Description
Data Available
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Description
This dataset involves whole exome, genome, and genotyping array data (both pre-imputation and post-imputation data) from the University of Alabama at Birmingham (UAB) Alzheimer’s Disease Research Center. Participants are enrolled as either cognitively unimpaired, MCI, or a target of mild dementia and followed longitudinally. The cohort aims to recruit a substantial fraction of self-reported African American / Black participants. There were total of 81 subjects that were enrolled in the study and the specifications for each data type are provided below.
Whole genome sequencing data includes 15 samples that were prepared by Covaris shearing, end repair, adapter ligation, and PCR using standard protocols. Library concentrations were normalized using KAPA qPCR prior to sequencing.
Whole exome Sequencing data includes 17 samples and the variants were genotyped using Integrated DNA Technologies xGen Exome Hyb Panel v2 at 100x coverage.
Genotyping SNP array data includes 64 samples variants were genotyped using the Illumina Global Diversity Array plus Neuro consortium content. PLINK v1.90 and PLINK v2.00 were used to annotate the data with hg19. One set of the data was pre-imputed, the other was imputed using the TOPMed Imputation Panel and Server v1.3.3. For the imputed set, the Pre-Imputation script located here:
Pre-imputation script (https://github.com/HudsonAlpha/Pre-Imputation-QC-Pipeline)was used on the data before submitting to the imputation server. Post-Imputation script (https://github.com/HudsonAlpha/Post-Imputation-Pipeline) was used after imputation to recover the typed only variants.
Sample Summary per Data Type
Available Filesets
Name | Accession | Latest Release | Description |
---|---|---|---|
UAB WGS | fsa000059 | NG00135.v1 | Whole Genome Sequencing data |
UAB WES | fsa000060 | NG00135.v1 | Whole Exome Sequencing data |
UAB Pre-Imputation | fsa000061 | NG00135.v1 | Genotyping SNP Array |
UAB Post-Imputation | fsa000062 | NG00135.v1 | Genotyping SNP Array |
UAB ADRC Documentation | fsa000063 | NG00135.v1 | Phenotype File and README |
View the File Manifest for a full list of files released in this dataset.
Subject Information
This dataset contains 15 samples that have Whole Exome sequencing, 17 samples Whole Genome Sequencing in FASTQ format. Also, 64 samples were genotyped using the Illumina Global Diversity Array plus Neuro consortium content. PLINK v1.90 and PLINK v2.00 were used to annotate the data with hg19. One set of the data was pre-imputed, the other was imputed to GHRCh38 using the TOPMed Imputation Panel and Server v1.3.3. The UAB ADRC cohort aims to recruit a substantial fraction of self-reported African American / Black participants. Participants are enrolled as either cognitively unimpaired, MCI, or a target of mild dementia and followed longitudinally.
Sample Set | Accession Number | Number of subjects |
---|---|---|
UAB ADRC | snd10046 | 81 |
Related Studies
Consent Levels
Consent Level | Number of Subjects |
---|---|
DS-ADRD-IRB-PUB | 81 |
Visit the Data Use Limitations page for definitions of the consent levels above.
Approved Users
- Investigator:Cruchaga, CarlosInstitution:Washington University School of MedicineProject Title:The Familial Alzheimer Sequencing (FASe) ProjectDate of Approval:May 9, 2024Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:The goal of this study is to identify new genes and mutations that cause or increase risk for Alzheimer disease (AD), as well as protective factors. Individuals and families were selected from the Knight-ADRC (Washington University) and the NIA-LOAD study. Only families with at least three first-degree affected individuals were included. Families with pathogenic variants in the known AD or FTD genes, or in which APOE4 segregated with disease were excluded. At least two cases and one control were selected per family. Cases had an age at onset (AAO) after 65 yo and controls had a larger age at last assessment than the latest AAO within the family. Whole exome (WES) and whole genome sequencing (WGS) was generated for 1,235 individuals (285 families) that together with data from our collaborators and the ADSP family-based cohort (3,449 individuals and 757 families) will provide enough statistical power to identify new genes for AD. Dr. Tanzi (Harvard Medical School) will provide WGS from 400 families from the NIMH Alzheimer disease genetics initiative study. We will perform single variant and gene-based analyses to identify genes and variants that increase risk for disease in AD families. Single variant analysis will consist of a combination of association and segregation analyses. We will run family-based gene-based methods to identify genes that show and overall enrichment of variants in AD cases. We will also look for protective and modifier variants. To do this we will identify families loaded with AD cases, that also include individuals with a high burden of known risk variants but that do not develop the disease (escapees). We will use the sequence data and the family structure to identify variants that segregate with the escapee phenotype. The most promising variants and genes will be replicated in independent datasets (ADSP case-control, ADNI, Knight-ADRC, NIA-LOAD ). We will perform single variant and gene-based analyses to replicate the initial findings, and survival analysis to replicate the protective variants. We will select the most promising variants/genes for functional studiesNon-Technical Research Use Statement:Family-based approaches led to the identification of disease-causing Alzheimer’s Disease (AD) variants in the genes encoding APP, PSEN1 and PSEN2. The identification of these genes led to the A?-cascade hypothesis and to the development of drugs that target this pathway. Recently, we have identified rare coding variants in TREM2, ABCA7, PLD3 and SORL1 with large effect sizes for risk for AD, confirming that rare coding variants play a role in the etiology of AD. In this proposal, we will identify rare risk and protective alleles using sequence data from families densely affected by AD. We hypothesize that these families are enriched for genetic risk factors. We already have sequence data from 695 families (2,462 individuals), that combined with the ADSP and the NIMH dataset will lead to a dataset of more than 1,042 families (4,684 individuals). Our preliminary results support the flexibility of this approach and strongly suggest that protective and risk variants with large effect size will be found, which will lead to a better understanding of the biology of the disease.
- Investigator:Zhou, WeichenInstitution:University of MichiganProject Title:Explore the functional impact of transposable elements in Alzheimer’s disease and related dementiasDate of Approval:May 9, 2024Request status:ApprovedResearch use statements:Show statementsTechnical Research Use Statement:Explore somatic transposable elements and their Alzheimer's disease-related patterns using genomic and phenotypic data from large cohorts:In order to explore the impact of the transposable element in Alzheimer's disease, we propose to conduct a systematic survey in the available large cohorts. The ADSP dataset in NIAGAlzheimer's diseaseS (Accession No. NG00067) includes 16,906 whole-genome sequences and 20,504 whole-exome sequences for case-control and family-based studies of Alzheimer's disease from diverse populations, which is a perfect resource to leverage in this project. Under the support of the Michigan Alzheimer's Disease Center, we will request to access NIAGADS. To detect somatic transposable elements in the ADSP dataset, we will employ established computational pipelines to resolve the transposable elements in the sequencing data, MELT and xTEA for WGS and SCRAMble for WES, respectively. Parameters in these tools, for instance, the calling threshold of supporting reads, will be adjusted accordingly to cooperate with the detection of somatic transposable elements in cells at low frequency. To exclude potential germline transposable elements, we will leverage a master set of polymorphic transposable elements from diverse populations, which are based on our previous projects at the Human Genome Structural Variation Consortium, and the case-control information provided by ADSP. We aim to summarize a spectrum of somatic transposable elements that would be Alzheimer's disease-relevant along with various clinical and phenotypic information. To build Alzheimer's disease-related genetic patterns we will implement Mutect2 (GATK) and Strelka2 to discover SNVs from WGS and WES data and link them with transposable elements in the same haplotype. After obtaining this set of patterns, we will collect phenotypic information from the ADSP dataset to conduct family-based associated analysis and gene-burden analysis. RegulomeDB will be used to annotate the effects of non-coding functional impact and regulatory changes for these Alzheimer's disease-related patterns.Non-Technical Research Use Statement:It seeks to explore the connection between the somatic transposable elements in the human genome and Alzheimer’s disease and related dementias. It will leverage large-scale datasets to extensively explore the genome-wide transposable elements and then stratify Alzheimer’s disease-relevant ones by using the rich clinical information from the cohorts. Further analysis pipelines will be built based on the results of the proposed project to investigate the functional impact of these transposable elements on Alzheimer’s disease and would improve the understanding of genetic causes of Alzheimer’s disease and related dementias.
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 NG00135.
For investigators using University of Alabama at Birmingham Alzheimer’s Disease Research Center (sa000036) data:
Funding for genome sequencing was provided by the HudsonAlpha Memory and Mobility program. Funding for exome sequencing was provided by the Alzheimer’s Association. Funding for array genotyping was provided by NIA grant 5P20AG068024.
Related Publications
Wright AC., et al. Contributions of rare and common variation to early-onset and atypical dementia risk. medRxiv. 2023 Feb 8. doi:10.1101/2023.02.06.23285383.Pubmed Link