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Precision medicine in the clouds

Nature Biotechnology volume 36, pages 678–680 (2018)Cite this article

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An Author Correction to this article was published on 01 October 2018

This article has been updated

To the Editor:

P100 is an exploratory study of associations in networks of biomarkers and risk factors established from large and dynamic data clouds of 108 participants. Over the course of a 9-month period, participants underwent whole-genome sequencing (yielding 127 polygenic scores for disease risks plus three copy number variations); testing of metabolome (643 metabolites), proteome (262 proteins) and microbiome (4,616 taxonomic units) three times; 218 other clinical tests and measurements; and daily activity tracking via 'quantified self' technologies. Associations between these biomarkers yielded a total of 3,470 connections in a correlation network. The P100 study is a project designed to display the potentials for novel technologies and gather support for precision or P4 medicine (predictive, preventive, personalized and participatory), and it has received prominent publicity in Nature5. The P100 will also be scaled up to include 100,000 participants in the 100K Wellness Project3. Against this background, we provide our view of whether the P100 study actually supports the prospect of substantial benefits from data-driven disease prevention and argue that it presents severe challenges.

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Change history

  • 04 September 2018

    In the version of this article initially published, author John Brodersen's name was misspelled Broderson and a second affiliation for him was missing: Primary Health Care Research Unit, Region Zealand, Denmark. The error has been corrected in the HTML and PDF versions of the article.

  • 01 October 2018

    Nat. Biotechnol. 36, 678–680 (2018); published online 6 August 2018; corrected after print 4 September 2018 In the version of this article initially published, author John Brodersen's name was misspelled Broderson and a second affiliation for him was missing: Primary Health Care Research Unit, Region Zealand, Denmark.

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Acknowledgements

H.V. wishes to thank L. Getz and I. Hetlevik at the General Practice Research Unit, Norwegian University of Science and Technology; this article builds on his PhD project, which they supervised.

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Authors and Affiliations

  1. Department of Public Health and Nursing, Norwegian University of Science and Technology, General Practice Research Unit, Trondheim, Norway

    Henrik Vogt

  2. Department of Science Education & Centre for Medical Science and Technology Studies, Department of Public Health, Section for History and Philosophy of Science, University of Denmark, Copenhagen, Denmark

    Sara Green

  3. Department of Public Health, Section of General Practice & Research Unit for General Practice, University of Copenhagen, Copenhagen, Denmark

    John Brodersen

  4. Primary Health Care Research Unit, Region Zealand, Denmark

    John Brodersen

Authors
  1. Henrik Vogt
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  2. Sara Green
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  3. John Brodersen
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Correspondence to Henrik Vogt.

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Vogt, H., Green, S. & Brodersen, J. Precision medicine in the clouds. Nat Biotechnol 36, 678–680 (2018). https://doi.org/10.1038/nbt.4210

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