Overview
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Description
Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in ancestry groups of predominantly non-European ancestral backgrounds in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry collection of GWAS datasets in the Alzheimer’s Disease Genetics Consortium (ADGC) to test for novel shared and population-specific late-onset Alzheimer’s Disease (LOAD) susceptibility loci. We evaluated the underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American (AFA), 8,899 Hispanic (HIS), and 3,232 East Asian individuals (EAS), performing within ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. All Cases met either NINCDS-ADRDA Working Group (McKhann et al 1984; PMID: 6610841) or NIA-AA Working Group (PMID: 21514250) criteria for clinical AD diagnoses or have autopsy-confirmed disease and have diagnosis after age 60 years. All non-cases/controls were cognitively intact, with an MMSE>28 and at least 60 years of age at their last exam; or were deceased after age 60 and free of cognitive complaint prior to death or have autopsy-confirmation of limited AD pathology. Data available here include ancestry-specific GWAS meta-analysis summary statistics (NHW, AFA, HIS, EAS) and cross-ancestry GWAS meta-analysis summary statistics (NHW+AFA+HIS+EAS).
Available Filesets
| Name | Accession | Latest Release | Description |
|---|---|---|---|
| ADGC Multi-Ancestry GWAS Meta-Analysis Summary Statistics (application needed) | fsa000141 | NG00177.v1 | Full Summary Statistics |
| ADGC Multi-Ancestry GWAS Meta-Analysis P-values only (open access) | fsa000142 | NG00177.v1 | P-values Only |
View the File Manifest for a full list of files released in this dataset.
Related Studies
- Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset…
Consent Levels
| Consent Level | Number of Subjects |
|---|---|
| DS-ADRD-IRB-PUB-NPU | NA |
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 NG00177.
For investigators using Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK, GRB14, and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium (sa000070) data:
The National Institutes of Health, National Institute on Aging (NIH-NIA) supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; Samples from the National Cell Repository for Alzheimer’s Disease (NCRAD), which receives government support under a cooperative agreement grant (U24 AG21886) 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; 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); GCAD, U54 AG052427; NACC, U01 AG016976; NIA LOAD (Columbia University), U24AG056270; Banner Sun Health Research Institute P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, AG025259, R01 AG048927, RF1 AG057519, R01AG33193, R01 AG009029; Columbia University, P30AG066462, R01 AG072474, R01 AG067501; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, U01 AG006781, U01 HG004610, U01 HG006375, U01 HG008657; Indiana University, P30 AG10133, R01 AG009956, RC2 AG036650; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134, P30 AG062421; Mayo Clinic, P50 AG016574, R01 AG032990, KL2 RR024151; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; North Carolina A&T University, P20 MD000546, R01 AG28786-01A1; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG030146, R01 AG01101, RC2 AG036650, R01 AG22018; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671, P30 AG053760; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG030653, P50 AG041718, P50 AG064877, P30 AG066468; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG070864, AG052410, AG074527 and U01 AG058654, AG057659, AG062943, AG066767, AG076482 AND U19 AG074865; University of Washington and Kaiser Foundation Research Institute, P50 AG005136, R01 AG042437, P30 AG066509, U19 AG066567; University of Wisconsin, P50 AG033514; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991, P01 AG026276. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant # NS39764, NIMH MH60451 and by Glaxo Smith Kline. Support was also from the Alzheimer’s Association (LAF, IIRG-08-89720; MP-V, IIRG-05-14147), the US Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program, and BrightFocus Foundation (M.P.-V., A2111048). P.S.G.-H. is supported by Wellcome Trust, Howard Hughes Medical Institute, and the Canadian Institute of Health Research. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG041232 to AJM and MJH, The Banner Alzheimer’s Foundation, The Johnnie B. Byrd Sr. Alzheimer’s Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council, local NHS trusts and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council),South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England (HEFCE), Alzheimer’s Research Trust (ART), BRACE, Alzheimer's Brain Bank UK, and Development and Alumni Relations (DARO) Office, as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, Universitat de Barcelona. ADNI data collection and sharing was funded by the National Institutes of Health Grant U01 AG024904 and Department of Defense award number W81XWH-12-2-0012. Funding for Saarland University was provided by the German Federal Ministry of Education and Research (BMBF), grant number 01GS08125 to Matthias Riemenschneider. ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Eisai Inc.; 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.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of 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. Additional salary and analytical support were provided by NIA grants R01 AG054060 and RF1 AG061351. We thank Drs. D. Stephen Snyder and Marilyn Miller from NIA who are ex-officio ADGC members.
Related Publications
Rajabli, F., et al. Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK, GRB14, and KIAA0825 as novel risk loci for Alzheimer’s disease: the Alzheimer’s Disease Genetics Consortium. Genome Biol. 2025 Jul. doi: 10.1186/s13059-025-03564-z PubMed link
Kunkle, B., et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat Genet. 2019 Mar. doi: 10.1038/s41588-019-0358-2 PubMed link
Naj, A., et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nat Genet. 2011 May. doi: 10.1038/ng.801 PubMed link
Approved Users
- Investigator:Wingo, ThomasInstitution:University of California DavisProject Title:Identifying Alzheimer's Disease Genetic Risk Factors By Integrated Genomic and Proteomic AnalysisDate of Approval:January 21, 2026Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:We aim to uncover new genetic risk variants for Alzheimer’s disease (AD), AD-related dementia (ADRD), and behavioral and psychiatric symptoms (BPS) associated with AD/ADRD. We expect to use whole-genome sequencing (WGS), whole-genome genotyping (WGG), and whole-exome sequencing (WES) data. Additionally, we will use the results of brain proteomic analysis to nominate genes and pathways for AD, ADRD, and dementia BPS. We plan to publish our findings to share them with the scientific community.Outcomes that will be tested include: (1) clinical disease status, (2) pathologic characterization (e.g., measures of beta-amyloid, tau, etc.), (3) cognitive decline, (4) BPSD, and (5) outcomes related to AD/ADRD severity. For sequencing data, we will extract raw sequencing reads from CRAM/BAM (or equivalent encrypted files) and re-map those to hg38 build of the human genome using PEMapper. Bascalling will be performed using PECaller using default settings. Variant annotation will use Bystro and quality control will follow approaches to assess completeness and account for ancestry as is customary in our lab. For rare variants, we will a variety of kernel-based approaches and for common variants, use standard statistical modeling. For all analyses, we plan to control for population structure deriving principal components from the underlying sequencing or genotyping data.Non-Technical Research Use Statement:Our aim is to identify genetic variants that are associated with Alzheimer's Disease (AD) to uncover new genetic associations. We will examine the role of important risk factors for AD (e.g., age and sex) in our analyses. Separately, we will perform integration of genetic findings for AD with information about how genetic variants influence or are associated with gene expression in the brain, cerebrospinal fluid, or blood to uncover new pathways of disease. Our overarching aim is to use genetic discoveries to identify mechanisms of AD pathogenesis to help nominate new treatment targets.
- Investigator:Yang, JingjingInstitution:Emory UniversityProject Title:Novel statistical methods for integrating transcriptomic and proteomic data in GWASDate of Approval:December 2, 2025Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:The objective of the proposed project is to derive novel statistical methods to integrate multi-omics data and pathology data in genome-wide association studies (GWAS) for studying complex phenotypes, with the goal of prioritizing genetic variants and identifying causal genes. First, we will develop novel statistical methods to integrate summary-level omics data and pathology data of diverse populations with GWAS data to prioritize risk genes. Second, we will apply our tools to publicly available xQTL data and the ADSP GWAS data. Third, we will also use the ADSP GWAS summary data to conduct causal analysis of other aging-related phenotypes and AD dementia.We will first develop novel statistical methods to integrate summary-level xQTL data of multiple populations with GWAS data to test gene associations with complex human diseases. We are interested in studying all complex phenotypes that were profiled for the ADSP samples, especially Alzheimer’s disease (AD) and AD-related complex phenotypes. Especially, our lab has access to the ROS/MAP multi-omics data shared by the Rush Alzheimer’s disease center (http://www.radc.rush.edu/), and GTEx data. All samples in the ROS/MAP study are well-characterized with extensive complex phenotypes profiled, including clinical diagnosis of AD, AD-related complex phenotypes, and psychological phenotypes. GTEx provides transcriptomic data of multiple human tissues. We will leverage multiple omics data profiled from the ROS/MAP study and transcriptomics data profiled from GTEx to learn SNP-omics relations, and then integrate such learned relationships with ADSP data to identify risk genes of complex diseases. We will also validate our findings by using omics and pathology data in the requested data sets.The purpose of using ADSP data is to increase sample size for testing our derived methods for functional genetic association studies of complex phenotypes, studying the genetic etiology of AD and AD-related phenotypes, and validating our finding by using the omics data from Rush Alzheimer's Disease Center. We are not limited to studying AD only. We are flexible to study any complex phenotypes that are profiled for ADSP samples.Non-Technical Research Use Statement:This proposed project is to develop novel statistical methods to integrate summary-level multi-omics data such as transcriptomic, proteomics, and epigenetics, and pathology data, in genome-wide association studies (GWAS) of complex phenotypes, with the goal of identifying causal genes. i) We will develop novel statistical method for integrating summary-level omics data and pathology data with GWAS data. ii) We will apply our tools to publicly available summary-level omics data, omics data from the ROS/MAP study, and ADSP GWAS data for studying AD and AD-related phenotypes. iii) We will conduct causal inference to test the causal relationship between AD and other aging-related phenotypes. We propose to test our proposed methods on the applied genomic analysis data to study complex phenotypes that are profiled for ADSP, including AD, AD-related pathology traits, and related psychological disorders.