IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-33050-0.html
   My bibliography  Save this article

An online atlas of human plasma metabolite signatures of gut microbiome composition

Author

Listed:
  • Koen F. Dekkers

    (Uppsala University)

  • Sergi Sayols-Baixeras

    (Uppsala University
    CIBER Cardiovascular diseases (CIBERCV), Instituto de Salud Carlos III)

  • Gabriel Baldanzi

    (Uppsala University)

  • Christoph Nowak

    (Karolinska Institute)

  • Ulf Hammar

    (Uppsala University)

  • Diem Nguyen

    (Uppsala University)

  • Georgios Varotsis

    (Uppsala University)

  • Louise Brunkwall

    (Lund University)

  • Nynne Nielsen

    (Clinical Microbiomics A/S)

  • Aron C. Eklund

    (Clinical Microbiomics A/S)

  • Jacob Bak Holm

    (Clinical Microbiomics A/S)

  • H. Bjørn Nielsen

    (Clinical Microbiomics A/S)

  • Filip Ottosson

    (Lund University)

  • Yi-Ting Lin

    (Uppsala University)

  • Shafqat Ahmad

    (Uppsala University)

  • Lars Lind

    (Uppsala University)

  • Johan Sundström

    (Uppsala University
    University of New South Wales)

  • Gunnar Engström

    (Lund University)

  • J. Gustav Smith

    (Sahlgrenska University Hospital
    Lund University and Skåne University Hospital
    Lund University)

  • Johan Ärnlöv

    (Karolinska Institute
    Dalarna University)

  • Marju Orho-Melander

    (Lund University)

  • Tove Fall

    (Uppsala University)

Abstract

Human gut microbiota produce a variety of molecules, some of which enter the bloodstream and impact health. Conversely, dietary or pharmacological compounds may affect the microbiota before entering the circulation. Characterization of these interactions is an important step towards understanding the effects of the gut microbiota on health. In this cross-sectional study, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for a detailed characterization of the gut microbiota and plasma metabolome, respectively, of 8583 participants invited at age 50 to 64 from the population-based Swedish CArdioPulmonary bioImage Study. Here, we find that the gut microbiota explain up to 46% of the variance of individual plasma metabolites and we present 997 associations between alpha diversity and plasma metabolites and 546,819 associations between specific gut metagenomic species and plasma metabolites in an online atlas ( https://gutsyatlas.serve.scilifelab.se/ ). We exemplify the potential of this resource by presenting novel associations between dietary factors and oral medication with the gut microbiome, and microbial species strongly associated with the uremic toxin p-cresol sulfate. This resource can be used as the basis for targeted studies of perturbation of specific metabolites and for identification of candidate plasma biomarkers of gut microbiota composition.

Suggested Citation

  • Koen F. Dekkers & Sergi Sayols-Baixeras & Gabriel Baldanzi & Christoph Nowak & Ulf Hammar & Diem Nguyen & Georgios Varotsis & Louise Brunkwall & Nynne Nielsen & Aron C. Eklund & Jacob Bak Holm & H. Bj, 2022. "An online atlas of human plasma metabolite signatures of gut microbiome composition," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33050-0
    DOI: 10.1038/s41467-022-33050-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-33050-0
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-33050-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Helle Krogh Pedersen & Valborg Gudmundsdottir & Henrik Bjørn Nielsen & Tuulia Hyotylainen & Trine Nielsen & Benjamin A. H. Jensen & Kristoffer Forslund & Falk Hildebrand & Edi Prifti & Gwen Falony & E, 2016. "Human gut microbes impact host serum metabolome and insulin sensitivity," Nature, Nature, vol. 535(7612), pages 376-381, July.
    2. Dina Vojinovic & Djawad Radjabzadeh & Alexander Kurilshikov & Najaf Amin & Cisca Wijmenga & Lude Franke & M. Arfan Ikram & Andre G. Uitterlinden & Alexandra Zhernakova & Jingyuan Fu & Robert Kraaij & , 2019. "Relationship between gut microbiota and circulating metabolites in population-based cohorts," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    3. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    4. Arnau Vich Vila & Valerie Collij & Serena Sanna & Trishla Sinha & Floris Imhann & Arno R. Bourgonje & Zlatan Mujagic & Daisy M. A. E. Jonkers & Ad A. M. Masclee & Jingyuan Fu & Alexander Kurilshikov &, 2020. "Impact of commonly used drugs on the composition and metabolic function of the gut microbiota," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    5. Kristoffer Forslund & Falk Hildebrand & Trine Nielsen & Gwen Falony & Emmanuelle Le Chatelier & Shinichi Sunagawa & Edi Prifti & Sara Vieira-Silva & Valborg Gudmundsdottir & Helle Krogh Pedersen & Man, 2015. "Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota," Nature, Nature, vol. 528(7581), pages 262-266, December.
    6. 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.
    7. Alessia Visconti & Caroline I. Le Roy & Fabio Rosa & Niccolò Rossi & Tiphaine C. Martin & Robert P. Mohney & Weizhong Li & Emanuele Rinaldis & Jordana T. Bell & J. Craig Venter & Karen E. Nelson & Tim, 2019. "Interplay between the human gut microbiome and host metabolism," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kirsty Brown & Carolyn A. Thomson & Soren Wacker & Marija Drikic & Ryan Groves & Vina Fan & Ian A. Lewis & Kathy D. McCoy, 2023. "Microbiota alters the metabolome in an age- and sex- dependent manner in mice," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Kui Deng & Jin-jian Xu & Luqi Shen & Hui Zhao & Wanglong Gou & Fengzhe Xu & Yuanqing Fu & Zengliang Jiang & Menglei Shuai & Bang-yan Li & Wei Hu & Ju-Sheng Zheng & Yu-ming Chen, 2023. "Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Louise Grahnemo & Maria Nethander & Eivind Coward & Maiken Elvestad Gabrielsen & Satya Sree & Jean-Marc Billod & Klara Sjögren & Lars Engstrand & Koen F. Dekkers & Tove Fall & Arnulf Langhammer & Kris, 2023. "Identification of three bacterial species associated with increased appendicular lean mass: the HUNT study," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yadid M. Algavi & Elhanan Borenstein, 2023. "A data-driven approach for predicting the impact of drugs on the human microbiome," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    2. Efrat Muller & Itamar Shiryan & Elhanan Borenstein, 2024. "Multi-omic integration of microbiome data for identifying disease-associated modules," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Kui Deng & Jin-jian Xu & Luqi Shen & Hui Zhao & Wanglong Gou & Fengzhe Xu & Yuanqing Fu & Zengliang Jiang & Menglei Shuai & Bang-yan Li & Wei Hu & Ju-Sheng Zheng & Yu-ming Chen, 2023. "Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Feng Tong & Teng Wang & Na L. Gao & Ziying Liu & Kuiqing Cui & Yiqian Duan & Sicheng Wu & Yuhong Luo & Zhipeng Li & Chengjian Yang & Yixue Xu & Bo Lin & Liguo Yang & Alfredo Pauciullo & Deshun Shi & G, 2022. "The microbiome of the buffalo digestive tract," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    5. Fiona B. Tamburini & Dylan Maghini & Ovokeraye H. Oduaran & Ryan Brewster & Michaella R. Hulley & Venesa Sahibdeen & Shane A. Norris & Stephen Tollman & Kathleen Kahn & Ryan G. Wagner & Alisha N. Wade, 2022. "Short- and long-read metagenomics of urban and rural South African gut microbiomes reveal a transitional composition and undescribed taxa," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    6. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
    7. Ernesto Carrella & Richard M. Bailey & Jens Koed Madsen, 2018. "Indirect inference through prediction," Papers 1807.01579, arXiv.org.
    8. Rui Wang & Naihua Xiu & Kim-Chuan Toh, 2021. "Subspace quadratic regularization method for group sparse multinomial logistic regression," Computational Optimization and Applications, Springer, vol. 79(3), pages 531-559, July.
    9. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
    10. Masakazu Higuchi & Mitsuteru Nakamura & Shuji Shinohara & Yasuhiro Omiya & Takeshi Takano & Daisuke Mizuguchi & Noriaki Sonota & Hiroyuki Toda & Taku Saito & Mirai So & Eiji Takayama & Hiroo Terashi &, 2022. "Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach," IJERPH, MDPI, vol. 19(18), pages 1-13, September.
    11. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    12. Vincent, Martin & Hansen, Niels Richard, 2014. "Sparse group lasso and high dimensional multinomial classification," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 771-786.
    13. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    14. Perrot-Dockès Marie & Lévy-Leduc Céline & Chiquet Julien & Sansonnet Laure & Brégère Margaux & Étienne Marie-Pierre & Robin Stéphane & Genta-Jouve Grégory, 2018. "A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 17(5), pages 1-14, October.
    15. Fan, Jianqing & Jiang, Bai & Sun, Qiang, 2022. "Bayesian factor-adjusted sparse regression," Journal of Econometrics, Elsevier, vol. 230(1), pages 3-19.
    16. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    17. Jun Li & Serguei Netessine & Sergei Koulayev, 2018. "Price to Compete … with Many: How to Identify Price Competition in High-Dimensional Space," Management Science, INFORMS, vol. 64(9), pages 4118-4136, September.
    18. Sung Jae Jun & Sokbae Lee, 2024. "Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 998-1009, July.
    19. Rina Friedberg & Julie Tibshirani & Susan Athey & Stefan Wager, 2018. "Local Linear Forests," Papers 1807.11408, arXiv.org, revised Sep 2020.
    20. Xiangwei Li & Thomas Delerue & Ben Schöttker & Bernd Holleczek & Eva Grill & Annette Peters & Melanie Waldenberger & Barbara Thorand & Hermann Brenner, 2022. "Derivation and validation of an epigenetic frailty risk score in population-based cohorts of older adults," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33050-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.