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Description

A dried blood spot (DBS) collection in Round 7 (2017) of NHATS provided the biological material for genotyping. Samples were genotyped at Erasmus Medical Center in Rotterdam, Netherlands on the Illumina Infinium Global Screening Array v3.0. The array contains clinical and rare variants ideal for multiethnic populations. After quality control steps removing variants with high (>5%) missingness and individuals with high missingness (>5%), a total of 700,009 variants and 4,006 samples were included in the NHATS genetic dataset.  Quality control was performed at the Arking Lab at the Johns Hopkins University and validated independently at the University of Michigan. We include genotyped data (build hg19/GRCh37 plink format), TOPMed imputed data (build GRCh38, vcf format), ancestry-specific analytic groups, as well as recommended sample filtering information. Within ancestry principal components are available from the NHATS study by request.

Self-reported primary race/ethnicity with missing values assigned the modal category indicated 729 non-Hispanic Black, 2,962 non-Hispanic White, 223 Hispanic, and 92 other race/ethnicity samples (see population breakdown below). For detail about each self-reported race/ethnicity group see the NHATS User Guide [https://nhats.org/researcher/nhats/methods-documentation?id=user_guide].  To request phenotype data for participants in this study, apply at https://www.nhats.org/researcher/data-access/sensitive-data-files?id=restricted_data_files

MaleFemaleTotal
Non-Hispanic White1,2611,7012,962
Non-Hispanic Black279450729
Other*444892
Hispanic87136223
Total1,6712,3354,006
*American Indian, Alaska Native, Asian, Native Hawaiian, Pacific Islander

Sample Summary per Data Type

Sample SetAccessionData TypeNumber of Samples
National Health & Aging Trends Study (NHATS) GWASsnd10042GWAS4,006

Available Filesets

NameAccessionLatest ReleaseDescription
NHATS GWAS: Genotype datafsa000044NG00134.v1Genotype data
NHATS GWAS: TOPMed imputation datafsa000045NG00134.v1TOPMed imputation data

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

Provided in this dataset is a set of GWAS files that underwent a process of quality control measures by the Arking Lab at the Johns Hopkins University, as well as imputed genotypes from the TOPMed reference panel. 4,006 subjects were genotyped at the Erasmus Medical Center in Rotterdam, Netherlands on the Illumina Infinium Global Screening Array v3.0, which captures genotype data on 700,009 genomic SNPs.

Sample SetAccession NumberNumber of Subjects
National Health & Aging Trends Study (NHATS) GWASsnd100424,006
Consent LevelNumber of Subjects
GRU-IRB-PUB-NPU4,006

Visit the Data Use Limitations page for definitions of the consent levels above.

Total number of approved DARs: 1
  • Investigator:
    Zhao, Jinying
    Institution:
    University of Florida
    Project Title:
    Identifying novel biomarkers for human complex diseases using an integrated multi-omics approach
    Date of Approval:
    November 21, 2023
    Request status:
    Approved
    Research use statements:
    Show statements
    Technical Research Use Statement:
    GWAS, WES and WGS have identified many genes associated with Alzheimer’s Dementia (AD) and its related traits. However, the identified genes thus far collectively explain only a small proportion of disease heritability, suggesting that more genes remained to be identified. Moreover, there is a clear gender and ethnic disparity for AD susceptibility, but little research has been done to identify gender- and ethnic-specific variants associated with AD. Of the many challenges for deciphering AD pathology, lacking of efficient and power statistical methods for genetic association mapping and causal inference represents a major bottleneck. To tackle this challenge, we have developed a set of novel statistical and bioinformatics approaches for genetic association mapping and multi-omics causation inference in large-scale ethnicity-specific epidemiological studies. The goal of this project is to leverage the multi-omics and clinical data archived by the ADSP, ADNI, ADGC as well as other AD-related data repositories to identify novel genes and molecular markers for AD. Specifically, we will (1) validate our novel methods for identifying novel risk and protective genomic variants and multi-omics causal pathways of AD; (2) identify novel ethnicity- and gender-specific genes and molecular causal pathways of AD. We will share our results, statistical methods and computational software with the scientific community.
    Non-Technical Research Use Statement:
    Although many genes have been associated with Alzheimer’s Dementia (AD), these genes altogether explain only a small fraction of disease etiology, suggesting more genes remained to be identified. Of the many challenges for deciphering AD pathology, lacking of power statistical methods represents a major bottleneck. To tackle this challenge, we have developed a set of novel statistical and bioinformatics approaches for genetic association mapping and multi-omics causation inference in large-scale ethnicity-specific epidemiological studies. The goal of this project is to leverage the rich genetic and other omic data along with clinical data archived by the ADSP, ADNI, ADGC as well as other AD-related data repositories to identify novel genes and molecular markers for AD. Such results will enhance our understanding of AD pathogenesis and may also serve as biomarkers for early diagnosis and therapeutic targets.

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 NG00134.

For investigators using National Health and Aging Trends Study (NHATS) (sa000030) data:

In text: “National Health and Aging Trends Study (NHATS) is sponsored by the National Institute on Aging (grant number NIA U01AG32947) and conducted by the Johns Hopkins University.”

In references: “National Health and Aging Trends Study. Produced and distributed by www.nhats.org with funding from the National Institute on Aging (grant number NIA U01AG32947).”