Phenotyping: Targeting genotype's rich cousin for diagnosis

Authors

  • Gareth Baynam,

    Corresponding author
    1. Genetic Services of Western Australia, Princess Margaret Hospital for Children, Perth, Western Australia, Australia
    2. School of Paediatrics and Child Health, University of Western Australia, Perth, Western Australia, Australia
    3. Office of Population Health Genomics, Department of Health, Government of Western Australia, Perth, Western Australia, Australia
    4. Institute for Immunology and Infectious Diseases, Murdoch University, Perth, Western Australia, Australia
    • Correspondence: Dr Gareth Baynam, School of Paediatrics and Child Health, University of Western Australia, Perth, WA 6151, Australia. Fax: 61893401678; email: gareth.baynam@health.wa.gov.au

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  • Mark Walters,

    1. Cranio-Maxillo-Facial Unit, Princess Margaret Hospital for Children, Perth, Western Australia, Australia
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  • Peter Claes,

    1. Medical Imaging Research Centre, Faculty of Engineering, KU Leuven, Leuven, Belgium
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  • Stefanie Kung,

    1. School of Paediatrics and Child Health, University of Western Australia, Perth, Western Australia, Australia
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  • Peter LeSouef,

    1. School of Paediatrics and Child Health, University of Western Australia, Perth, Western Australia, Australia
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  • Hugh Dawkins,

    1. School of Pathology and Laboratory Medicine, University of Western Australia, Perth, Western Australia, Australia
    2. Office of Population Health Genomics, Department of Health, Government of Western Australia, Perth, Western Australia, Australia
    3. Centre for Population Health Research, Curtin Health Innovation Research Institute, Curtin University of Technology, Perth, Western Australia, Australia
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  • Matthew Bellgard,

    1. Centre for Comparative Genomics, Murdoch University, Perth, Western Australia, Australia
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  • Marta Girdea,

    1. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
    2. Centre for Computational Medicine, Hospital for Sick Children, Toronto, Ontario, Canada
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  • Michael Brudno,

    1. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
    2. Centre for Computational Medicine, Hospital for Sick Children, Toronto, Ontario, Canada
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  • Peter Robinson,

    1. Institute of Medical Genetics and Human Genetics, Charité – Universitätsmedizin, Berlin, Germany
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  • Andreas Zankl,

    1. Discipline of Genetic Medicine, University of Sydney, Sydney, New South Wales, Australia
    2. Academic Department of Medical Genetics, Western Sydney Genetics Program, Sydney Children's Hospital Network, Sydney, New South Wales, Australia
    3. Centre for Clinical Research, University of Queensland, Brisbane, Queensland, Australia
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  • Tudor Groza,

    1. School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Queensland, Australia
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  • David Gillett,

    1. Cranio-Maxillo-Facial Unit, Princess Margaret Hospital for Children, Perth, Western Australia, Australia
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  • Jack Goldblatt

    1. Genetic Services of Western Australia, Princess Margaret Hospital for Children, Perth, Western Australia, Australia
    2. School of Paediatrics and Child Health, University of Western Australia, Perth, Western Australia, Australia
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  • Conflict of interest: None declared.

Abstract

There are many current and evolving tools to assist clinicians in their daily work of phenotyping. In medicine, the term ‘phenotype’ is usually taken to mean some deviation from normal morphology, physiology and behaviour. It is ascertained via history, examination and investigations, and a primary aim is diagnosis. Therefore, doctors are, by necessity, expert ‘phenotypers’. There is an inherent and partially realised power in phenotypic information that when harnessed can improve patient care. Furthermore, phenotyping developments are increasingly important in an era of rapid advances in genomic technology. Fortunately, there is an expanding network of phenotyping tools that are poised for clinical translation. These tools will preferentially be implemented to mirror clinical workflows and to integrate with advances in genomic and information-sharing technologies. This will synergise with and augment the clinical acumen of medical practitioners. We outline key enablers of the ascertainment, integration and interrogation of clinical phenotype by using genetic diseases, particularly rare ones, as a theme. Successes from the test bed or rare diseases will support approaches to common disease.

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