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Morales J, Welter D, Bowler EH, Cerezo M, Harris LW, McMahon AC, Hall P, Junkins HA, Milano A, Hastings E, Malangone C, Buniello A, Burdett T, Flicek P, Parkinson H, Cunningham F, Hindorff LA, MacArthur JAL. A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog. Genome Biol 2018; 19:21. [PMID: 29448949 PMCID: PMC5815218 DOI: 10.1186/s13059-018-1396-2] [Citation(s) in RCA: 134] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Accepted: 01/19/2018] [Indexed: 12/23/2022] Open
Abstract
The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.
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Affiliation(s)
- Joannella Morales
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Danielle Welter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Emily H. Bowler
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Maria Cerezo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Laura W. Harris
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Aoife C. McMahon
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Peggy Hall
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-9305 USA
| | - Heather A. Junkins
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-9305 USA
| | - Annalisa Milano
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Emma Hastings
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Cinzia Malangone
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Annalisa Buniello
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Tony Burdett
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Fiona Cunningham
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Lucia A. Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-9305 USA
| | - Jacqueline A. L. MacArthur
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
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Peprah E, Xu H, Tekola-Ayele F, Royal CD. Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease. Public Health Genomics 2014; 18:40-51. [PMID: 25427668 DOI: 10.1159/000367962] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Accepted: 08/29/2014] [Indexed: 01/11/2023] Open
Abstract
Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.
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