Combinatorial, additive and dose-dependent drug–microbiome associations

Research output: Contribution to journalJournal articleResearchpeer-review

  • Sofia K. Forslund
  • Rima Chakaroun
  • Maria Zimmermann-Kogadeeva
  • Lajos Markó
  • Judith Aron-Wisnewsky
  • Trine Nielsen
  • Lucas Moitinho-Silva
  • Thomas S.B. Schmidt
  • Gwen Falony
  • Sara Vieira-Silva
  • Solia Adriouch
  • Renato J. Alves
  • Karen Assmann
  • Jean Philippe Bastard
  • Till Birkner
  • Robert Caesar
  • Julien Chilloux
  • Luis Pedro Coelho
  • Leopold Fezeu
  • Nathalie Galleron
  • Gerard Helft
  • Richard Isnard
  • Boyang Ji
  • Michael Kuhn
  • Emmanuelle Le Chatelier
  • Antonis Myridakis
  • Lisa Olsson
  • Nicolas Pons
  • Edi Prifti
  • Benoit Quinquis
  • Hugo Roume
  • Christian Lewinter
  • Nadja B. Søndertoft
  • Helle Krogh Pedersen
  • Tue H. Hansen
  • Hartmann, Bolette
  • Holst, Jens Juul
  • Malene Hornbak
  • Jørgensen, Niklas Rye
  • Justesen, Johanne Marie
  • Nikolaj Krarup
  • Mathilde Svendstrup
  • The MetaCardis Consortium*

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1–5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug–host–microbiome interactions in cardiometabolic disease.

Original languageEnglish
Pages (from-to)500-517
Number of pages18
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.

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