| Literature DB >> 29590070 |
Lisa Bastarache1, Jacob J Hughey1, Scott Hebbring2, Joy Marlo1, Wanke Zhao3, Wanting T Ho3, Sara L Van Driest4,5, Tracy L McGregor5, Jonathan D Mosley4, Quinn S Wells4,6, Michael Temple1, Andrea H Ramirez4, Robert Carroll1, Travis Osterman1,4, Todd Edwards4, Douglas Ruderfer4, Digna R Velez Edwards7, Rizwan Hamid5, Joy Cogan5, Andrew Glazer4, Wei-Qi Wei1, QiPing Feng6, Murray Brilliant2, Zhizhuang J Zhao3, Nancy J Cox4, Dan M Roden1,4,6, Joshua C Denny8,4.
Abstract
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.Entities:
Mesh:
Year: 2018 PMID: 29590070 PMCID: PMC5959723 DOI: 10.1126/science.aal4043
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728