Abstract

The gut microbiome is affected by multiple factors, including genetics. In this study, we assessed the influence of host genetics on microbial species, pathways and gene ontology categories, on the basis of metagenomic sequencing in 1,514 subjects. In a genome-wide analysis, we identified associations of 9 loci with microbial taxonomies and 33 loci with microbial pathways and gene ontology terms at P < 5 × 10−8. Additionally, in a targeted analysis of regions involved in complex diseases, innate and adaptive immunity, or food preferences, 32 loci were identified at the suggestive level of P < 5 × 10−6. Most of our reported associations are new, including genome-wide significance for the C-type lectin molecules CLEC4FCD207 at 2p13.3 and CLEC4AFAM90A1 at 12p13. We also identified association of a functional LCT SNP with the Bifidobacterium genus (P = 3.45 × 10−8) and provide evidence of a gene–diet interaction in the regulation of Bifidobacterium abundance. Our results demonstrate the importance of understanding host–microbe interactions to gain better insight into human health.

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Acknowledgements

We thank the participants and the staff of LifeLines-DEEP, 500FG and MIBS for their collaboration. We thank J. Dekens, M. Platteel, J. Pietersma and A. Maatman for management and technical support, and K. McIntyre and J. Senior for editing the manuscript.

This project was funded by grants from Top Institute Food and Nutrition, Wageningen, to C.W. (TiFN GH001), the Netherlands Organization for Scientific Research to J.F. (NWO-VIDI 864.13.013), L.F. (ZonMW-VIDI 917.14.374) and R.K.W. (ZonMW-VIDI 016.136.308), and CardioVasculair Onderzoek Nederland to M.H.H., M.G.N., A.Z. and J.F. (CVON 2012-03). A.Z. holds a Rosalind Franklin Fellowship (University of Groningen). This research received funding from the European Research Council under the European Union's Seventh Framework Programme: C.W. is supported by FP7/2007-2013/ERC Advanced Grant (agreement 2012-322698) and a Spinoza Prize from the Netherlands Organization for Scientific Research. M.G.N. holds an ERC Consolidator Grant (310372). L.F. has an FP7/2007-2013 grant (agreement 259867) and an ERC Starting Grant (637640, ImmRisk). Y.L. holds a Netherlands Organization for Scientific Research VENI grant (863.13.011).

Author information

Author notes

    • Maria Carmen Cenit

    Present address: Department of Pediatrics, Dr. Peset University Hospital, Valencia, Spain.

    • Marc Jan Bonder
    •  & Alexander Kurilshikov

    These authors contributed equally to this work.

    • Jingyuan Fu
    •  & Alexandra Zhernakova

    These authors jointly directed this work.

Affiliations

  1. University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands.

    • Marc Jan Bonder
    • , Alexander Kurilshikov
    • , Ettje F Tigchelaar
    • , Patrick Deelen
    • , Daria V Zhernakova
    • , Soesma A Jankipersadsing
    • , Maria Carmen Cenit
    • , Morris A Swertz
    • , Yang Li
    • , Vinod Kumar
    • , Lude Franke
    • , Cisca Wijmenga
    • , Jingyuan Fu
    •  & Alexandra Zhernakova
  2. Institute of Chemical Biology and Fundamental Medicine SB RAS, Novosibirsk, Russia.

    • Alexander Kurilshikov
  3. Department of Natural Sciences, Novosibirsk State University, Novosibirsk, Russia.

    • Alexander Kurilshikov
  4. Top Institute Food and Nutrition, Wageningen, the Netherlands.

    • Ettje F Tigchelaar
    • , Zlatan Mujagic
    •  & Alexandra Zhernakova
  5. Division of Gastroenterology-Hepatology, Department of Internal Medicine, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, the Netherlands.

    • Zlatan Mujagic
    • , Ad A M Masclee
    •  & Daisy Jonkers
  6. University of Groningen, University Medical Center Groningen, Department of Gastroenterology and Hepatology, Groningen, the Netherlands.

    • Floris Imhann
    • , Arnau Vich Vila
    •  & Rinse K Weersma
  7. University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands.

    • Patrick Deelen
    •  & Morris A Swertz
  8. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Tommi Vatanen
    • , Melanie Schirmer
    •  & Ramnik J Xavier
  9. Department of Computer Science, Aalto University School of Science, Espoo, Finland.

    • Tommi Vatanen
  10. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

    • Melanie Schirmer
  11. Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.

    • Sanne P Smeekens
    • , Martin Jaeger
    • , Marije Oosting
    • , Leo Joosten
    •  & Mihai G Netea
  12. Radboud Center of Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.

    • Sanne P Smeekens
    • , Martin Jaeger
    • , Marije Oosting
    • , Leo Joosten
    •  & Mihai G Netea
  13. University of Groningen, University Medical Center Groningen, Department of Pediatrics, Groningen, the Netherlands.

    • Soesma A Jankipersadsing
    • , Marten H Hofker
    •  & Jingyuan Fu
  14. University of Groningen, University Medical Center Groningen, Department of Medical Microbiology, Groningen, the Netherlands.

    • Hermie Harmsen
  15. Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Ramnik J Xavier
  16. Gastrointestinal Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Ramnik J Xavier
  17. Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Ramnik J Xavier

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Contributions

Conceptualization: A.Z., J.F., C.W. and M.J.B. Methodology: M.J.B., A.K., L.F., J.F., P.D., T.V. and M.S. Software: M.J.B., A.K., L.F., J.F., P.D., M.A.S. and D.V.Z. Formal analysis: M.J.B., A.K., J.F. and A.Z. Investigation: A.Z., J.F., M.J.B., A.K., F.I., D.V.Z., S.A.J., A.V.V., E.F.T., H.H. and M.C.C. Resources: C.W., A.Z., L.F., J.F., M.A.S., M.G.N., R.J.X., L.J. and A.A.M.M. Data curation: M.J.B., A.K., J.F., P.D., L.F., S.A.J. and Y.L. Writing–original draft: A.Z., J.F., M.J.B., A.K. and C.W. Writing–review and editing: M.J.B., A.K., E.F.T., Z.M., F.I., A.V.V., P.D., T.V., M.S., S.P.S., D.V.Z., S.A.J., M.J., M.O., M.A.S., M.C.C., Y.L., V.K., H.H., R.K.W., L.F., M.H.H., D.J., M.G.N., C.W., J.F. and A.Z. Visualization: A.K., M.J.B., A.Z. and J.F. Supervision: A.Z., J.F., C.W., L.F., R.K.W. and M.H.H. Project administration: A.Z., J.F., C.W., L.F., M.G.N., D.J., A.A.M.M. and S.P.S. Funding acquisition: A.Z., J.F., C.W., L.F., M.G.N., D.J. and A.A.M.M.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Cisca Wijmenga or Jingyuan Fu or Alexandra Zhernakova.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–5.

Excel files

  1. 1.

    Supplementary Table 1

    Abundance levels of microbes, MetaCyc pathways and GO2000 terms.

  2. 2.

    Supplementary Table 2

    Summary of the tested number of associations per analysis branch.

  3. 3.

    Supplementary Table 3

    Genome-wide microbial QTL results.

  4. 4.

    Supplementary Table 4

    Estimations for the FDRs presented in the paper.

  5. 5.

    Supplementary Table 5

    Correlations between microbial abundance and MetaCyc abundance levels.

  6. 6.

    Supplementary Table 6

    Correlations between microbial abundance and GO2000 abundance levels.

  7. 7.

    Supplementary Table 7

    SNP selection list GWAS-associated SNPs.

  8. 8.

    Supplementary Table 8

    SNP selection list for innate immunity and food preference, including references.

  9. 9.

    Supplementary Table 9

    Microbial QTLs on abundance and functional levels for SNPs previously related to GWAS.

  10. 10.

    Supplementary Table 10

    Microbial QTLs on abundance and functional levels for the variants in the HLA.

  11. 11.

    Supplementary Table 11

    Microbial QTLs on abundance and functional levels for SNPs related to innate immunity.

  12. 12.

    Supplementary Table 12

    Microbial QTLs on abundance and functional levels for SNPs related to food preference.

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DOI

https://doi.org/10.1038/ng.3663

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