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Sci Transl Med. 2014 Sep 3;6(252):252ra123. doi: 10.1126/scitranslmed.3009262.

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

Author information

1
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland. Labor Berlin-Charité Vivantes GmbH, Humangenetik, Föhrer Straße 15, 13353 Berlin, Germany.
2
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
3
Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. Berlin-Brandenburg Center for Regenerative Therapies, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.
4
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany.
5
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Max Delbrück Center for Molecular Medicine, Robert-Rössle-Str. 10, 13125 Berlin, Germany.
6
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. Cologne Center for Genomics, University of Cologne, D-50931 Cologne, Germany.
7
Agilent Technologies, Hewlett-Packard-Straße 8, 76337 Waldbronn, Germany.
8
Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, 3001 Leuven, Belgium.
9
Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
10
University Library and Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland, OR 97327, USA.
11
Mouse Informatics Group, Wellcome Trust Sanger Institute, CB10 1SA Hinxton, UK.
12
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. Berlin-Brandenburg Center for Regenerative Therapies, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.
13
Institute for Medical Genetics and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. Berlin-Brandenburg Center for Regenerative Therapies, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany. Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany. peter.robinson@charite.de.

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.

PMID:
25186178
PMCID:
PMC4512639
DOI:
10.1126/scitranslmed.3009262
[Indexed for MEDLINE]
Free PMC Article

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