NIA genetics of Alzheimer's disease data storage site (NIAGADS): Update 2020: Genetics/genetic factors of Alzheimer's disease. (7th December 2020)

• Record Type: Journal Article
• Authors: Vogel, Briana; Kuzma, Amanda B.; Valladares, Otto; Greenfest‐Allen, Emily; Klamann, Conor; Issen, Heather; Gangadharan, Prabhakaran; Katanic, Zivadin; Zhao, Yi; Qu, Liming; Lin, Han‐Jen; Moon, Michelle K.; Leung, Yuk Yee; Naj, Adam C.; Stoeckert, Christian J.; Schellenberg, Gerard D.; Wang, Li‐San
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• 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.044284
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: NIAGADS is a national genetics data repository that facilitates access of genotypic data to qualified investigators for the study of the genetics of late‐onset Alzheimer's disease (AD) and other 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 Genome 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 by the research community and utilized to their fullest extent. Method: NIAGADS is supported by National Institute on Aging (NIA) under a cooperative agreement (U24 AG041689). 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 Genomics Database to search annotation resources that link published AD studies to AD‐relevant sequence features and genome‐wide annotations. Result: As of January 2020, NIAGADS houses 67 datasets (23 added in 2019) with >59, 000 samples and nearly 34 billion genotypes. Qualified investigators can retrieve ADSP sequencing data with ease and flexibility through the NIAGADS DSS. The ADSP and other contributing studies have completed whole exome sequencing (WES) of 20, 630 subjects and whole‐genome sequencing (WGS) of 4, 750 subjects. Raw WES and WGS files, quality controlled VCF files, and phenotype data files are available via qualified access. The next planned dataset release will occur in late 2020 and will contain an additional 13, 136 genomes jointly genotype called with the first release of 4, 750 genomes, totaling about 17, 886 genomes. Conclusion: NIAGADS is a rich resource for AD researchers, with the goal of facilitating advances in Alzheimer's genetics research. By housing datasets from multiple projects and institutions, NIAGADS enables AD researchers to be more efficient in meeting their research goals. Datasets, guidelines, and new features are available on our website at https://www.niagads.org .