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

Abstract

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.

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Acknowledgements

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, http://www.lucamp.org). 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 (http://www.metabol.ku.dk). 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.

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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). https://doi.org/10.1038/nature11450

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