The GA4GH Phenopacket schema defines a computable representation of clinical data

Julius O B Jacobsen¹, Michael Baudis^{2

3}, Gareth S Baynam^{4

5

6}, Jacques S Beckmann⁷, Sergi Beltran^{8

9

10}, Orion J Buske¹¹, Tiffany J Callahan¹², Christopher G Chute¹³, Mélanie Courtot^{14

15}, Daniel Danis¹⁶, Olivier Elemento¹⁷, Andrea Essenwanger¹⁸, Robert R Freimuth¹⁹, Michael A Gargano¹⁶, Tudor Groza²⁰, Ada Hamosh²¹, Nomi L Harris²², Rajaram Kaliyaperumal²³, Kevin C Kent Lloyd^{24

25}, Aly Khalifa¹⁹, Peter M Krawitz²⁶, Sebastian Köhler²⁷, Brian J Laraway¹², Heikki Lehväslaiho²⁸, Leslie Matalonga⁸, Julie A McMurry¹², Alejandro Metke-Jimenez²⁹, Christopher J Mungall²², Monica C Munoz-Torres¹², Soichi Ogishima³⁰, Anastasios Papakonstantinou⁸, Davide Piscia⁸, Nikolas Pontikos^{31

32}, Núria Queralt-Rosinach²³, Marco Roos²³, Julian Sass¹⁸, Paul N Schofield^{33

34

35}, Dominik Seelow^{36

37}, Anastasios Siapos³⁸, Damian Smedley³⁹, Lindsay D Smith^{15

40}, Robin Steinhaus^{36

37}, Jagadish Chandrabose Sundaramurthi¹⁶, Emilia M Swietlik^{41

42

43}, Sylvia Thun¹⁸, Nicole A Vasilevsky¹², Alex H Wagner^{44

45}, Jeremy L Warner⁴⁶, Claus Weiland⁴⁷; GAGH Phenopacket Modeling Consortium; Melissa A Haendel⁴⁸, Peter N Robinson^{49

50}

Collaborators, Affiliations

Collaborators

GAGH Phenopacket Modeling Consortium:
Myles Axton, Lawrence Babb, Cornelius F Boerkoel, Bimal P Chaudhari, Hui-Lin Chin, Michel Dumontier, Nour Gazzaz, David P Hansen, Harry Hochheiser, Veronica A Kinsler, Hanns Lochmüller, Alexander R Mankovich, Gary I Saunders, Panagiotis I Sergouniotis, Rachel Thompson, Andreas Zankl

Affiliations

¹ William Harvey Research Institute, Queen Mary University of London, London, UK. j.jacobsen@qmul.ac.uk.
² Department of Molecular Life Sciences, University of Zurich, Zürich, Switzerland.
³ Computational Oncogenomics Group, Swiss Institute of Bioinformatics, Zürich, Switzerland.
⁴ Western Australian Register of Developmental Anomalies and Genetic Services of WA, King Edward Memorial Hospital, Perth, Western Australia, Australia.
⁵ Faculty of Health and Medical Sciences, Division of Paediatrics, University of Western Australia, Perth, Western Australia, Australia.
⁶ Genetic and Rare Diseases, Telethon Kids Institute, Perth, Western Australia, Australia.
⁷ Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
⁸ CNAG-CRG, Centre for Genomic Regulation (CRG), Bioinformatics Unit, The Barcelona Institute of Science and Technology, Barcelona, Spain.
⁹ Universitat Pompeu Fabra (UPF), Barcelona, Spain.
¹⁰ Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Spain.
¹¹ PhenoTips, Toronto, Ontario, Canada.
¹² Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹³ Schools of Medicine, Public Health, and Nursing, Baltimore, Johns Hopkins University, Baltimore, MD, USA.
¹⁴ European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Hinxton, UK.
¹⁵ Genome Informatics, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
¹⁶ Genomic Medicine, The Jackson Laboratory, Farmington, CT, USA.
¹⁷ Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
¹⁸ Core Facility Digital Medicine and Interoperability, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
¹⁹ Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
²⁰ EMBL-EBI, Cambridge, UK.
²¹ Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
²² Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
²³ Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
²⁴ Mouse Biology Program, University of California Davis, Davis, CA, USA.
²⁵ Department of Surgery, University of California Davis School of Medicine, Sacramento, CA, USA.
²⁶ University Hospital Bonn, Bonn, Germany, and Institute for Genomic Statistics and Bioinformatics, Bonn, Germany.
²⁷ Ada Health GmbH, Berlin, Germany.
²⁸ Sensitive Data Services, CSC-IT Center for Science, Espoo, Finland.
²⁹ The Australian e-Health Research Centre, CSIRO, Herston, Queensland, Australia.
³⁰ Tohoku University, INGEM, Sendai, Japan.
³¹ Institute of Ophthalmology, University College London, London, UK.
³² Genetics Service, Moorfields Eye Hospital, London, UK.
³³ Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
³⁴ Mammalian Genetics, The Jackson Laboratory, Bar Harbor, ME, USA.
³⁵ The Alan Turing Institute, London, UK.
³⁶ Bioinformatics and Translational Genetics, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
³⁷ Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
³⁸ Lifebit Biotech Ltd., London, UK.
³⁹ William Harvey Research Institute, Queen Mary University of London, London, UK.
⁴⁰ Global Alliance for Genomics and Health, N/A, Toronto, Ontario, Canada.
⁴¹ 40Medicine Department, University of Cambridge, Cambridge, UK.
⁴² Respiratory Medicine Department, Addenbrooke's Hospital, Cambridge, UK.
⁴³ Cambridge Centre for Lung Infection, Royal Papworth Hospital, Cambridge, UK.
⁴⁴ The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.
⁴⁵ Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA.
⁴⁶ Departments of Medicine and Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
⁴⁷ Senckenberg-Leibniz Institution for Biodiversity and Earth System Research, Data and Modelling Centre, Frankfurt/Main, Germany.
⁴⁸ Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. melissa@tislab.org.
⁴⁹ Genomic Medicine, The Jackson Laboratory, Farmington, CT, USA. peter.robinson@jax.org.
⁵⁰ Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA. peter.robinson@jax.org.

PMID: 35705716
PMCID: PMC9363006
DOI: 10.1038/s41587-022-01357-4

The GA4GH Phenopacket schema defines a computable representation of clinical data

Julius O B Jacobsen et al. Nat Biotechnol. 2022 Jun.

. 2022 Jun;40(6):817-820.

doi: 10.1038/s41587-022-01357-4.

Authors

Collaborators

GAGH Phenopacket Modeling Consortium:
Myles Axton, Lawrence Babb, Cornelius F Boerkoel, Bimal P Chaudhari, Hui-Lin Chin, Michel Dumontier, Nour Gazzaz, David P Hansen, Harry Hochheiser, Veronica A Kinsler, Hanns Lochmüller, Alexander R Mankovich, Gary I Saunders, Panagiotis I Sergouniotis, Rachel Thompson, Andreas Zankl

Affiliations

¹ William Harvey Research Institute, Queen Mary University of London, London, UK. j.jacobsen@qmul.ac.uk.
² Department of Molecular Life Sciences, University of Zurich, Zürich, Switzerland.
³ Computational Oncogenomics Group, Swiss Institute of Bioinformatics, Zürich, Switzerland.
⁴ Western Australian Register of Developmental Anomalies and Genetic Services of WA, King Edward Memorial Hospital, Perth, Western Australia, Australia.
⁵ Faculty of Health and Medical Sciences, Division of Paediatrics, University of Western Australia, Perth, Western Australia, Australia.
⁶ Genetic and Rare Diseases, Telethon Kids Institute, Perth, Western Australia, Australia.
⁷ Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
⁸ CNAG-CRG, Centre for Genomic Regulation (CRG), Bioinformatics Unit, The Barcelona Institute of Science and Technology, Barcelona, Spain.
⁹ Universitat Pompeu Fabra (UPF), Barcelona, Spain.
¹⁰ Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Spain.
¹¹ PhenoTips, Toronto, Ontario, Canada.
¹² Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹³ Schools of Medicine, Public Health, and Nursing, Baltimore, Johns Hopkins University, Baltimore, MD, USA.
¹⁴ European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Hinxton, UK.
¹⁵ Genome Informatics, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
¹⁶ Genomic Medicine, The Jackson Laboratory, Farmington, CT, USA.
¹⁷ Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
¹⁸ Core Facility Digital Medicine and Interoperability, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
¹⁹ Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
²⁰ EMBL-EBI, Cambridge, UK.
²¹ Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
²² Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
²³ Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
²⁴ Mouse Biology Program, University of California Davis, Davis, CA, USA.
²⁵ Department of Surgery, University of California Davis School of Medicine, Sacramento, CA, USA.
²⁶ University Hospital Bonn, Bonn, Germany, and Institute for Genomic Statistics and Bioinformatics, Bonn, Germany.
²⁷ Ada Health GmbH, Berlin, Germany.
²⁸ Sensitive Data Services, CSC-IT Center for Science, Espoo, Finland.
²⁹ The Australian e-Health Research Centre, CSIRO, Herston, Queensland, Australia.
³⁰ Tohoku University, INGEM, Sendai, Japan.
³¹ Institute of Ophthalmology, University College London, London, UK.
³² Genetics Service, Moorfields Eye Hospital, London, UK.
³³ Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
³⁴ Mammalian Genetics, The Jackson Laboratory, Bar Harbor, ME, USA.
³⁵ The Alan Turing Institute, London, UK.
³⁶ Bioinformatics and Translational Genetics, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
³⁷ Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
³⁸ Lifebit Biotech Ltd., London, UK.
³⁹ William Harvey Research Institute, Queen Mary University of London, London, UK.
⁴⁰ Global Alliance for Genomics and Health, N/A, Toronto, Ontario, Canada.
⁴¹ 40Medicine Department, University of Cambridge, Cambridge, UK.
⁴² Respiratory Medicine Department, Addenbrooke's Hospital, Cambridge, UK.
⁴³ Cambridge Centre for Lung Infection, Royal Papworth Hospital, Cambridge, UK.
⁴⁴ The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.
⁴⁵ Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA.
⁴⁶ Departments of Medicine and Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
⁴⁷ Senckenberg-Leibniz Institution for Biodiversity and Earth System Research, Data and Modelling Centre, Frankfurt/Main, Germany.
⁴⁸ Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. melissa@tislab.org.
⁴⁹ Genomic Medicine, The Jackson Laboratory, Farmington, CT, USA. peter.robinson@jax.org.
⁵⁰ Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA. peter.robinson@jax.org.

PMID: 35705716
PMCID: PMC9363006
DOI: 10.1038/s41587-022-01357-4

No abstract available

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Figures

**Figure 1.. Phenopacket schema overview.**
The GA4GH Phenopacket schema consists of several optional elements, each of which contains information about a certain topic, such as phenotype, variant, or pedigree. An element can contain other elements, which allows a hierarchical representation of data. For instance, Phenopacket contains elements of type Individual, PhenotypicFeature, Biosample, and so on. Individual elements can therefore be regarded as building blocks that are combined to create larger structures. Colors represent the major themes of elements within the schema.

See this image and copyright information in PMC

References

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1. Hripcsak G & Albers DJ Next-generation phenotyping of electronic health records. J. Am. Med. Inform. Assoc 20, 117–121 (2013). - PMC - PubMed
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1. Wei W-Q & Denny JC Extracting research-quality phenotypes from electronic health records to support precision medicine. Genome Med. 7, 41 (2015). - PMC - PubMed
1. Richesson RL, Sun J, Pathak J, Kho AN & Denny JC Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods. Artif. Intell. Med 71, 57–61 (2016). - PMC - PubMed

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The GA4GH Phenopacket schema defines a computable representation of clinical data

Collaborators

Affiliations

The GA4GH Phenopacket schema defines a computable representation of clinical data

Authors

Collaborators

Affiliations

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References

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LinkOut - more resources

Full Text Sources