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Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism

Author

Listed:
  • Yurong Cheng

    (Faculty of Medicine and Medical Center - University of Freiburg
    Faculty of Biology, University of Freiburg)

  • Pascal Schlosser

    (Faculty of Medicine and Medical Center - University of Freiburg)

  • Johannes Hertel

    (School of Medicine, National University of Ireland, Galway
    University of Greifswald, University Medicine Greifswald, Department of Psychiatry and Psychotherapy)

  • Peggy Sekula

    (Faculty of Medicine and Medical Center - University of Freiburg)

  • Peter J. Oefner

    (University of Regensburg)

  • Ute Spiekerkoetter

    (Medical Center and Faculty of Medicine - University of Freiburg)

  • Johanna Mielke

    (Bayer AG, Division Pharmaceuticals, Open Innovation & Digital Technologies)

  • Daniel F. Freitag

    (Bayer AG, Division Pharmaceuticals, Open Innovation & Digital Technologies)

  • Miriam Schmidts

    (Medical Center and Faculty of Medicine - University of Freiburg)

  • Florian Kronenberg

    (Medical University of Innsbruck)

  • Kai-Uwe Eckardt

    (University of Erlangen-Nürnberg
    Charité - Universitätsmedizin Berlin)

  • Ines Thiele

    (School of Medicine, National University of Ireland, Galway
    Division of Microbiology, National University of Ireland, Galway
    APC Microbiome Ireland)

  • Yong Li

    (Faculty of Medicine and Medical Center - University of Freiburg)

  • Anna Köttgen

    (Faculty of Medicine and Medical Center - University of Freiburg
    Albert-Ludwigs-Universität Freiburg)

Abstract

Metabolite levels in urine may provide insights into genetic mechanisms shaping their related pathways. We therefore investigate the cumulative contribution of rare, exonic genetic variants on urine levels of 1487 metabolites and 53,714 metabolite ratios among 4864 GCKD study participants. Here we report the detection of 128 significant associations involving 30 unique genes, 16 of which are known to underlie inborn errors of metabolism. The 30 genes are strongly enriched for shared expression in liver and kidney (odds ratio = 65, p-FDR = 3e−7), with hepatocytes and proximal tubule cells as driving cell types. Use of UK Biobank whole-exome sequencing data links genes to diseases connected to the identified metabolites. In silico constraint-based modeling of gene knockouts in a virtual whole-body, organ-resolved metabolic human correctly predicts the observed direction of metabolite changes, highlighting the potential of linking population genetics to modeling. Our study implicates candidate variants and genes for inborn errors of metabolism.

Suggested Citation

  • Yurong Cheng & Pascal Schlosser & Johannes Hertel & Peggy Sekula & Peter J. Oefner & Ute Spiekerkoetter & Johanna Mielke & Daniel F. Freitag & Miriam Schmidts & Florian Kronenberg & Kai-Uwe Eckardt & , 2021. "Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20877-8
    DOI: 10.1038/s41467-020-20877-8
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