Bastarache Lisa, Hughey Jacob J, Hebbring Scott, Marlo Joy, Zhao Wanke, Ho Wanting T, Van Driest Sara L, McGregor Tracy L, Mosley Jonathan D, Wells Quinn S, Temple Michael, Ramirez Andrea H, Carroll Robert, Osterman Travis, Edwards Todd, Ruderfer Douglas, Velez Edwards Digna R, Hamid Rizwan, Cogan Joy, Glazer Andrew, Wei Wei-Qi, Feng QiPing, Brilliant Murray, Zhao Zhizhuang J, Cox Nancy J, Roden Dan M, Denny Joshua C
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Center for Human Genetics, Marshfield Clinic Research Institute, Marshfield, WI, USA.
Science. 2018 Mar 16;359(6381):1233-1239. doi: 10.1126/science.aal4043.
Genetic association studies often examine features independently, potentially missing subpopulations with multiple phenotypes that share a single cause. We describe an approach that aggregates phenotypes on the basis of patterns described by Mendelian diseases. We mapped the clinical features of 1204 Mendelian diseases into phenotypes captured from the electronic health record (EHR) and summarized this evidence as phenotype risk scores (PheRSs). In an initial validation, PheRS distinguished cases and controls of five Mendelian diseases. Applying PheRS to 21,701 genotyped individuals uncovered 18 associations between rare variants and phenotypes consistent with Mendelian diseases. In 16 patients, the rare genetic variants were associated with severe outcomes such as organ transplants. PheRS can augment rare-variant interpretation and may identify subsets of patients with distinct genetic causes for common diseases.
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