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Mosley JD, Witte JS, Larkin EK, Bastarache L, Shaffer CM, Karnes JH, Stein CM, Phillips E, Hebbring SJ, Brilliant MH, Mayer J, Ye Z, Roden DM, Denny JC. Identifying genetically driven clinical phenotypes using linear mixed models. Nature communications. 2016 Apr 25;7(7). 11433 p.
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