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  Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome

Zemojtel, T., Köhler, S., Mackenroth, L., Jäger, M., Hecht, J., Krawitz, P., et al. (2014). Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Science Translational Madicine, 6(252): 252ra123. doi:10.1126/scitranslmed.3009262.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-B433-E Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-B436-8
Genre: Journal Article

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© 2014 American Association for the Advancement of Science
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 Creators:
Zemojtel, T., Author
Köhler, S., Author
Mackenroth, L., Author
Jäger, M., Author
Hecht, J.1, Author              
Krawitz, P.2, Author
Graul-Neumann, L., Author
Doelken, S., Author
Ehmke, N., Author
Spielmann, M.1, Author              
Oien, N. C., Author
Schweiger, M. R.3, Author              
Krüger, U., Author
Frommer, G., Author
Fischer, B.2, Author
Kornak, U.1, Author              
Flöttmann, R., Author
Ardeshirdavani, A., Author
Moreau, Y., Author
Lewis, S. E., Author
Haendel, M., AuthorSmedley, D., AuthorHorn, D., AuthorMundlos, S.1, Author              Robinson, P. N.1, Author               more..
Affiliations:
1Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433557              
2Max Planck Society, ou_persistent13              
3Cancer Genomics (Michal-Ruth Schweiger), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479649              

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 Abstract: Less than half of patients with suspected genetic disease receive a molecular diagnosis. We have therefore integrated next-generation sequencing (NGS), bioinformatics, and clinical data into an effective diagnostic workflow. We used variants in the 2741 established Mendelian disease genes [the disease-associated genome (DAG)] to develop a targeted enrichment DAG panel (7.1 Mb), which achieves a coverage of 20-fold or better for 98% of bases. Furthermore, we established a computational method [Phenotypic Interpretation of eXomes (PhenIX)] that evaluated and ranked variants based on pathogenicity and semantic similarity of patients' phenotype described by Human Phenotype Ontology (HPO) terms to those of 3991 Mendelian diseases. In computer simulations, ranking genes based on the variant score put the true gene in first place less than 5% of the time; PhenIX placed the correct gene in first place more than 86% of the time. In a retrospective test of PhenIX on 52 patients with previously identified mutations and known diagnoses, the correct gene achieved a mean rank of 2.1. In a prospective study on 40 individuals without a diagnosis, PhenIX analysis enabled a diagnosis in 11 cases (28%, at a mean rank of 2.4). Thus, the NGS of the DAG followed by phenotype-driven bioinformatic analysis allows quick and effective differential diagnostics in medical genetics.

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Language(s): eng - English
 Dates: 2014-09-03
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1126/scitranslmed.3009262
ISSN: 1946-6242 (Electronic)1946-6234 (Print)
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Title: Science Translational Madicine
Source Genre: Journal
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Publ. Info: American Association for the Advancement of Science
Pages: - Volume / Issue: 6 (252) Sequence Number: 252ra123 Start / End Page: - Identifier: -