@article{4789be5e79f34ffdb6578a5c3a9f94cb,
title = "Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency",
abstract = "Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease-gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein-protein association neighbors. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease-gene associations and ranked the correct seeded variant in up to 87% when detectable disease-gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders.",
keywords = "exome sequencing, model organisms, phenotype, semantic comparison, undiagnosed diseases",
author = "Bone, {William P.} and Washington, {Nicole L.} and Buske, {Orion J.} and Adams, {David R.} and Joie Davis and David Draper and Flynn, {Elise D.} and Marta Girdea and Rena Godfrey and Gretchen Golas and Catherine Groden and Julius Jacobsen and Sebastian K{\"o}hler and Lee, {Elizabeth M.J.} and Links, {Amanda E.} and Markello, {Thomas C.} and Mungall, {Christopher J.} and Michele Nehrebecky and Robinson, {Peter N.} and Murat Sincan and Soldatos, {Ariane G.} and Tifft, {Cynthia J.} and Camilo Toro and Heather Trang and Elise Valkanas and Nicole Vasilevsky and Colleen Wahl and Wolfe, {Lynne A.} and Boerkoel, {Cornelius F.} and Michael Brudno and Haendel, {Melissa A.} and Gahl, {William A.} and Damian Smedley",
note = "Funding Information: We thank Megan Kane, Mariska Davids, Katherine Schaffer, Christopher Adams, and Michael Warburton for critical review of the manuscript. This work was supported by the Intramural Research Program of the National Human Genome Research Institute and the Common Fund of the NIH Office of the Director. Monarch grants: This work was supported by the NIH Office of Director (1R24OD011883) and NIH-UDP (HHSN268201300036C). Sanger grants: This work was supported by the Wellcome Trust grant (098051) and National Institutes of Health grant (NIH) (1 U54 HG006370-01). The dbSNP accession numbers for the exome sequences reported in this paper are ss1208862056, ss1208863483, ss1208860559, ss1208862693, ss1208862520, ss1208863303, ss1208863213, ss1208863671, ss1208861977, ss1208862000, ss1208862346, ss1208862176, ss1208863049, and ss1208862880. Publisher Copyright: {\textcopyright} 2016 American College of Medical Genetics and Genomics.",
year = "2016",
month = jun,
day = "1",
doi = "10.1038/gim.2015.137",
language = "English (US)",
volume = "18",
pages = "608--617",
journal = "Genetics in Medicine",
issn = "1098-3600",
publisher = "Lippincott Williams and Wilkins",
number = "6",
}