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Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide

Author

Listed:
  • Petros Andrikopoulos

    (Imperial College London
    Imperial College London)

  • Judith Aron-Wisnewsky

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital)

  • Rima Chakaroun

    (University of Leipzig Medical Center
    University of Gothenburg)

  • Antonis Myridakis

    (Imperial College London
    Imperial College London)

  • Sofia K. Forslund

    (European Molecular Biology Laboratory
    Experimental and Clinical Research Center, a cooperation of Charité-Universitätsmedizin and the Max-Delbrück Center
    Max Delbrück Center for Molecular Medicine (MDC)
    Charité University Hospital)

  • Trine Nielsen

    (University of Copenhagen)

  • Solia Adriouch

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics))

  • Bridget Holmes

    (Danone Research)

  • Julien Chilloux

    (Imperial College London)

  • Sara Vieira-Silva

    (KU Leuven
    VIB
    University Medical Center of the Johannes Gutenberg-University Mainz
    Institute of Molecular Biology (IMB))

  • Gwen Falony

    (KU Leuven
    VIB
    University Medical Center of the Johannes Gutenberg-University Mainz
    Institute of Molecular Biology (IMB))

  • Joe-Elie Salem

    (Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital)

  • Fabrizio Andreelli

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital)

  • Eugeni Belda

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Sorbonne Université, IRD, Unité de Modélisation Mathématique et Informatique des Systèmes Complexes, UMMISCO)

  • Julius Kieswich

    (The Royal London Hospital
    Queen Mary University of London)

  • Kanta Chechi

    (Imperial College London
    Imperial College London)

  • Francesc Puig-Castellvi

    (European Genomics Institute for Diabetes, EGENODIA, INSERM U1283, CNRS UMR8199, Institut Pasteur de Lille, Lille University Hospital, University of Lille)

  • Mickael Chevalier

    (European Genomics Institute for Diabetes, EGENODIA, INSERM U1283, CNRS UMR8199, Institut Pasteur de Lille, Lille University Hospital, University of Lille)

  • Emmanuelle Chatelier

    (Metagenopolis, INRA, AgroParisTech, Université Paris-Saclay)

  • Michael T. Olanipekun

    (Imperial College London)

  • Lesley Hoyles

    (Nottingham Trent University)

  • Renato Alves

    (European Molecular Biology Laboratory)

  • Gerard Helft

    (Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital
    Institute of Cardiometabolism and Nutrition, ICAN, INSERM)

  • Richard Isnard

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital)

  • Lars Køber

    (University of Copenhagen)

  • Luis Pedro Coelho

    (European Molecular Biology Laboratory)

  • Christine Rouault

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics))

  • Dominique Gauguier

    (INSERM UMR 1124, Université de Paris
    McGill Genome Centre, McGill University)

  • Jens Peter Gøtze

    (University of Copenhagen)

  • Edi Prifti

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Sorbonne Université, IRD, Unité de Modélisation Mathématique et Informatique des Systèmes Complexes, UMMISCO)

  • Philippe Froguel

    (European Genomics Institute for Diabetes, EGENODIA, INSERM U1283, CNRS UMR8199, Institut Pasteur de Lille, Lille University Hospital, University of Lille
    Imperial College London)

  • Jean-Daniel Zucker

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Sorbonne Université, IRD, Unité de Modélisation Mathématique et Informatique des Systèmes Complexes, UMMISCO)

  • Fredrik Bäckhed

    (University of Gothenburg
    University of Copenhagen)

  • Henrik Vestergaard

    (University of Copenhagen
    Bornholms Hospital)

  • Torben Hansen

    (University of Copenhagen)

  • Jean-Michel Oppert

    (Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital)

  • Matthias Blüher

    (University of Leipzig Medical Center)

  • Jens Nielsen

    (Chalmers University of Technology)

  • Jeroen Raes

    (KU Leuven
    VIB)

  • Peer Bork

    (European Molecular Biology Laboratory
    Max Delbrück Center for Molecular Medicine (MDC)
    University of Würzburg
    Yonsei University)

  • Muhammad M. Yaqoob

    (The Royal London Hospital
    Queen Mary University of London)

  • Michael Stumvoll

    (University of Leipzig Medical Center)

  • Oluf Pedersen

    (University of Copenhagen
    Gentofte University Hospital)

  • S. Dusko Ehrlich

    (University College London)

  • Karine Clément

    (Sorbonne Université, INSERM, Nutrition and obesities; systemic approaches (NutriOmics)
    Assistance Publique Hôpitaux de Paris, Pitie-Salpêtrière Hospital)

  • Marc-Emmanuel Dumas

    (Imperial College London
    Imperial College London
    European Genomics Institute for Diabetes, EGENODIA, INSERM U1283, CNRS UMR8199, Institut Pasteur de Lille, Lille University Hospital, University of Lille
    McGill Genome Centre, McGill University)

Abstract

The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied “explainable” machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.

Suggested Citation

  • Petros Andrikopoulos & Judith Aron-Wisnewsky & Rima Chakaroun & Antonis Myridakis & Sofia K. Forslund & Trine Nielsen & Solia Adriouch & Bridget Holmes & Julien Chilloux & Sara Vieira-Silva & Gwen Fal, 2023. "Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39824-4
    DOI: 10.1038/s41467-023-39824-4
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    References listed on IDEAS

    as
    1. Doris Vandeputte & Gunter Kathagen & Kevin D’hoe & Sara Vieira-Silva & Mireia Valles-Colomer & João Sabino & Jun Wang & Raul Y. Tito & Lindsey De Commer & Youssef Darzi & Séverine Vermeire & Gwen Falo, 2017. "Quantitative microbiome profiling links gut community variation to microbial load," Nature, Nature, vol. 551(7681), pages 507-511, November.
    2. Tingley, Dustin & Yamamoto, Teppei & Hirose, Kentaro & Keele, Luke & Imai, Kosuke, 2014. "mediation: R Package for Causal Mediation Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i05).
    3. Ho, Daniel & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2011. "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i08).
    4. Noam Bar & Tal Korem & Omer Weissbrod & David Zeevi & Daphna Rothschild & Sigal Leviatan & Noa Kosower & Maya Lotan-Pompan & Adina Weinberger & Caroline I. Roy & Cristina Menni & Alessia Visconti & Ma, 2020. "A reference map of potential determinants for the human serum metabolome," Nature, Nature, vol. 588(7836), pages 135-140, December.
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