4.8 Article

Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative

Journal

MICROBIOME
Volume 6, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s40168-018-0479-3

Keywords

Gut microbiome; Genome-wide association studies (GWAS); Meta-analysis

Categories

Funding

  1. COPSAC, Copenhagen Prospective Studes on Asthma in Childhood, Herlev and Gentofte, Hospital, University of Copenhagen, Copenhagen, Denmark
  2. Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
  3. Department of Molecular Cell Biology, Weizmann Institute, of Science Rehovot, Israel
  4. Division of Gastroenterology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
  5. Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
  6. Department of Biostatistics and Center for Statistical Genetics, University of Michigan, MI, USA
  7. University of Groningen, University Medical Center Groningen, Department Genetics, Groningen, The Netherlands
  8. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
  9. Department of Biological Psychology, Amsterdam Public Heath Research Institute, VU Amsterdam, Amsterdam, The Netherlands
  10. Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Toronto, Ontario, Canada
  11. Avera Institute for Human Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD, USA
  12. Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
  13. Unit of Clinical Epidemiology, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
  14. Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
  15. Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
  16. Health Science Center at Houston, University of Texas, Houston, TN, USA
  17. Department of Medicine A, University Medicine Greifswald, Greifswald, Germany
  18. Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Germany
  19. MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
  20. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
  21. Department of Internal Medicine, Diabetes Centre, VU University Medical Centre, Amsterdam, The Netherlands
  22. Division of Gastroenterology-Hepatology, Department of Internal Medicine, NUTRIM School of Nutrition and Translational Research in, Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
  23. Department of Biochemistry, School of Medicine, Ewha Womans University, Seoul, South Korea
  24. Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
  25. Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio, University Hospital, Kuopio, Finland
  26. Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
  27. Institute of Genomics, University of Tartu, Estonia
  28. Department of Medicine, Department of Human Genetics, Molecular Biology Institute, Department of Microbiology, Immunology and Molecular Genetics, University of California, CA, USA
  29. Department of Medicine 2, University Hospital, Ludwig-Maximilians-University, Munich, Germany
  30. The Generation R Study Group, Erasmus MC, 3000 CA Rotterdam, The Netherlands
  31. Department of Epidemiology, Erasmus MC, 3000 CA Rotterdam, The Netherlands
  32. Department of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
  33. Department of Genetics, University of North Carolina at Chapel Hill, NC, USA
  34. Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
  35. Genetics and Genome Biology, The Hospital for Sick Children Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
  36. Departments of Neurology and Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
  37. Department of Microbiology and Immunology, Rega Institute. KU Leuven - University of Leuven, Leuven, Belgium
  38. VIB Center for Microbiology, Leuven, Belgium
  39. Department of Psychiatry, Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
  40. Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
  41. Institute for Community Medicine, Greifswald University Hospital, Greifswald, Germany
  42. K.G. Jebsen Coeliac Disease Re. search Centre, Department of Immunology, University of Oslo, Norway
  43. Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
  44. MRC [MR/N01183X/1, MR/N030125/1, MC_UU_12013/3] Funding Source: UKRI

Ask authors/readers for more resources

Background: In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Results: Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. Conclusion: We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available