Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota

Nature Genetics volume 48, pages 1396–1406 (2016)Cite this article

Subjects

Abstract

Human gut microbiota is an important determinant for health and disease, and recent studies emphasize the numerous factors shaping its diversity. Here we performed a genome-wide association study (GWAS) of the gut microbiota using two cohorts from northern Germany totaling 1,812 individuals. Comprehensively controlling for diet and non-genetic parameters, we identify genome-wide significant associations for overall microbial variation and individual taxa at multiple genetic loci, including the VDR gene (encoding vitamin D receptor). We observe significant shifts in the microbiota of Vdr−/− mice relative to control mice and correlations between the microbiota and serum measurements of selected bile and fatty acids in humans, including known ligands and downstream metabolites of VDR. Genome-wide significant (P < 5 × 10−8) associations at multiple additional loci identify other important points of host–microbe intersection, notably several disease susceptibility genes and sterol metabolism pathway components. Non-genetic and genetic factors each account for approximately 10% of the variation in gut microbiota, whereby individual effects are relatively small.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Overview of variation in the gut microbiota and significantly associated non-genetic parameters.
Figure 2: Individual and combined effects of significant loci and overview of all significant loci identified in this study.
Figure 3: VDR and POMC as examples of genes associated with β diversity.

References

  1. Ley, R.E., Peterson, D.A. & Gordon, J.I. Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell 124, 837–848 (2006).

    Article  CAS  PubMed  Google Scholar 

  2. Fraune, S. & Bosch, T.C. Why bacteria matter in animal development and evolution. BioEssays 32, 571–580 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Sekirov, I., Russell, S.L., Antunes, L.C.B.B. & Finlay, B.B. Gut microbiota in health and disease. Physiol. Rev. 90, 859–904 (2010).

    Article  CAS  PubMed  Google Scholar 

  4. Chow, J. & Mazmanian, S.K. A pathobiont of the microbiota balances host colonization and intestinal inflammation. Cell Host Microbe 7, 265–276 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Costello, E.K., Stagaman, K., Dethlefsen, L., Bohannan, B.J. & Relman, D.A. The application of ecological theory toward an understanding of the human microbiome. Science 336, 1255–1262 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Walter, J. & Ley, R. The human gut microbiome: ecology and recent evolutionary changes. Annu. Rev. Microbiol. 65, 411–429 (2011).

    Article  CAS  PubMed  Google Scholar 

  7. Antonopoulos, D.A. et al. Reproducible community dynamics of the gastrointestinal microbiota following antibiotic perturbation. Infect. Immun. 77, 2367–2375 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Caporaso, J.G. et al. Moving pictures of the human microbiome. Genome Biol. 12, R50 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Eckburg, P.B. et al. Diversity of the human intestinal microbial flora. Science 308, 1635–1638 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Goodrich, J.K. et al. Human genetics shape the gut microbiome. Cell 159, 789–799 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cotillard, A. et al. Dietary intervention impact on gut microbial gene richness. Nature 500, 585–588 (2013).

    Article  CAS  PubMed  Google Scholar 

  14. David, L.A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).

    Article  CAS  PubMed  Google Scholar 

  15. Rehman, A. et al. Geographical patterns of the standing and active human gut microbiome in health and IBD. Gut 65, 238–248 (2016).

    Article  PubMed  Google Scholar 

  16. Maurice, C.F., Haiser, H.J. & Turnbaugh, P.J. Xenobiotics shape the physiology and gene expression of the active human gut microbiome. Cell 152, 39–50 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Rausch, P. et al. Colonic mucosa-associated microbiota is influenced by an interaction of Crohn disease and FUT2 (Secretor) genotype. Proc. Natl. Acad. Sci. USA 108, 19030–19035 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Rehman, A. et al. Nod2 is essential for temporal development of intestinal microbial communities. Gut 60, 1354–1362 (2011).

    Article  CAS  PubMed  Google Scholar 

  19. Blekhman, R. et al. Host genetic variation impacts microbiome composition across human body sites. Genome Biol. 16, 191 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Krawczak, M. et al. PopGen: population-based recruitment of patients and controls for the analysis of complex genotype–phenotype relationships. Community Genet. 9, 55–61 (2006).

    PubMed  Google Scholar 

  21. Müller, N. et al. IL-6 blockade by monoclonal antibodies inhibits apolipoprotein (a) expression and lipoprotein (a) synthesis in humans. J. Lipid Res. 56, 1034–1042 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Biedermann, L. et al. Smoking cessation induces profound changes in the composition of the intestinal microbiota in humans. PLoS One 8, e59260 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Haussler, M.R. et al. Vitamin D receptor: molecular signaling and actions of nutritional ligands in disease prevention. Nutr. Rev. 66 (Suppl. 2), S98–S112 (2008).

    Article  PubMed  Google Scholar 

  24. Makishima, M. et al. Vitamin D receptor as an intestinal bile acid sensor. Science 296, 1313–1316 (2002).

    Article  CAS  PubMed  Google Scholar 

  25. Jin, D. et al. Lack of vitamin D receptor causes dysbiosis and changes the functions of the murine intestinal microbiome. Clin. Ther. 37, 996–1009 e7 (2015).

    Article  CAS  PubMed  Google Scholar 

  26. D'Aldebert, E. et al. Bile salts control the antimicrobial peptide cathelicidin through nuclear receptors in the human biliary epithelium. Gastroenterology 136, 1435–1443 (2009).

    Article  CAS  PubMed  Google Scholar 

  27. Sayin, S.I. et al. Gut microbiota regulates bile acid metabolism by reducing the levels of tauro-β-muricholic acid, a naturally occurring FXR antagonist. Cell Metab. 17, 225–235 (2013).

    Article  CAS  PubMed  Google Scholar 

  28. Inoue, Y., Yu, A.M., Inoue, J. & Gonzalez, F.J. Hepatocyte nuclear factor 4α is a central regulator of bile acid conjugation. J. Biol. Chem. 279, 2480–2489 (2004).

    Article  CAS  PubMed  Google Scholar 

  29. Sato, H. et al. Group III secreted phospholipase A2 transgenic mice spontaneously develop inflammation. Biochem. J. 421, 17–27 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. Yano, J.M. et al. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161, 264–276 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Olivares, M. et al. The HLA-DQ2 genotype selects for early intestinal microbiota composition in infants at high risk of developing coeliac disease. Gut 64, 406–417 (2015).

    Article  CAS  PubMed  Google Scholar 

  32. Okada, Y. et al. HLA-Cw*1202–B*5201–DRB1*1502 haplotype increases risk for ulcerative colitis but reduces risk for Crohn's disease. Gastroenterology 141, 864–871 e1, 5 (2011).

    Article  CAS  PubMed  Google Scholar 

  33. Arimura, Y. et al. Characteristics of Japanese inflammatory bowel disease susceptibility loci. J. Gastroenterol. 49, 1217–1230 (2014).

    Article  PubMed  Google Scholar 

  34. Terao, C. et al. Two susceptibility loci to Takayasu arteritis reveal a synergistic role of the IL12B and HLA-B regions in a Japanese population. Am. J. Hum. Genet. 93, 289–297 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Benson, A.K. et al. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc. Natl. Acad. Sci. USA 107, 18933–18938 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pers, T.H. et al. Biological interpretation of genome-wide association studies using predicted gene functions. Nat. Commun. 6, 5890 (2015).

    Article  CAS  PubMed  Google Scholar 

  37. Phay, J.E., Hussain, H.B. & Moley, J.F. Cloning and expression analysis of a novel member of the facilitative glucose transporter family, SLC2A9 (GLUT9). Genomics 66, 217–220 (2000).

    Article  CAS  PubMed  Google Scholar 

  38. Kliewer, S.A., Umesono, K., Noonan, D.J., Heyman, R.A. & Evans, R.M. Convergence of 9-cis retinoic acid and peroxisome proliferator signalling pathways through heterodimer formation of their receptors. Nature 358, 771–774 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Repa, J.J. et al. Regulation of absorption and ABC1-mediated efflux of cholesterol by RXR heterodimers. Science 289, 1524–1529 (2000).

    Article  CAS  PubMed  Google Scholar 

  40. Wahlström, A., Sayin, S.I., Marschall, H.U. & Bäckhed, F. Intestinal crosstalk between bile acids and microbiota and its impact on host metabolism. Cell Metab. 24, 41–50 (2016).

    Article  PubMed  CAS  Google Scholar 

  41. Duparc, T. et al. Hepatocyte MyD88 affects bile acids, gut microbiota and metabolome contributing to regulate glucose and lipid metabolism. Gut http://dx.doi.org/10.1136/gutjnl-2015-310904 (2016).

  42. Jostins, L. et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Liu, J.Z. et al. Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis. Nat. Genet. 45, 670–675 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Sun, J. VDR/vitamin D receptor regulates autophagic activity through ATG16L1. Autophagy 12, 1057–1058 (2016).

    Article  CAS  PubMed  Google Scholar 

  45. Krude, H., Biebermann, H. & Gruters, A. Mutations in the human proopiomelanocortin gene. Ann. NY Acad. Sci. 994, 233–239 (2003).

    Article  CAS  PubMed  Google Scholar 

  46. Tuoresmäki, P., Väisänen, S., Neme, A., Heikkinen, S. & Carlberg, C. Patterns of genome-wide VDR locations. PLoS One 9, e96105 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Wang, J. et al. Analysis of intestinal microbiota in hybrid house mice reveals evolutionary divergence in a vertebrate hologenome. Nat. Commun. 6, 6440 (2015).

    Article  CAS  PubMed  Google Scholar 

  48. Srinivas, G. et al. Genome-wide mapping of gene–microbiota interactions in susceptibility to autoimmune skin blistering. Nat. Commun. 4, 2462 (2013).

    Article  PubMed  CAS  Google Scholar 

  49. McKnite, A.M. et al. Murine gut microbiota is defined by host genetics and modulates variation of metabolic traits. PLoS One 7, e39191 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Leamy, L.J. et al. Host genetics and diet, but not immunoglobulin A expression, converge to shape compositional features of the gut microbiome in an advanced intercross population of mice. Genome Biol. 15, 552 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Kozich, J.J., Westcott, S.L., Baxter, N.T., Highlander, S.K. & Schloss, P.D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Magocˇ, T. & Salzberg, S.L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Edgar, R.C., Haas, B.J., Clemente, J.C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Wang, Q., Garrity, G.M., Tiedje, J.M. & Cole, J.R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Edgar, R.C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Abu-Hayyeh, S. et al. Prognostic and mechanistic potential of progesterone sulfates in intrahepatic cholestasis of pregnancy and pruritus gravidarum. Hepatology 63, 1287–1298 (2016).

    Article  CAS  PubMed  Google Scholar 

  57. Bjørndal, B. et al. Krill powder increases liver lipid catabolism and reduces glucose mobilization in tumor necrosis factor-α transgenic mice fed a high-fat diet. Metabolism 61, 1461–1472 (2012).

    Article  PubMed  CAS  Google Scholar 

  58. Nöthlings, U., Hoffmann, K., Bergmann, M.M. & Boeing, H. Fitting portion sizes in a self-administered food frequency questionnaire. J. Nutr. 137, 2781–2786 (2007).

    Article  PubMed  Google Scholar 

  59. Dehne, L.I., Klemm, C., Henseler, G. & Hermann-Kunz, E. The German food code and nutrient data base (BLS II.2). Eur. J. Epidemiol. 15, 355–359 (1999).

    Article  CAS  PubMed  Google Scholar 

  60. Xu, L., Paterson, A.D., Turpin, W. & Xu, W. Assessment and selection of competing models for zero-inflated microbiome data. PLoS One 10, e0129606 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Degenhardt, F. et al. Genome-wide association study of serum coenzyme Q10 levels identifies susceptibility loci linked to neuronal diseases. Hum. Mol. Genet. http://dx.doi.org/10.1093/hmg/ddw134 (2016).

  62. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ellinghaus, D. et al. Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci. Nat. Genet. 48, 510–518 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Wood, A.R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173–1186 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Bolger, A.M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Schmieder, R. & Edwards, R. Fast identification and removal of sequence contamination from genomic and metagenomic datasets. PLoS One 6, e17288 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank A.D. Paterson and colleagues for support in selection of models for GWAS. We further thank Der Norddeutsche Verbund für Hoch- und Höchstleistungsrechnen (HLRN) and S. Knief and H. Marten for computational resources and support. This work was supported by German Research Foundation (DFG) Collaborative Research Center 1182, 'Origin and Function of Metaorganisms' (J.F.B. and A.F.) and Excellence Cluster 306, 'Inflammation at Interfaces' (J.F.B. and A.F.) and by German Federal Ministry of Education and Research (BMBF) project 'SysINFLAME' (J.F.B. and A.F.). Project support was also provided by the Norwegian PSC Research Center and the Western Norway Regional Health Authority (grant 911802) (T.H.K.). M.K. is the recipient of a Postdoctoral Research Fellowship from the German Research Foundation (DFG). J.R.H. was funded by the Norwegian Research Council (240787/F20).

Author information

Author notes

  1. Jun Wang & Silke Szymczak

    Present address: Present addresses: Department of Microbiology and Immunology, KU Leuven and Center for the Biology of Disease, VIB, Leuven, Belgium (J.W.) and Institute of Medical Informatics and Statistics, Christian Albrechts University of Kiel, Kiel, Germany (S.S.).,

  2. Jun Wang, Louise B Thingholm and Jurgita Skiecevičienė: These authors contributed equally to this work.

  3. Tom H Karlsen, John F Baines and Andre Franke: These authors jointly directed this work.

Authors and Affiliations

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

    Jun Wang, Philipp Rausch, Sven Künzel & John F Baines

  2. Institute for Experimental Medicine, Christian Albrechts University of Kiel, Kiel, Germany

    Jun Wang, Philipp Rausch, Katja Cloppenborg-Schmidt & John F Baines

  3. Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany

    Louise B Thingholm, Jurgita Skiecevičienė, Frauke Degenhardt, Femke-Anouska Heinsen, Malte C Rühlemann, Silke Szymczak, Jörn Bethune, Felix Sommer, David Ellinghaus, Matthias Hübenthal, Wei-Hung Pan, Raheleh Sheibani-Tezerji, Robert Häsler, Philipp Rosenstiel & Andre Franke

  4. Division of Surgery, Norwegian PSC Research Center, Inflammatory Medicine and Transplantation, Oslo, Norway

    Martin Kummen, Johannes R Hov, Kristian Holm & Tom H Karlsen

  5. Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway

    Martin Kummen, Johannes R Hov, Kristian Holm & Tom H Karlsen

  6. K,

    Martin Kummen, Johannes R Hov, Kristian Holm & Tom H Karlsen

  7. .G. Jebsen Inflammation Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Martin Kummen, Johannes R Hov, Kristian Holm & Tom H Karlsen

  8. Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway

    Martin Kummen, Johannes R Hov, Kristian Holm & Tom H Karlsen

  9. Department of Transplantation Medicine, Section of Gastroenterology, Oslo University Hospital Rikshospitalet, Oslo, Norway

    Johannes R Hov & Tom H Karlsen

  10. Estonian Genome Center, University of Tartu, Tartu, Estonia

    Tönu Esko

  11. Division of Gastroenterology and Hepatology, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA

    Jun Sun

  12. Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, Germany

    Mihaela Pricop-Jeckstadt & Ute Nöthlings

  13. Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

    Samer Al-Dury & Hanns-Ulrich Marschall

  14. Department of Clinical Science, University of Bergen, Bergen, Norway

    Pavol Bohov & Rolf K Berge

  15. Department of Heart Disease, Haukeland University Hospital, Bergen, Norway

    Rolf K Berge

  16. Institute of Epidemiology, Christian Albrechts University of Kiel, Kiel, Germany

    Manja Koch & Wolfgang Lieb

  17. Institute of Human Nutrition and Food Science, University of Kiel, Kiel, Germany

    Karin Schwarz, Gerald Rimbach & Patricia Hübbe

  18. BioDonostia Health Research Institute, San Sebastian and Ikerbasque, Basque Foundation for Science, Bilbao, Spain

    Mauro D'Amato

  19. Department of Medicine Solna, Unit of Clinical Epidemiology, Karolinska Institutet, Stockholm, Sweden

    Mauro D'Amato

  20. Department of Internal Medicine I, University Hospital S.-H. (UKSH, Campus Kiel), Kiel, Germany

    Matthias Laudes

  21. Department of Clinical Medicine, University of Bergen, Bergen, Norway

    Tom H Karlsen

Authors
  1. Jun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Louise B Thingholm
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jurgita Skiecevičienė
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Philipp Rausch
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Martin Kummen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Johannes R Hov
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Frauke Degenhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Femke-Anouska Heinsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Malte C Rühlemann
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Silke Szymczak
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Kristian Holm
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Tönu Esko
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Jun Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Mihaela Pricop-Jeckstadt
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Samer Al-Dury
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Pavol Bohov
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Jörn Bethune
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Felix Sommer
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. David Ellinghaus
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Rolf K Berge
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Matthias Hübenthal
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Manja Koch
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Karin Schwarz
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Gerald Rimbach
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Patricia Hübbe
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Wei-Hung Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Raheleh Sheibani-Tezerji
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. Robert Häsler
    View author publications

    You can also search for this author in PubMed Google Scholar

  29. Philipp Rosenstiel
    View author publications

    You can also search for this author in PubMed Google Scholar

  30. Mauro D'Amato
    View author publications

    You can also search for this author in PubMed Google Scholar

  31. Katja Cloppenborg-Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  32. Sven Künzel
    View author publications

    You can also search for this author in PubMed Google Scholar

  33. Matthias Laudes
    View author publications

    You can also search for this author in PubMed Google Scholar

  34. Hanns-Ulrich Marschall
    View author publications

    You can also search for this author in PubMed Google Scholar

  35. Wolfgang Lieb
    View author publications

    You can also search for this author in PubMed Google Scholar

  36. Ute Nöthlings
    View author publications

    You can also search for this author in PubMed Google Scholar

  37. Tom H Karlsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  38. John F Baines
    View author publications

    You can also search for this author in PubMed Google Scholar

  39. Andre Franke
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.F., J.F.B. and T.H.K. conceived the project. U.N., W.L., M.L. and K.S. organized recruitment and sample collection for the PopGen and FoCus cohorts. Genotyping data were collected and processed by L.B.T., J. Skiecevicˇienė, J.R.H., F.D. and K.H.; nutritional data were generated and processed by S.S., M.P.-J., M. Koch and U.N.; microbiome data were generated and processed by J.W., P. Rausch, F.-A.H., M.C.R., P. Rosenstiel, K.C.-S., S.K. and J.F.B.; and bile acid and fatty acid data were generated and processed by S.A.-D., P.B., R.K.B., M.D'A. and H.-U.M. T.E., J. Sun, J.B., F.S., D.E., M.H., G.R., P.H., W.-H.P., R.S.-T., R.H. and P. Rosenstiel contributed to additional experiments and data for this study. Statistical analyses were performed by J.W., L.B.T., J. Skiecevicˇienė, P. Rausch and M. Kummen, and J.W., L.B.T., J. Skiecevicˇienė, P. Rausch, M. Kummen, J.R.H., M.D'A., H.-U.M., T.H.K., J.F.B. and A.F. interpreted the results. J.W., L.B.T., J. Skiecevicˇienė, P. Rausch, M. Kummen, J.R.H., T.H.K., J.F.B. and A.F. wrote the manuscript, with input from all other authors.

Corresponding author

Correspondence to Andre Franke.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–19 and Supplementary Note. (PDF 13872 kb)

Supplementary Tables 1–9

Supplementary Tables 1–9. (XLSX 97 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Thingholm, L., Skiecevičienė, J. et al. Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota. Nat Genet 48, 1396–1406 (2016). https://doi.org/10.1038/ng.3695

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3695

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing