Genome-wide association studies (GWAS) have identified many loci contributing to variation in complex traits, yet the majority of loci that contribute to the heritability of complex traits remain elusive. Large study populations with sufficient statistical power are required to detect the small effect sizes of the yet unidentified genetic variants. However, the analysis of huge cohorts, like UK Biobank, is challenging. Here, we present an atlas of genetic associations for 118 non-binary and 660 binary traits of 452,264 UK Biobank participants of European ancestry. Results are compiled in a publicly accessible database that allows querying genome-wide association results for 9,113,133 genetic variants, as well as downloading GWAS summary statistics for over 30 million imputed genetic variants (>23 billion phenotype–genotype pairs). Our atlas of associations (GeneATLAS, http://geneatlas.roslin.ed.ac.uk) will help researchers to query UK Biobank results in an easy and uniform way without the need to incur high computational costs.

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Data availability

All summary results from the analyses performed are available at the GeneATLAS website, http://geneatlas.roslin.ed.ac.uk/.

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This research has been conducted using the UK Biobank Resource under project 788. The work was funded by the Roslin Institute Strategic Programme Grant from the BBSRC (BB/P013732/1) and MRC grant (MR/N003179/1) granted to A.T. A.T. also acknowledges funding from the Medical Research Council and O.C.-X. from MRC fellowship MR/R025851/1. Analyses were performed using the ARCHER UK National Supercomputing Service.

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Author notes

  1. These authors contributed equally: Oriol Canela-Xandri, Konrad Rawlik, Albert Tenesa.


  1. The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK

    • Oriol Canela-Xandri
    • , Konrad Rawlik
    •  & Albert Tenesa
  2. MRC Human Genetics Unit at the MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK

    • Oriol Canela-Xandri
    •  & Albert Tenesa


  1. Search for Oriol Canela-Xandri in:

  2. Search for Konrad Rawlik in:

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All authors contributed equally to the design, running of the analyses, and writing of the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Albert Tenesa.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–24 and Supplementary Note

  2. Reporting Summary

  3. Supplementary Tables 1, 2 and 4–13

    Supplementary Tables 1, 2 and 4–13

  4. Supplementary Table 3

    List of lead variants for each phenotype

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