB-IRB-PUB-MDS4

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 NG00023.

For investigators using Alzheimer’s Disease Genetics Consortium (sa000003) data:

Use the following for use of any ADGC generated data:

The Alzheimer’s Disease Genetics Consortium (ADGC) supported sample preparation, sequencing and data processing through NIA grant U01AG032984. Sequencing data generation and harmonization is supported by the Genome Center for Alzheimer’s Disease, U54AG052427, and data sharing is supported by NIAGADS, U24AG041689. Samples from the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD), which receives government support under a cooperative agreement grant (U24 AG021886) awarded by the National Institute on Aging (NIA), were used in this study. We thank contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible.

See below for additional dataset specific acknowledgments:

For use with GWAS Datasets ADC1-15:

The NACC database is funded by NIA/NIH Grant U24 AG072122. NACC data are contributed by the NIA-funded ADRCs: P30 AG062429 (PI James Brewer, MD, PhD), P30 AG066468 (PI Oscar Lopez, MD), P30 AG062421 (PI Bradley Hyman, MD, PhD), P30 AG066509 (PI Thomas Grabowski, MD), P30 AG066514 (PI Mary Sano, PhD), P30 AG066530 (PI Helena Chui, MD), P30 AG066507 (PI Marilyn Albert, PhD), P30 AG066444 (PI John Morris, MD), P30 AG066518 (PI Jeffrey Kaye, MD), P30 AG066512 (PI Thomas Wisniewski, MD), P30 AG066462 (PI Scott Small, MD), P30 AG072979 (PI David Wolk, MD), P30 AG072972 (PI Charles DeCarli, MD), P30 AG072976 (PI Andrew Saykin, PsyD), P30 AG072975 (PI David Bennett, MD), P30 AG072978 (PI Neil Kowall, MD), P30 AG072977 (PI Robert Vassar, PhD), P30 AG066519 (PI Frank LaFerla, PhD), P30 AG062677 (PI Ronald Petersen, MD, PhD), P30 AG079280 (PI Eric Reiman, MD), P30 AG062422 (PI Gil Rabinovici, MD), P30 AG066511 (PI Allan Levey, MD, PhD), P30 AG072946 (PI Linda Van Eldik, PhD), P30 AG062715 (PI Sanjay Asthana, MD, FRCP), P30 AG072973 (PI Russell Swerdlow, MD), P30 AG066506 (PI Todd Golde, MD, PhD), P30 AG066508 (PI Stephen Strittmatter, MD, PhD), P30 AG066515 (PI Victor Henderson, MD, MS), P30 AG072947 (PI Suzanne Craft, PhD), P30 AG072931 (PI Henry Paulson, MD, PhD), P30 AG066546 (PI Sudha Seshadri, MD), P20 AG068024 (PI Erik Roberson, MD, PhD), P20 AG068053 (PI Justin Miller, PhD), P20 AG068077 (PI Gary Rosenberg, MD), P20 AG068082 (PI Angela Jefferson, PhD), P30 AG072958 (PI Heather Whitson, MD), P30 AG072959 (PI James Leverenz, MD). NACC phenotypes were provided by the ADSP Phenotype Harmonization Consortium (ADSP-PHC), funded by NIA (U24 AG074855, U01 AG068057 and R01 AG059716).

For use with the ADGC_AA_WES (snd10003) data:

NIH grants supported enrollment and data collection for the individual studies including: GenerAAtions R01AG20688 (PI M. Daniele Fallin, PhD); Miami/Duke R01 AG027944, R01 AG028786 (PI Margaret A. Pericak-Vance, PhD); NC A&T P20 MD000546, R01 AG28786-01A1 (PI Goldie S. Byrd, PhD); Case Western (PI Jonathan L. Haines, PhD); MIRAGE R01 AG009029 (PI Lindsay A. Farrer, PhD); ROS P30AG10161, R01AG15819, R01AG30146, TGen (PI David A. Bennett, MD); MAP R01AG17917, R01AG15819, TGen (PI David A. Bennett, MD); MARS R01AG022018 (PI Lisa L. Barnes).[CL1] [KA2] The NACC database is funded by NIA/NIH Grant U24 AG072122. NACC data are contributed by the NIA-funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P30 AG062428-01 (PI James Leverenz, MD) P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P30 AG062421-01 (PI Bradley Hyman, MD, PhD), P30 AG062422-01 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Thomas Wisniewski, MD), P30 AG013854 (PI Robert Vassar, PhD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD, MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P30 AG062429-01(PI James Brewer, MD, PhD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG053760 (PI Henry Paulson, MD, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P30 AG049638 (PI Suzanne Craft, PhD), P50 AG005136 (PI Thomas Grabowski, MD), P30 AG062715-01 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PI John Morris, MD), P50 AG047270 (PI Stephen Strittmatter, MD, PhD).

For use with the ADGC-TARCC-WGS (snd10030) data:

This study was made possible by the Texas Alzheimer’s Research and Care Consortium (TARCC) funded by the state of Texas through the Texas Council on Alzheimer’s Disease and Related Disorders and the Darrell K Royal Texas Alzheimer’s Initiative.

Naj, A., et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nature genetics. 2011 May. doi:10.1038/ng.801. PubMed link

Lambert, J.C., et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nature genetics. 2013 Dec. doi:10.1038/ng.2802. PubMed link

Jun, G.R., et al. Transethnic genome-wide scan identifies novel Alzheimer’s disease loci. Alzheimer’s & dementia : the journal of the Alzheimer’s Association. 2017 Jul. doi:10.1016/j.jalz.2016.12.012 PubMed link

Reitz, C., et al. Variants in the ATP-binding cassette transporter (ABCA7), apolipoprotein E ϵ4, and the risk of late-onset Alzheimer disease in African Americans. JAMA. 2013 Apr. doi:10.1001/jama.2013.2973 PubMed link

Kunkle, B.W., et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nature genetics. 2019 Mar. doi:10.1038/s41588-019-0358-2. PubMed link

Sims, R., et al. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer’s disease. Nature genetics. 2017 Sep. doi:10.1038/ng.3916. PubMed link

Kunkle, B.W., et al. Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis. JAMA neurology. 2021 Jan. doi:10.1001/jamaneurol.2020.3536. PubMed link

Bellenguez C., et al. New insights into the genetic etiology of Alzheimer’s disease and related dementias. Nature genetics. 2022 Apr. doi:10.1038/s41588-022-01024-z. PubMed link