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A metagenome-wide association study of gut microbiota in type 2 diabetes


Assessment and characterization of gut microbiota has become a major research area in human disease, including type 2 diabetes, the most prevalent endocrine disease worldwide. To carry out analysis on gut microbial content in patients with type 2 diabetes, we developed a protocol for a metagenome-wide association study (MGWAS) and undertook a two-stage MGWAS based on deep shotgun sequencing of the gut microbial DNA from 345 Chinese individuals. We identified and validated approximately 60,000 type-2-diabetes-associated markers and established the concept of a metagenomic linkage group, enabling taxonomic species-level analyses. MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance. An analysis of 23 additional individuals demonstrated that these gut microbial markers might be useful for classifying type 2 diabetes.

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Figure 1: Identification of T2D-associated markers from gut metagenome.
Figure 2: Taxonomic and functional characterization of gut microbiota in T2D.
Figure 3: Gut microbiota of T2D patients show a moderate degree of dysbiosis.
Figure 4: A trial classification of T2D using gut microbial gene markers.

Accession codes

Primary accessions

Sequence Read Archive

Data deposits

The raw Illumina read data of all 368 samples has been deposited in the NCBI Sequence Read Archive under accession numbers SRA045646 and SRA050230. The assembly data, updated metagenome gene catalogue, annotation information, and MGLs are published in the GigaScience database, GigaDB35.


  1. 1

    Wellen, K. E. & Hotamisligil, G. S. Inflammation, stress, and diabetes. J. Clin. Invest. 115, 1111–1119 (2005)

    CAS  Article  Google Scholar 

  2. 2

    Risérus, U., Willett, W. C. & Hu, F. B. Dietary fats and prevention of type 2 diabetes. Prog. Lipid Res. 48, 44–51 (2009)

    Article  Google Scholar 

  3. 3

    The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007)

  4. 4

    Scott, L. J. et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316, 1341–1345 (2007)

    ADS  CAS  Article  Google Scholar 

  5. 5

    Musso, G., Gambino, R. & Cassader, M. Interactions between gut microbiota and host metabolism predisposing to obesity and diabetes. Annu. Rev. Med. 62, 361–380 (2011)

    CAS  Article  Google Scholar 

  6. 6

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

    ADS  Article  Google Scholar 

  7. 7

    Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009)

    ADS  CAS  Article  Google Scholar 

  8. 8

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

    CAS  Article  Google Scholar 

  9. 9

    The Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012)

  10. 10

    The Human Microbiome Project Consortium. A framework for human microbiome research. Nature 486, 215–221 (2012)

  11. 11

    Vijay-Kumar, M. et al. Metabolic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5. Science 328, 228–231 (2010)

    ADS  CAS  Article  Google Scholar 

  12. 12

    Bäckhed, F. et al. The gut microbiota as an environmental factor that regulates fat storage. Proc. Natl Acad. Sci. USA 101, 15718–15723 (2004)

    ADS  Article  Google Scholar 

  13. 13

    Ley, R. E. et al. Obesity alters gut microbial ecology. Proc. Natl Acad. Sci. USA 102, 11070–11075 (2005)

    ADS  CAS  Article  Google Scholar 

  14. 14

    Zhang, H. et al. Human gut microbiota in obesity and after gastric bypass. Proc. Natl Acad. Sci. USA 106, 2365–2370 (2009)

    ADS  CAS  Article  Google Scholar 

  15. 15

    Bäckhed, F., Manchester, J. K., Semenkovich, C. F. & Gordon, J. I. Mechanisms underlying the resistance to diet-induced obesity in germ-free mice. Proc. Natl Acad. Sci. USA 104, 979–984 (2007)

    ADS  Article  Google Scholar 

  16. 16

    Turnbaugh, P. J. et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027–1031 (2006)

    ADS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Manichanh, C. et al. Reduced diversity of faecal microbiota in Crohn’s disease revealed by a metagenomic approach. Gut 55, 205–211 (2006)

    CAS  Article  Google Scholar 

  18. 18

    Joossens, M. et al. Dysbiosis of the faecal microbiota in patients with Crohn’s disease and their unaffected relatives. Gut 60, 631–637 (2011)

    Article  Google Scholar 

  19. 19

    Larsen, N. et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS ONE 5, e9085 (2010)

    ADS  Article  Google Scholar 

  20. 20

    Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011)

    CAS  Article  Google Scholar 

  21. 21

    Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nature Genet. 38, 904–909 (2006)

    CAS  Article  Google Scholar 

  22. 22

    Woo, P. C. Y. et al. Bacteremia due to Clostridium hathewayi in a patient with acute appendicitis. J. Clin. Microbiol. 42, 5947–5949 (2004)

    Article  Google Scholar 

  23. 23

    Elsayed, S. & Zhang, K. Bacteremia caused by Clostridium symbiosum. J. Clin. Microbiol. 42, 4390–4392 (2004)

    Article  Google Scholar 

  24. 24

    McClean, K. L., Sheehan, G. J. & Harding, G. K. Intraabdominal infection: a review. Clin. Inf. Dis. 19, 100–116 (1994)

    CAS  Article  Google Scholar 

  25. 25

    Brook, I. Clostridial infection in children. J. Med. Microbiol. 42, 78–82 (1995)

    CAS  Article  Google Scholar 

  26. 26

    Greenblum, S., Turnbaugh, P. J. & Borenstein, E. Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proc. Natl Acad. Sci. USA 109, 594–599 (2012)

    ADS  CAS  Article  Google Scholar 

  27. 27

    McArdle, B. H. & Anderson, M. J. Fitting multivariate models to community data: a comment on distance-based redundancy analysis. Ecology 82, 290–297 (2001)

    Article  Google Scholar 

  28. 28

    Yang, B. et al. Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers. BMC Bioinformatics 11 (suppl. 2). S5 (2010)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Krause, L. et al. Phylogenetic classification of short environmental DNA fragments. Nucleic Acids Res. 36, 2230–2239 (2008)

    CAS  Article  Google Scholar 

  30. 30

    Wang, T. et al. Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers. ISME J. 6, 320–329 (2012)

    CAS  Article  Google Scholar 

  31. 31

    Biagi, E. et al. Through ageing, and beyond: gut microbiota and inflammatory status in seniors and centenarians. PLoS ONE 5, e10667 (2010)

    ADS  Article  Google Scholar 

  32. 32

    Kashyap, P. & Farrugia, G. Oxidative stress: key player in gastrointestinal complications of diabetes. Neurogastroenterol. Motil. 23, 111–114 (2011)

    CAS  Article  Google Scholar 

  33. 33

    Lyssenko, V. et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N. Engl. J. Med. 359, 2220–2232 (2008)

    CAS  Article  Google Scholar 

  34. 34

    Godon, J. J., Zumstein, E., Dabert, P., Habouzit, F. & Moletta, R. Molecular microbial diversity of an anaerobic digestor as determined by small-subunit rDNA sequence analysis. Appl. Environ. Microbiol. 63, 2802–2813 (1997)

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35

    Li, S. et. al. Type 2 diabetes gut metagenome (microbiome) data from 368 Chinese samples. GigaScience (2012)

  36. 36

    Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011)

    ADS  CAS  Article  Google Scholar 

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We thank L. Goodman for editing the manuscript and providing comments. This research was supported by the Ministry of Science and Technology of China, 863 program (2012AA02A201), the National Natural Science Foundation of China (30890032, 30725008, 30811130531, 31161130357), the Shenzhen Municipal Government of China (ZYC200903240080A, BGI20100001, CXB201108250096A, CXB201108250098A), the Danish Strategic Research Council grant (2106-07-0021), the Ole Rømer grant from Danish Natural Science Research Council, the Solexa project (272-07-0196), and the European Commission FP7 grant HEALTH-F4-2007-201052. The Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention and Care (LuCamp, The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation ( We are also indebted to many additional faculty and staff of BGI-Shenzhen who contributed to this work.

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The project idea was conceived and the project was designed by Ju.W., K.K., O.P., R.N. and S.D.E.; J.Q., Y.L., Sh.L. and Ju.W. managed the project. F.Z., Z.C., R.X., Su.L., L.H., D.L., P.W., Y.D., X.S., Z.L., A.T., S.Z., M.W., Q.F. and T.H. performed sample collection and clinical study. Wen.Z., M.G., J.Y., Y.Z. and W.X. performed DNA experiments. Ju.W., K.K., O.P., R.N., S.D.E., J.Q., Y.L., Sh.L. and J.Z. designed the analysis. J.Q., Y.L., Sh.L., J.Z., Su.L., Y.G., Y.P., D.S., X.L., W.C., D.Z., Y.Q., M.Z., Z.Z., Z.J., G.S., J.L., J.R., S.O., H.C. and W.W. performed the data analysis. J.Q., Sh.L., J.Z., Y.G., Y.P., M.A., E.L., P.R., N.P. and J.-M.B. worked on metagenomic linkage group method. J.Q., D.S., Su.L., Y.Q., J.R., G.F. and S.O. did the functional annotation analyses. J.Q., Sh.L., D.S., J.Z., Y.P. and Y.L. wrote the paper. Ju.W., O.P., K.K., R.N., S.D.E., Ji.W., H.Y., So.L., Wei.Z. and R.Y. revised the paper.

Corresponding author

Correspondence to Jun Wang.

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The authors declare no competing financial interests.

Supplementary information

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This file contains Supplementary Methods, Supplementary Figures 1-15 and additional references. (PDF 3495 kb)

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Qin, J., Li, Y., Cai, Z. et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012).

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