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Genome-wide association study in 8,956 German individuals identifies influence of ABO histo-blood groups on gut microbiome

Nature Genetics volume 53, pages 147–155 (2021)Cite this article

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Abstract

The intestinal microbiome is implicated as an important modulating factor in multiple inflammatory1,2, neurologic3 and neoplastic diseases4. Recent genome-wide association studies yielded inconsistent, underpowered and rarely replicated results such that the role of human host genetics as a contributing factor to microbiome assembly and structure remains uncertain5,6,7,8,9,10,11. Nevertheless, twin studies clearly suggest host genetics as a driver of microbiome composition11. In a genome-wide association analysis of 8,956 German individuals, we identified 38 genetic loci to be associated with single bacteria and overall microbiome composition. Further analyses confirm the identified associations of ABO histo-blood groups and FUT2 secretor status with Bacteroides and Faecalibacterium spp. Mendelian randomization analysis suggests causative and protective effects of gut microbes, with clade-specific effects on inflammatory bowel disease. This holistic investigative approach of the host, its genetics and its associated microbial communities as a ‘metaorganism’ broaden our understanding of disease etiology, and emphasize the potential for implementing microbiota in disease treatment and management.

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Fig. 1: Summary of cohort properties.
Fig. 2: Results from the GWAS.
Fig. 3: ABO histo-blood groups show connection to gut microbial features.

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Data availability

Cohort-level summaries of microbial feature abundances are available in Supplementary Table 1. Complete summary statistics of all tested microbial features are available via the NHGRI-EBI GWAS catalog (https://www.ebi.ac.uk/gwas), GCP ID: GCP000068; study accession nos. GCST90011301–GCST90011730. The German mGWAS browser application is available for local query of results from Dockerhub: https://hub.docker.com/r/mruehlemann/german_mgwas_browser_app. Due to the informed consent obtained from the participants, phenotypes, as well as genotyping and not all 16S rRNA gene-sequencing data, can be deposited publicly; however, all data are available upon request from the respective biobanks (see Supplementary Note for details). PopGen and Focus: 16S rRNA-sequencing data are available at the National Center for Biotechnology Information Sequence Read Archive, accession no. PRJNA673102; http://www.uksh.de/p2n/Information+for+Researchers.html. KORA FF4: https://epi.helmholtz-muenchen.de. SHIP and SHIP-TREND: https://www.fvcm.med.uni-greifswald.de/dd_service/data_use_intro.php (German website; English-speaking assistance for the application process can be requested via: transfer@uni-greifswald.de).

Code availability

Microbiome data pre-processing, GWAS analysis and post-processing code are available via github: https://github.com/mruehlemann/german_mgwas_code.

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Acknowledgements

We thank T. Hauptmann, I. Urbach and I. Wulf of the IKMB Microbiome Lab for excellent technical assistance. We thank K. Wade for her valuable input on the MR analysis and M. Schulzky for support in figure design. This work was supported by the Deutsche Forschungsgemeinschaft (DFG) Collaborative Research Center 1182 ‘Origin and Function of Metaorganisms’ (grant no. SFB1182, Project A2 to A.F.) and the DFG Cluster of Excellence 2167 ‘Precision Medicine in Chronic Inflammation (PMI)’ (grant no. EXC2167 to A.F.). The SHIP part of the study was supported by the PePPP-project (ESF/14-BM-A55_0045/16 to M.M.L.) and the RESPONSE-project (BMBF grant no. 03ZZ0921E to M.M.L.). The SHIP is part of the Research Network Community Medicine of the University Medicine Greifswald, which is supported by the German Federal State of Mecklenburg-West Pomerania.

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Authors and Affiliations

  1. Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany

    Malte Christoph Rühlemann, Corinna Bang, Lucas Moitinho-Silva, Louise Bruun Thingholm, Frauke Degenhardt, Michael Wittig, Jan Kässens & Andre Franke

  2. Evolutionary Genomics, Max Planck Institute for Evolutionary Biology, Plön, Germany

    Britt Marie Hermes, Shauni Doms & John F. Baines

  3. Institute of Experimental Medicine, Kiel University, Kiel, Germany

    Britt Marie Hermes, Shauni Doms & John F. Baines

  4. Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany

    Britt Marie Hermes

  5. Department of Dermatology, Kiel University, Kiel, Germany

    Lucas Moitinho-Silva

  6. Department of Medicine A, University Medicine Greifswald, Greifswald, Germany

    Fabian Frost, Frank Ulrich Weiss, Stefan Weiss & Markus M. Lerch

  7. Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany

    Annette Peters & Harald Grallert

  8. German Center for Diabetes Research, Neuherberg, Germany

    Annette Peters

  9. ZIEL—Institute for Food & Health, Technical University of Munich, Freising, Germany

    Klaus Neuhaus & Dirk Haller

  10. Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany

    Uwe Völker, Henry Völzke, Georg Homuth & Stefan Weiss

  11. Department of Internal Medicine 1, Kiel University, Kiel, Germany

    Matthias Laudes

  12. Institute of Epidemiology, Kiel University, Kiel, Germany

    Wolfgang Lieb

  13. Chair of Nutrition and Immunology, Technical University of Munich, Freising, Germany

    Dirk Haller

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  1. Malte Christoph Rühlemann
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Contributions

M.C.R. performed microbiome sample preparation, data generation and curation, implemented ABO blood group inference, implemented statistical models, performed the (meta-)analysis, curated and interpreted results, and wrote the manuscript draft. B.M.H. curated and interpreted results and wrote the manuscript draft. C.B. performed microbiome sample preparation, data generation, curated and interpreted results, and advised in the writing of the draft manuscript. S.D. implemented statistical models, performed the (meta-)analysis and wrote the manuscript draft. L.M.-S. and L.B.T. curated and interpreted results. F.F. and F.D. performed data QC and curation. M.W. implemented ABO blood group inference. J.K. implemented statistical models and performed the (meta-)analysis. F.U.W. performed microbiome sample preparation, data generation and curation. A.P., U.V., S.W. H.G., M.L. and W.L. performed genotype and phenotype data generation and collection. K.H. performed microbiome sample preparation, data generation and curation. H.V. performed genotype and phenotype data generation and collection and data QC and curation. G.H. performed genotype and phenotype data collection. D.H. and M.M.L. designed the experiment. J.F.B. and A.F. designed the experiment and advised on the writing of the draft manuscript. All authors reviewed, edited and approved the final manuscript.

Corresponding author

Correspondence to Andre Franke.

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Peer review information Nature Genetics thanks Tao Zhang, Jonathan Braun and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary information

Supplementary Notes 1–6 and Supplementary Figs. 1–3.

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Supplementary Tables 1–8.

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Rühlemann, M.C., Hermes, B.M., Bang, C. et al. Genome-wide association study in 8,956 German individuals identifies influence of ABO histo-blood groups on gut microbiome. Nat Genet 53, 147–155 (2021). https://doi.org/10.1038/s41588-020-00747-1

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