Overview
The p-value only files are available in the “Open Access Dataset” tab.
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Description
This dataset includes summary statistics from AD GWAS in 9,168 subjects of African ancestry (Ncases = 2,903, Ncontrols = 6,265).
Genome-wide single-variant association analyses of common and rare variants were performed individually on each dataset using SNPTEST. Logistic regression was used for case-control datasets and generalized estimating equations (GEE) as implemented in GWAF were used for family-based datasets. Associations with extreme beta coefficients (|β| > 5) were filtered out. Within-study results were subsequently meta-analyzed with METAL employing an inverse-variance based model with genomic control. Variants showing significant heterogeneity between studies (I2 > 75%) were removed.
There are summary statistics for two different models:
Model1: Age, sex, and population stratification (as determined by the first three principal components (PCs) calculated individually on each dataset) were entered as covariates.
Model2: Same covariates as Model 1, but APOEe4 allele dosage (coded as 0,1,2) was entered as an additional covariate.
Available Filesets
| Name | Accession | Latest Release | Description |
|---|---|---|---|
| AD AA GWAS Ray: Full Summary Statistics (application needed) | fsa000143 | NG00179.v1 | Full Summary Statistics |
| AD AA GWAS Ray: P-values only (open access) | fsa000144 | NG00179.v1 | P-values only |
View the File Manifest for a full list of files released in this dataset.
Related Studies
- Alzheimer’s Disease (AD) GWAS was conducted in 9,168 subjects (2,903 cases; 6,265 controls) of African ancestry. Participants were diagnosed for AD according to the National Institute of Neurological and Communicative…
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 NG00179.
For investigators using Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry – Ray et al., 2024 (sa000071) data:
This study was supported by NIH grants: U19AG074865, R01AG072547, U01AG058654, R01AG048927, R01AG064614, U24AG056270, P30AG066462, AG057659, AG062943, U01AG072579, RF1AG059018.
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 FBS (Columbia University), U24 AG026395, U24 AG026390, R01AG041797; Banner Sun Health Research Institute P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01 AG048927, R01AG33193, R01 AG009029; Columbia University, P50 AG008702, R37 AG015473, R01 AG037212, R01 AG028786; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG006781, UO1 HG004610, UO1 HG006375, U01 HG008657; Indiana University, P30 AG10133, R01 AG009956, RC2 AG036650; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; 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; REAADI study is supported by NIA grant AG052410; 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; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653, AG041718, AG07562, AG02365; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136, R01 AG042437; 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 (MP-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 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. 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.
Publications
- Ray NR. Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024 Aug. PubMed link
Approved Users
- Investigator:Belloy, MichaelInstitution:Washington University in St LouisProject Title:Elucidating sex-specific risk for Alzheimer's disease through state-of-the-art genetics and multi-omicsDate of Approval:March 31, 2026Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:• Objectives: In this project, we seek to holistically investigate the genetic and molecular drivers of sex dimorphism in Alzheimer’s disease across ancestries. • Study design: This study integrates large-scale population genetics with multi-omics and endophenotype analyses. We are integrating all data available from ADGC and ADSP, together with other data from AMP-AD and biobanks such as UKB, FinnGen, and MVP to conduct large-scale multi-ancestry GWAS, rare-variant gene aggregation analyses, QTL studies, PWAS, TWAS, etc. We also particularly focus on X chromosome association studies. The study design also interrogates interactions with ancestry, hormone exposures, and with APOE*4, as well as comparisons to non-stratified GWAS/XWAS of Alzheimer’s disease. Further, we will also employ genetic correlation analyses, mendelian randomization, colocalization, and pleiotropy analyses, to interrogate overlap with other complex traits to better understand the mechanisms underlying sex dimorphism in Alzheimer’s disease. • Analysis plan, including the phenotypic characteristics that will be evaluated in association with genetic variants: Our phenotypes will include Alzheimer’s disease risk, conversion risk, various endophenotypes (including amyloid/tau biomarkers, brain imaging metrics, etc.) as well as molecular traits. As noted above, we will conduct large-scale multi-ancestry GWAS, XWAS, rare-variant gene aggregation analyses, QTL studies, PWAS, TWAS, etc. Specific aims include interrogating these question and analyses on (1) the autosomes, (2) the X chromosome, and (3) leveraging sex stratified QTL studies to drive discovery of risk genes.Non-Technical Research Use Statement:Alzheimer’s disease (AD) manifests itself differently across men and women, but the genetic and molecular factors that drive this remain elusive. AD is the most common cause of dementia and till today remains largely untreatable. It is thus crucial to study the genetics of AD in a sex-specific manner, as this will help the field gain important insights into disease pathophysiology, identify novel sex-specific risk factors relevant to personalized genetic medicine, and uncover potential new AD drug targets that may benefit both sexes. This project uses large-scale genomics and multi-omics to elucidate novel sex agnostic and sex-specific AD risk genes. We will interrogate sex dimorphism for AD risk on the autosomes and the sex chromosomes. We similarly interrogate sex dimorphism in the genetic regulation of gene expression and protein levels, which we will integrate with genetic risk for Alzheimer’s disease to further discovery risk genes. Throughout, we will also interrogate how sex-specific risk for AD interactions with hormone exposures, ancestry, and the APOE*4 risk allele.
- Investigator:Engelman, CorinneInstitution:University of Wisconsin - MadisonProject Title:AD Risk PredictionDate of Approval:March 10, 2026Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:Currently, no combined measure of rare (minor allele frequency [MAF] less than 0.5%), low frequency (MAF 0.5% to 5%), and common variant (MAF 5% or higher) risk of Alzheimer’s disease (AD) exists. Common variant polygenic risk scores (PRSs) have been a central approach to predicting genetic risk of AD, however, we know that rare and low frequency variants can account for the missing heritability in AD. One objective of this project is to determine the risk for AD based on variants across the full allele frequency spectrum. An additional objective of this project is to utilize GWAS summary statistics from multiple ancestries to calculate the PRS and AD risk.To accomplish these objectives, we will leverage sequencing data from the ADSP (our study is contributing 1,531 samples to the Follow Up phase) and summary statistics from published GWAS from different ancestries. To generate the common variant PRS, we will use these summary statistics and methods such as PRS-CSx. We will determine the carrier status for rare and low frequency AD risk alleles based on the literature and bioinformatics tools. Prediction of AD case-control status and age-at-onset for quantiles of the common variant PRS and carrier status will be characterized with an empirical receiver operating characteristic (ROC) curve. The statistical software R will be used to perform regression analyses and to evaluate the AUC.Non-Technical Research Use Statement:Currently, risk prediction for the later-onset form of Alzheimer’s disease (AD) focuses on genetic variants that are more common in the population, but ignores less common variants. Prediction is also largely based on data from populations of European ancestry. The goals of this project are to incorporate genetic variants across the full allele frequency spectrum (more and less common genetic variants) and to include more ancestrally diverse populations. To accomplish these goals, we will leverage genetic data from the ADSP and summary statistics (results) from published studies in diverse populations. We will determine the prediction of AD case-control status and age-at-onset.
- Investigator:Kamboh, M. IlyasInstitution:University of PittsburghProject Title:Genetics of Alzheimer's Disease and EndophenotypesDate of Approval:March 31, 2026Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:Objectives: We are requesting access to the NIAGADS datasets to augment our ongoing studies on the genetics of Alzheimer’s disease (AD) and AD-related endophenotypes being carried out by Kamboh and his group since 1995. We are doing GWAS using array genotypes, whole-exome sequencing and whole-genome sequencing on datasets derived from University of Pittsburgh ADRC and ancillary population-based longitudinal studies on dementia and biomarkers. Different available phenotypes include AD and non-AD dementia, age-at-set, disease progression and survival, neuroimaging, cognitive decline, plasma biomarkers for the core ATN and non-ATN pathologies. We also plan to expand on gene-gene interaction and sex-stratified analyses which require the actual genotype data. The NIAGADS datasets will be used for replication and meta-analysis, and for gene-gene interaction and sex-stratified analyses. Study Design: A case-control design will incorporate a diverse cohort of individuals with AD and age-matched controls. For quantitative traits (neuroimaging and plasma biomarkers, cognitive performance measures, indicators of disease progression), linear regression analyses will be performed to identify genetic loci. To ensure the findings are robust and inclusive, participants from diverse demographic backgrounds will be included, enabling the exploration of potential genetic variations across populations. Analysis Plan: We will conduct GWAS and targeted analyses on candidate genes on different AD and AD-related phenotypes. Primary phenotypic variables include AD disease status, age-at-onset, last age for controls, APOE genotype, cognitive decline trajectories, sex, and race. Analyses will evaluate the influence of specific genetic variants on disease risk, cognitive performance, and biomarker levels, considering both individual and interactive effects of the APOE genotype. Results will be adjusted for potential confounders, such as demographic factors, to ensure valid associations. Detail analytical methods are described in our published papers for case-control (PMID: 32651314;35694926), quantitative traits (PMID: 30361487;37666928), and cognitive decline (PMID: 37089073; 30954325).Non-Technical Research Use Statement:Our research group at the University of Pittsburgh (Pitt), has been working on the genetics of Alzheimer’s disease (AD) and AD-related endophenotypes for almost three decades, on data derived largely from the University of Pittsburgh Alzheimer’s Disease Research Center and ancillary dementia studies. We are requesting access to the NIAGADS genotype and phenotype datasets to augment our sample size to increase power to detect novel genetic associations with AD and related endophenotypes.