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A global overview of pleiotropy and genetic architecture in complex traits

Nature Genetics volume 51, pages 1339–1348 (2019)Cite this article

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An Author Correction to this article was published on 06 February 2020

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Abstract

After a decade of genome-wide association studies (GWASs), fundamental questions in human genetics, such as the extent of pleiotropy across the genome and variation in genetic architecture across traits, are still unanswered. The current availability of hundreds of GWASs provides a unique opportunity to address these questions. We systematically analyzed 4,155 publicly available GWASs. For a subset of well-powered GWASs on 558 traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait-associated loci cover more than half of the genome, and 90% of these overlap with loci from multiple traits. We find that potential causal variants are enriched in coding and flanking regions, as well as in regulatory elements, and show variation in polygenicity and discoverability of traits. Our results provide insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource (https://atlas.ctglab.nl).

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Fig. 1: Trait-associated locus, gene and SNP pleiotropy across the genome.
Fig. 2: Within- and between-domain genetic correlations.
Fig. 3: Distribution and characterization of lead SNPs and credible SNPs of 558 traits.
Fig. 4: SNP heritability and polygenicity of 558 traits.

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Data availability

All publicly available GWAS summary statistics (original) files curated in this study are accessible from the original links provided at https://atlas.ctglab.nl. GWAS summary statistics for 600 traits from UK Biobank performed in this study are also provided at https://atlas.ctglab.nl and an archived file will be made available upon publication from https://ctg.cncr.nl/software/summary_statistics.

Change history

  • 06 February 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

We thank all consortiums and all other individual laboratories for making GWAS summary statistics publicly available. We also thank P. Visscher and N. Wray for their thoughtful suggestions and discussions. We additionally thank A. Dale for his suggestions. This work was funded by the Netherlands Organization for Scientific Research (grant nos. NWO VICI 453-14-005 and NWO VIDI 452-12-014).

Author information

Authors and Affiliations

  1. Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, Amsterdam, the Netherlands

    Kyoko Watanabe, Sven Stringer, Maša Umićević Mirkov, Christiaan de Leeuw, Tinca J. C. Polderman, Sophie van der Sluis & Danielle Posthuma

  2. NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Oleksandr Frei & Ole A. Andreassen

  3. Department of Clinical Genetics, Section of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU Medical Center, Amsterdam, the Netherlands

    Sophie van der Sluis & Danielle Posthuma

  4. Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Ole A. Andreassen

  5. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Benjamin M. Neale

  6. Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Benjamin M. Neale

  7. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Benjamin M. Neale

Authors
  1. Kyoko Watanabe
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Contributions

D.P. designed the study. K.W. curated the database and performed analyses. T.J.C.P. assisted with harmonization of phenotype labels of the database. S.S. performed quality control on the UK Biobank data and wrote the analysis pipeline for UKB analyses. M.U.M. assisted with the fine-mapping analyses. C.d.L. assisted with the discussion of SNP heritability estimates with different models. O.F. and O.A.A. developed software the MiXeR and assisted with the analyses. S.v.d.S. and B.M.N. discussed and provided valuable suggestions for analyses. K.W. and D.P. wrote the paper. All authors critically reviewed the paper.

Corresponding author

Correspondence to Danielle Posthuma.

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Supplementary Tables 1–26

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Watanabe, K., Stringer, S., Frei, O. et al. A global overview of pleiotropy and genetic architecture in complex traits. Nat Genet 51, 1339–1348 (2019). https://doi.org/10.1038/s41588-019-0481-0

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