IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-08424-6.html
   My bibliography  Save this article

Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection

Author

Listed:
  • Armin P. Schoech

    (Harvard T.H. Chan School of Public Health
    Harvard T.H. Chan School of Public Health
    Broad Institute of MIT and Harvard)

  • Daniel M. Jordan

    (Icahn School of Medicine at Mount Sinai)

  • Po-Ru Loh

    (Broad Institute of MIT and Harvard
    Brigham and Women’s Hospital and Harvard Medical School)

  • Steven Gazal

    (Harvard T.H. Chan School of Public Health
    Broad Institute of MIT and Harvard)

  • Luke J. O’Connor

    (Harvard T.H. Chan School of Public Health
    Harvard T.H. Chan School of Public Health
    Broad Institute of MIT and Harvard)

  • Daniel J. Balick

    (Brigham and Women’s Hospital and Harvard Medical School
    Harvard Medical School)

  • Pier F. Palamara

    (University of Oxford)

  • Hilary K. Finucane

    (Broad Institute of MIT and Harvard)

  • Shamil R. Sunyaev

    (Broad Institute of MIT and Harvard
    Brigham and Women’s Hospital and Harvard Medical School
    Harvard Medical School)

  • Alkes L. Price

    (Harvard T.H. Chan School of Public Health
    Harvard T.H. Chan School of Public Health
    Broad Institute of MIT and Harvard)

Abstract

Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 − p)]α, where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of –0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF

Suggested Citation

  • Armin P. Schoech & Daniel M. Jordan & Po-Ru Loh & Steven Gazal & Luke J. O’Connor & Daniel J. Balick & Pier F. Palamara & Hilary K. Finucane & Shamil R. Sunyaev & Alkes L. Price, 2019. "Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08424-6
    DOI: 10.1038/s41467-019-08424-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-08424-6
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-019-08424-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Brieuc Lehmann & Maxine Mackintosh & Gil McVean & Chris Holmes, 2023. "Optimal strategies for learning multi-ancestry polygenic scores vary across traits," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Carla Márquez-Luna & Steven Gazal & Po-Ru Loh & Samuel S. Kim & Nicholas Furlotte & Adam Auton & Alkes L. Price, 2021. "Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets," Nature Communications, Nature, vol. 12(1), pages 1-11, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08424-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.