The UCLA ATLAS Community Health Initiative: Promoting precision health research in a diverse biobank

Summary: The UCLA ATLAS Community Health Initiative (ATLAS) has an initial target to recruit 150,000 participants from across the UCLA Health system with the goal of creating a genomic database to accelerate precision medicine efforts in California. This initiative includes a biobank embedded within...

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Main Authors: Ruth Johnson (Author), Yi Ding (Author), Arjun Bhattacharya (Author), Sergey Knyazev (Author), Alec Chiu (Author), Clara Lajonchere (Author), Daniel H. Geschwind (Author), Bogdan Pasaniuc (Author)
Format: Book
Published: Elsevier, 2023-01-01T00:00:00Z.
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100 1 0 |a Ruth Johnson  |e author 
700 1 0 |a Yi Ding  |e author 
700 1 0 |a Arjun Bhattacharya  |e author 
700 1 0 |a Sergey Knyazev  |e author 
700 1 0 |a Alec Chiu  |e author 
700 1 0 |a Clara Lajonchere  |e author 
700 1 0 |a Daniel H. Geschwind  |e author 
700 1 0 |a Bogdan Pasaniuc  |e author 
245 0 0 |a The UCLA ATLAS Community Health Initiative: Promoting precision health research in a diverse biobank 
260 |b Elsevier,   |c 2023-01-01T00:00:00Z. 
500 |a 2666-979X 
500 |a 10.1016/j.xgen.2022.100243 
520 |a Summary: The UCLA ATLAS Community Health Initiative (ATLAS) has an initial target to recruit 150,000 participants from across the UCLA Health system with the goal of creating a genomic database to accelerate precision medicine efforts in California. This initiative includes a biobank embedded within the UCLA Health system that comprises de-identified genomic data linked to electronic health records (EHRs). The first freeze of data from September 2020 contains 27,987 genotyped samples imputed to 7.9 million SNPs across the genome and is linked with de-identified versions of the EHRs from UCLA Health. Here, we describe a centralized repository of the genotype data and provide tools and pipelines to perform genome- and phenome-wide association studies across a wide range of EHR-derived phenotypes and genetic ancestry groups. We demonstrate the utility of this resource through the analysis of 7 well-studied traits and recapitulate many previous genetic and phenotypic associations. 
546 |a EN 
690 |a electronic health records 
690 |a biobanks 
690 |a multi-ancestry 
690 |a Global-Biobank Meta-analysis Initiative 
690 |a GWAS 
690 |a PheWAS 
690 |a Genetics 
690 |a QH426-470 
690 |a Internal medicine 
690 |a RC31-1245 
655 7 |a article  |2 local 
786 0 |n Cell Genomics, Vol 3, Iss 1, Pp 100243- (2023) 
787 0 |n http://www.sciencedirect.com/science/article/pii/S2666979X22002063 
787 0 |n https://doaj.org/toc/2666-979X 
856 4 1 |u https://doaj.org/article/c4f22e55703c4c1b8850fd5ace4e6da3  |z Connect to this object online.