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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
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