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Integration of molecular profiles in a longitudinal wellness profiling cohort

Author

Listed:
  • Abdellah Tebani

    (KTH Royal Institute of Technology)

  • Anders Gummesson

    (University of Gothenburg
    Sahlgrenska University Hospital, Department of Clinical Genetics and Genomics)

  • Wen Zhong

    (KTH Royal Institute of Technology)

  • Ina Schuppe Koistinen

    (KTH Royal Institute of Technology
    Karolinska Institutet)

  • Tadepally Lakshmikanth

    (Karolinska Institutet)

  • Lisa M. Olsson

    (University of Gothenburg)

  • Fredrik Boulund

    (Karolinska Institutet)

  • Maja Neiman

    (KTH Royal Institute of Technology)

  • Hans Stenlund

    (Umeå University)

  • Cecilia Hellström

    (KTH Royal Institute of Technology)

  • Max J. Karlsson

    (KTH Royal Institute of Technology)

  • Muhammad Arif

    (KTH Royal Institute of Technology)

  • Tea Dodig-Crnković

    (KTH Royal Institute of Technology)

  • Adil Mardinoglu

    (KTH Royal Institute of Technology
    King’s College London)

  • Sunjae Lee

    (KTH Royal Institute of Technology)

  • Cheng Zhang

    (KTH Royal Institute of Technology)

  • Yang Chen

    (Karolinska Institutet)

  • Axel Olin

    (Karolinska Institutet)

  • Jaromir Mikes

    (Karolinska Institutet)

  • Hanna Danielsson

    (Karolinska Institutet)

  • Kalle Feilitzen

    (KTH Royal Institute of Technology)

  • Per-Anders Jansson

    (University of Gothenburg
    Sahlgrenska University Hospital, Department of Internal Medicine)

  • Oskar Angerås

    (University of Gothenburg
    Sahlgrenska University Hospital, Department of Cardiology)

  • Mikael Huss

    (Codon Consulting
    Karolinska Institutet)

  • Sanela Kjellqvist

    (Karolinska Institutet)

  • Jacob Odeberg

    (KTH Royal Institute of Technology)

  • Fredrik Edfors

    (KTH Royal Institute of Technology)

  • Valentina Tremaroli

    (University of Gothenburg)

  • Björn Forsström

    (KTH Royal Institute of Technology)

  • Jochen M. Schwenk

    (KTH Royal Institute of Technology)

  • Peter Nilsson

    (KTH Royal Institute of Technology)

  • Thomas Moritz

    (Swedish University of Agricultural Sciences)

  • Fredrik Bäckhed

    (University of Gothenburg
    Sahlgrenska University Hospital, Department of Clinical Physiology
    University of Copenhagen)

  • Lars Engstrand

    (Karolinska Institutet)

  • Petter Brodin

    (Karolinska Institutet)

  • Göran Bergström

    (University of Gothenburg
    Sahlgrenska University Hospital, Department of Clinical Physiology)

  • Mathias Uhlen

    (KTH Royal Institute of Technology
    Danish Technical University)

  • Linn Fagerberg

    (KTH Royal Institute of Technology)

Abstract

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.

Suggested Citation

  • Abdellah Tebani & Anders Gummesson & Wen Zhong & Ina Schuppe Koistinen & Tadepally Lakshmikanth & Lisa M. Olsson & Fredrik Boulund & Maja Neiman & Hans Stenlund & Cecilia Hellström & Max J. Karlsson &, 2020. "Integration of molecular profiles in a longitudinal wellness profiling cohort," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18148-7
    DOI: 10.1038/s41467-020-18148-7
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