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

Tomasz Zemojtel, Sebastian Köhler, Luisa Mackenroth, Marten Jäger, Jochen Hecht, Peter Krawitz, Luitgard Graul-Neumann, Sandra Doelken, Nadja Ehmke, Malte Spielmann, Nancy Christine Øien, Michal R. Schweiger, Ulrike Krüger, Götz Frommer, Björn Fischer, Uwe Kornak, Ricarda Flöttmann, Amin Ardeshirdavani, Yves Moreau, Suzanna E. LewisMelissa Haendel, Damian Smedley, Denise Horn, Stefan Mundlos, Peter N. Robinson

Research output: Contribution to journalArticle

138 Scopus citations

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.

Original languageEnglish (US)
Article number252ra123
JournalScience translational medicine
Volume6
Issue number252
DOIs
StatePublished - Sep 3 2014

ASJC Scopus subject areas

  • Medicine(all)

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    Zemojtel, T., Köhler, S., Mackenroth, L., Jäger, M., Hecht, J., Krawitz, P., Graul-Neumann, L., Doelken, S., Ehmke, N., Spielmann, M., Øien, N. C., Schweiger, M. R., Krüger, U., Frommer, G., Fischer, B., Kornak, U., Flöttmann, R., Ardeshirdavani, A., Moreau, Y., ... Robinson, P. N. (2014). Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Science translational medicine, 6(252), [252ra123]. https://doi.org/10.1126/scitranslmed.3009262