Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

The GWAS Diversity Monitor tracks diversity by disease in real time

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

Subjects

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.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

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).

References

  1. Mills, M. C. & Rahal, C. Commun. Biol. 2, 9 (2019).

  2. Sirugo, G., Williams, S. M. & Tishkoff, S. A. Cell 177, 26–31 (2019).

    Article  CAS  Google Scholar 

  3. Martin, A. R. et al. Am. J. Hum. Genet. 100, 635–649 (2017).

    Article  CAS  Google Scholar 

  4. Duncan, L. et al. Nat. Commun. 10, 3328 (2019).

    Article  CAS  Google Scholar 

  5. Tropf, F. C. et al. Nat. Hum. Behav. 1, 757–765 (2017).

    Article  Google Scholar 

  6. Mostafavi, H., Harpak, A., Conley, D., Pritchard, J. K. & Przeworski, M. Preprint at bioRxiv https://doi.org/10.1101/629949 (2019).

  7. Torkamani, A., Wineinger, N. E. & Topol, E. J. Nat. Rev. Genet. 19, 581–590 (2018).

    Article  CAS  Google Scholar 

  8. Martin, A. R. et al. Nat. Genet. 51, 584–591 (2019).

    Article  CAS  Google Scholar 

  9. Amorim, C. E. G. et al. PLoS Genet. 13, e1006915 (2017).

    Article  Google Scholar 

  10. Genovese, G. et al. Science 329, 841–845 (2010).

    Article  CAS  Google Scholar 

  11. Buniello, A. et al. Nucleic Acids Res. 47 (D1), D1005–D1012 (2019).

Download references

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.

Author information

Authors and Affiliations

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

    Melinda C. Mills & Charles Rahal

Authors
  1. Melinda C. Mills
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Charles Rahal
    View author publications

    You can also search for this author in PubMed Google Scholar

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.

Corresponding author

Correspondence to Melinda C. Mills.

Ethics declarations

Competing interests

The authors declare no competing interests.

Supplementary information

Supplementary Information

Supplementary Notes 1–6 and Supplementary Tables 1 and 2

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41588-020-0580-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing