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PEDIA: prioritization of exome data by image analysis.
Hsieh, Tzung-Chien; Mensah, Martin A; Pantel, Jean T; Aguilar, Dione; Bar, Omri; Bayat, Allan; Becerra-Solano, Luis; Bentzen, Heidi B; Biskup, Saskia; Borisov, Oleg; Braaten, Oivind; Ciaccio, Claudia; Coutelier, Marie; Cremer, Kirsten; Danyel, Magdalena; Daschkey, Svenja; Eden, Hilda David; Devriendt, Koenraad; Wilson, Sandra; Douzgou, Sofia; Dukic, Dejan; Ehmke, Nadja; Fauth, Christine; Fischer-Zirnsak, Björn; Fleischer, Nicole; Gabriel, Heinz; Graul-Neumann, Luitgard; Gripp, Karen W; Gurovich, Yaron; Gusina, Asya; Haddad, Nechama; Hajjir, Nurulhuda; Hanani, Yair; Hertzberg, Jakob; Hoertnagel, Konstanze; Howell, Janelle; Ivanovski, Ivan; Kaindl, Angela; Kamphans, Tom; Kamphausen, Susanne; Karimov, Catherine; Kathom, Hadil; Keryan, Anna; Knaus, Alexej; Köhler, Sebastian; Kornak, Uwe; Lavrov, Alexander; Leitheiser, Maximilian; Lyon, Gholson J; Mangold, Elisabeth.
Afiliação
  • Hsieh TC; Institute of Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany.
  • Mensah MA; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Pantel JT; Berlin Institute of Health (BIH), Berlin, Germany.
  • Aguilar D; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Bar O; Berlin Institute of Health (BIH), Berlin, Germany.
  • Bayat A; Institute of Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany.
  • Becerra-Solano L; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Bentzen HB; Berlin Institute of Health (BIH), Berlin, Germany.
  • Biskup S; Centro de Cáncer de Mama, Tecnológico de Monterrey, Monterrey, Mexico.
  • Borisov O; FDNA Inc., Boston, MA, USA.
  • Braaten O; Rigshospitalet, Department of Neurology, Copenhagen, Denmark.
  • Ciaccio C; Unidad de Investigación Médica en Medicina Reproductiva, Mexico City, Mexico.
  • Coutelier M; Centre for Medical Ethics, Faculty of Medicine and the Norwegian Research Center for Computers and Law, Faculty of Law, University of Oslo, Oslo, Norway.
  • Cremer K; CeGaT GmbH, Tübingen, Germany.
  • Danyel M; Institute of Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany.
  • Daschkey S; Faculty of Medicine, Department of Medical Genetics, University of Oslo, Blindern, Oslo, Norway.
  • Eden HD; Developmental Neurology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
  • Devriendt K; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Wilson S; Department of Human Genetics, University Hospital of Bonn, Bonn, Germany.
  • Douzgou S; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Dukic D; Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
  • Ehmke N; FDNA Inc., Boston, MA, USA.
  • Fauth C; Department of Human Genetics, KU Leuven, Leuven, Belgium.
  • Fischer-Zirnsak B; Department of Human Genetics, University of Hamburg, Hamburg, Germany.
  • Fleischer N; Manchester Centre for Genomic Medicine, St Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust Manchester Academic Health Sciences Centre, Manchester, United Kingdom.
  • Gabriel H; School of Biological Sciences, Division of Evolution and Genomic Sciences, University of Manchester, Manchester, United Kingdom.
  • Graul-Neumann L; Institute of Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany.
  • Gripp KW; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Gurovich Y; Division of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria.
  • Gusina A; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Haddad N; FDNA Inc., Boston, MA, USA.
  • Hajjir N; Center for Genomics and Transcriptomics, Eberhard Karls University of Tübingen, Tübingen, Germany.
  • Hanani Y; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Hertzberg J; A. I. duPont Hospital for Children, Wilmington, DE, USA.
  • Hoertnagel K; FDNA Inc., Boston, MA, USA.
  • Howell J; National Research and Applied Medicine Centre 'Mother and Child'', Minsk, Belarus.
  • Ivanovski I; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Kaindl A; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Kamphans T; FDNA Inc., Boston, MA, USA.
  • Kamphausen S; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Medical Genetics and Human Genetics, Berlin, Germany.
  • Karimov C; CeGaT GmbH, Tübingen, Germany.
  • Kathom H; Lineagen, Salt Lake City, Utah, USA.
  • Keryan A; Clinical Genetics Unit, AUSL-IRCCS Reggio Emilia, Reggio Emilia, Italy.
  • Knaus A; Center for Chronically Sick Children (Sozialpädiatrisches Zentrum, SPZ), Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Köhler S; GeneTalk, Bonn, Germany.
  • Kornak U; University Hospital Magdeburg, Magdeburg, Germany.
  • Lavrov A; Children's Hospital of Los Angeles, Los Angeles, CA, USA.
  • Leitheiser M; Department of Pediatrics, Medical University of Sofia, Sofia, Bulgaria.
  • Lyon GJ; Children's Hospital of Los Angeles, Los Angeles, CA, USA.
  • Mangold E; Institute of Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany.
Genet Med ; 21(12): 2807-2814, 2019 12.
Article em En | MEDLINE | ID: mdl-31164752
ABSTRACT

PURPOSE:

Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists.

METHODS:

Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds.

RESULTS:

The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene.

CONCLUSION:

Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Análise de Sequência de DNA / Biologia Computacional Tipo de estudo: Guideline Limite: Female / Humans / Male Idioma: En Ano de publicação: 2019 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Análise de Sequência de DNA / Biologia Computacional Tipo de estudo: Guideline Limite: Female / Humans / Male Idioma: En Ano de publicação: 2019 Tipo de documento: Article