IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v7y2016i1d10.1038_ncomms11433.html
   My bibliography  Save this article

Identifying genetically driven clinical phenotypes using linear mixed models

Author

Listed:
  • Jonathan D. Mosley

    (Vanderbilt University)

  • John S. Witte

    (University of California)

  • Emma K. Larkin

    (Vanderbilt University)

  • Lisa Bastarache

    (Biomedical Informatics, Vanderbilt University)

  • Christian M. Shaffer

    (Vanderbilt University)

  • Jason H. Karnes

    (Vanderbilt University)

  • C. Michael Stein

    (Vanderbilt University)

  • Elizabeth Phillips

    (Vanderbilt University)

  • Scott J. Hebbring

    (Center for Human Genetics, Marshfield Clinic Research Foundation)

  • Murray H. Brilliant

    (Center for Human Genetics, Marshfield Clinic Research Foundation)

  • John Mayer

    (Biomedical Informatics Research Center, Marshfield Clinic Research Foundation)

  • Zhan Ye

    (Biomedical Informatics Research Center, Marshfield Clinic Research Foundation)

  • Dan M. Roden

    (Vanderbilt University)

  • Joshua C. Denny

    (Vanderbilt University
    Biomedical Informatics, Vanderbilt University)

Abstract

We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q

Suggested Citation

  • Jonathan D. Mosley & John S. Witte & Emma K. Larkin & Lisa Bastarache & Christian M. Shaffer & Jason H. Karnes & C. Michael Stein & Elizabeth Phillips & Scott J. Hebbring & Murray H. Brilliant & John , 2016. "Identifying genetically driven clinical phenotypes using linear mixed models," Nature Communications, Nature, vol. 7(1), pages 1-8, September.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11433
    DOI: 10.1038/ncomms11433
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms11433
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms11433?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. Jonathan D. Mosley & John P. Shelley & Alyson L. Dickson & Jacy Zanussi & Laura L. Daniel & Neil S. Zheng & Lisa Bastarache & Wei-Qi Wei & Mingjian Shi & Gail P. Jarvik & Elisabeth A. Rosenthal & Atla, 2024. "Clinical associations with a polygenic predisposition to benign lower white blood cell counts," Nature Communications, Nature, vol. 15(1), pages 1-12, 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:7:y:2016:i:1:d:10.1038_ncomms11433. 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.