2018•ScienceOpen access

Phenotype risk scores identify patients with unrecognized Mendelian disease patterns

Lisa A. Bastarache, Jacob Hughey, Scott Joseph Hebbring, Joy E. Marlo, Wanke Zhao, Wan‐Ting Ho, Sara L. Van Driest, Tracy L. McGregor, Jonathan D. Mosley, Quinn Stanton Wells, Michael J. Temple, Andrea H. Ramirez, Robert J. Carroll, Travis John Osterman, Todd L. Edwards, Douglas M. Ruderfer, Digna R. Velez Edwards, Rizwan Hamid, Joy D. Cogan, Andrew Michael Glazer, Wei‐Qi Wei, QiPing Feng, Murray H. Brilliant, Zhizhuang Joe Zhao, Nancy Jean Cox, Dan M. Roden, Joshua C. Denny

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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.

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What this paper is about

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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Available 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.

Key concepts: Mendelian inheritance, Phenotype, OMIM : Online Mendelian Inheritance in Man, Disease, Biology, Genetics, Clinical phenotype, Genetic association

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