Phenotype risk scores identify patients with unrecognized Mendelian disease patterns
Author(s) -
Lisa Bastarache,
Jacob Hughey,
Scott J. Hebbring,
Joy E. Marlo,
Wanke Zhao,
WanTing Ho,
Sara L. Van Driest,
Tracy L. McGregor,
Jonathan D. Mosley,
Quinn S. Wells,
Michael Temple,
Andrea H. Ramirez,
Robert J. Carroll,
Travis Osterman,
Todd L. Edwards,
Douglas M. Ruderfer,
Digna R. Velez Edwards,
Rizwan Hamid,
Joy D. Cogan,
Andrew M. Glazer,
WeiQi Wei,
QiPing Feng,
Murray H. Brilliant,
Zhizhuang Joe Zhao,
Nancy J. Cox,
Dan M. Roden,
Joshua C. Denny
Publication year - 2018
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.aal4043
Subject(s) - mendelian inheritance , phenotype , omim : online mendelian inheritance in man , disease , biology , genetics , clinical phenotype , genetic association , genetic variants , bioinformatics , medicine , genotype , gene , single nucleotide polymorphism , pathology
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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