NIA genetics of Alzheimer's disease data storage site (NIAGADS): 2021 update. (December 2021)

• Record Type: Journal Article
• Authors: Issen, Heather; Kuzma, Amanda B; Valladares, Otto; Greenfest‐Allen, Emily; Gangadharan, Prabhakaran; Katanic, Zivadin; Chou, Yi‐Fan; Wilk, Andrew; Zhao, Yi; Qu, Liming; Moon, Michelle K; Lerro, Alexis; Manuel, Joseph; Keskinen, Peter; Thomas, Carlos; Chou, Shin‐Yi; Lee, Wan‐Ping; Leung, Yuk Yee; Naj, Adam C; Stoeckert, Christian J; Schellenberg, Gerard D.; Wang, Li‐San
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.052258
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: NIAGADS is a national genomics data repository that facilitates access of genotypic and sequencing data to qualified investigators for the study of the genetics of Alzheimer's disease (AD) and related neurological diseases. Collaborations with large consortia and centers such as the Alzheimer's Disease Genetics Consortium (ADGC), Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, the Alzheimer's Disease Sequencing Project (ADSP), and the Genome Center for Alzheimer's Disease (GCAD) allow NIAGADS to lead the effort in managing large AD datasets that can be easily accessed and fully utilized by the research community. Method: NIAGADS is supported by National Institute on Aging (NIA) under a cooperative agreement. All data derived from NIA funded AD genetics studies are expected to be deposited in NIAGADS or another NIA approved site. NIAGADS manages a Data Sharing Service (DSS) that facilitates the deposition and sharing of genomic data and association results with approved users in the neurodegenerative research community. In addition, researchers are able to freely use the NIAGADS Alzheimer's Genomics Database (www.niagads.org/genomics/) to search annotation resources that link published AD studies to AD‐relevant sequence features and genome‐wide annotations. Result: As of January 2021, NIAGADS houses 74 datasets comprised of >90, 000 samples including GWAS, sequencing, gene expression, annotations, deep phenotypes, and summary statistics. Qualified investigators can retrieve ADSP sequencing data with ease and flexibility through the NIAGADS DSS. As of February 2021, the ADSP and other contributing studies have completed whole exome sequencing (WES) of 20, 504 samples and whole‐genome sequencing (WGS) of 16, 908 samples. Raw WES and WGS files, quality controlled VCF files, and phenotype data files are available via qualified access. The next round of sequencing currently underway will generate around 18, 000 additional genomes to be released at the end of 2021. Conclusion: NIAGADS is a rich resource for AD researchers, with the goal of facilitating advances in Alzheimer's genetics research. By housing datasets from many projects and institutions, NIAGADS enables AD researchers to meet their research goals more efficiently. Datasets, guidelines, and new features are available on our website at https://www.niagads.org.