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Integrated molecular, clinical, and ontological analysis identifies overlooked disease relationships

Winston A. Haynes, Rohit Vashisht, Francesco Vallania, Charles Liu, Gregory L. Gaskin, Erika Bongen, Shane Lofgren, Timothy E. Sweeney, Paul J. Utz, Nigam H. Shah, Purvesh Khatri
doi: https://doi.org/10.1101/214833
Winston A. Haynes
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
cBiomedical Informatics Training Program, Stanford University, Stanford, California, USA
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Rohit Vashisht
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
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Francesco Vallania
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Charles Liu
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
dStanford Institutes of Medicine Research Program, Stanford University, Stanford, California, USA
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Gregory L. Gaskin
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
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Erika Bongen
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
eStanford Immunology, Stanford University, Stanford, California, USA
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Shane Lofgren
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Timothy E. Sweeney
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Paul J. Utz
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Nigam H. Shah
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
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  • For correspondence: nigam@stanford.edu pkhatri@stanford.edu
Purvesh Khatri
aStanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA
bStanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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  • For correspondence: nigam@stanford.edu pkhatri@stanford.edu
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Abstract

Existing knowledge of human disease relationships is incomplete. To establish a comprehensive understanding of disease, we integrated transcriptome profiles of 41,000 human samples with clinical profiles of 2 million patients, across 89 diseases. Based on transcriptome data, autoimmune diseases clustered with their specific infectious triggers, and brain disorders clustered by disease class. Clinical profiles clustered diseases according to the similarity of their initial manifestation and later complications, identifying disease relationships absent in prior co-occurrence analyses. Our integrated analysis of transcriptome and clinical profiles identified overlooked, therapeutically actionable disease relationships, such as between myositis and interstitial cystitis. Our improved understanding of disease relationships will identify disease mechanisms, offer novel therapeutic targets, and create synergistic research opportunities.

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Posted February 16, 2018.
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Integrated molecular, clinical, and ontological analysis identifies overlooked disease relationships
Winston A. Haynes, Rohit Vashisht, Francesco Vallania, Charles Liu, Gregory L. Gaskin, Erika Bongen, Shane Lofgren, Timothy E. Sweeney, Paul J. Utz, Nigam H. Shah, Purvesh Khatri
bioRxiv 214833; doi: https://doi.org/10.1101/214833
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Integrated molecular, clinical, and ontological analysis identifies overlooked disease relationships
Winston A. Haynes, Rohit Vashisht, Francesco Vallania, Charles Liu, Gregory L. Gaskin, Erika Bongen, Shane Lofgren, Timothy E. Sweeney, Paul J. Utz, Nigam H. Shah, Purvesh Khatri
bioRxiv 214833; doi: https://doi.org/10.1101/214833

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