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The GWAS Diversity Monitor tracks diversity by disease in real time

Nature Genetics volume 52, pages 242–243 (2020)Cite this article

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To the Editor — The Genome-wide association study (GWAS) is a primary tool for the discovery of associations between genetic variants and complex phenotypes, cataloged by the National Human Genome Research Institute–European Bioinformatics Institute (NHGRI-EBI) GWAS Catalog, which currently contains information on more than 4,346 published studies across more than 4,933 diseases and traits. Although there has been a considerable expansion in the study sizes, the phenotypes considered and the number of identified variants, typical GWAS remain focused predominantly on European-ancestry samples. Our year-by-year estimates of the prevalence of European-ancestry samples range from as low as 65.93% of participants at the replication stage of studies published in 2012 to 92.18% at the discovery stage in 2019. Our cumulative estimate at the time of writing currently stands at 88.45%, even despite the recent launch of initiatives such as H3Africa, the African Genome Variation Project and GenomeAsia 100k. Geographic and demographic diversity is also limited, and other estimates suggest that 72% of participants are recruited from just three countries (the United States, the United Kingdom and Iceland)1.

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Fig. 1: A static representation of the GWAS Diversity Monitor.

Data availability

The data described in this manuscript come solely from the NHGRI-EBI Catalog of published GWAS (otherwise known as the ‘GWAS Catalog’) available at https://www.ebi.ac.uk/gwas/. Full and unreserved attribution is made to the GWAS Catalog team both here and on the dashboard itself, and re-use of their data is subject to the terms of use for EMBL-EBI services.

Code availability

The code powering the dashboard is available on Zenodo (https://doi.org/10.5281/zenodo.3600471; https://zenodo.org/record/3600472) and GitHub (https://github.com/OxfordDemSci/gwasdiversitymonitor).

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Acknowledgements

M.C.M. is supported by ERC grants 615603 and 835079, and both M.C.M. and C.R. are supported by The Leverhulme Trust, Leverhulme Centre for Demographic Science. C.R. is supported by a British Academy Postdoctoral Fellowship. Additional acknowledgements are available on the dashboard.

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Authors and Affiliations

  1. Leverhulme Centre for Demographic Science and Nuffield College, University of Oxford, Oxford, UK

    Melinda C. Mills & Charles Rahal

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  1. Melinda C. Mills
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  2. Charles Rahal
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Contributions

The authors jointly designed the study. C.R. built a prototype of the online dashboard, which was redesigned by M.C.M. and C.R. in collaboration with Global Initiative. M.C.M. wrote the main manuscript and supplementary material, which was revised jointly by both authors.

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Correspondence to Melinda C. Mills.

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The authors declare no competing interests.

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Supplementary Notes 1–6 and Supplementary Tables 1 and 2

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Mills, M.C., Rahal, C. The GWAS Diversity Monitor tracks diversity by disease in real time. Nat Genet 52, 242–243 (2020). https://doi.org/10.1038/s41588-020-0580-y

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