1 World Health Organization. Obesity and overweight. Fact sheet no. 311; http://www.who.int/mediacentre/factsheets/fs311/en/ (2006)

2 Kelly, T., Yang, W., Chen, C. S., Reynolds, K. & He, J. Global burden of obesity in 2005 and projections to 2030. Int. J. Obes. 32, 1431–1437 (2008)

3 Stunkard, A. J., Harris, J. R., Pedersen, N. L. & McClearn, G. E. The body-mass index of twins who have been reared apart. N. Engl. J. Med. 322, 1483–1487 (1990)

4 Allison, D. B. et al. The heritability of body mass index among an international sample of monozygotic twins reared apart. Int. J. Obes. Relat. Metab. Disord. 20, 501–506 (1996)

5 Maes, H. H., Neale, M. C. & Eaves, L. J. Genetic and environmental factors in relative body weight and human adiposity. Behav. Genet. 27, 325–351 (1997)

6 Speliotes, E. K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature Genet. 42, 937–948 (2010)

7 Frayling, T. M. et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894 (2007)

8 Loos, R. J. et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nature Genet. 40, 768–775 (2008)

9 Willer, C. J. et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nature Genet. 41, 25–34 (2009)

10 Thorleifsson, G. et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nature Genet. 41, 18–24 (2009)

11 Heid, I. M. et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nature Genet. 42, 949–960 (2010)

12 Lindgren, C. M. et al. Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS Genet. 5, e1000508 (2009)

13 Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J. I. Microbial ecology: human gut microbes associated with obesity. Nature 444, 1022–1023 (2006)

14 Furet, J. P. et al. Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss: links with metabolic and low-grade inflammation markers. Diabetes 59, 3049–3057 (2010)

15 Duncan, S. H. et al. Human colonic microbiota associated with diet, obesity and weight loss. Int. J. Obes. 32, 1720–1724 (2008)

16 Schwiertz, A. et al. Microbiota and SCFA in lean and overweight healthy subjects. Obesity 18, 190–195 (2010)

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

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

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

20 Turnbaugh, P. J., Backhed, F., Fulton, L. & Gordon, J. I. Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome. Cell Host Microbe 3, 213–223 (2008)

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

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

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

24 Cotillard, A. et al. Dietary intervention impact on gut microbial gene richness. Nature http://dx.doi.org/10.1038/nature12480 (this issue)

25 Rajilić-Stojanovic, M. et al. Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults. Environ. Microbiol. 11, 1736–1751 (2009)

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

27 Lepage, P. et al. Twin study indicates loss of interaction between microbiota and mucosa of patients with ulcerative colitis. Gastroenterology 141, 227–236 (2011)

28 Claesson, M. J. et al. Gut microbiota composition correlates with diet and health in the elderly. Nature 488, 178–184 (2012)

29 Costello, E. K. et al. Bacterial community variation in human body habitats across space and time. Science 326, 1694–1697 (2009)

30 Cho, I. et al. Antibiotics in early life alter the murine colonic microbiome and adiposity. Nature 488, 621–626 (2012)

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

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

33 Sokol, H. et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc. Natl Acad. Sci. USA 105, 16731–16736 (2008)

34 Devillard, E., McIntosh, F. M., Duncan, S. H. & Wallace, R. J. Metabolism of linoleic acid by human gut bacteria: different routes for biosynthesis of conjugated linoleic acid. J. Bacteriol. 189, 2566–2570 (2007)

35 Png, C. W. et al. Mucolytic bacteria with increased prevalence in IBD mucosa augment in vitro utilization of mucin by other bacteria. Am. J. Gastroenterol. 105, 2420–2428 (2010)

36 Swidsinski, A., Weber, J., Loening-Baucke, V., Hale, L. P. & Lochs, H. Spatial organization and composition of the mucosal flora in patients with inflammatory bowel disease. J. Clin. Microbiol. 43, 3380–3389 (2005)

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

38 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)

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

40 Chevaleyre, Y., Koriche, F. & Zucker, J.-D. Rounding methods for discrete linear classification. Proc. 30th Int. Conf. Machine Learning (ICML-13) 651–659 (2013)

41 Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995)

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

43 Ouchi, N., Parker, J. L., Lugus, J. J. & Walsh, K. Adipokines in inflammation and metabolic disease. Nature Rev. Immunol. 11, 85–97 (2011)

44 Shoelson, S. E., Lee, J. & Goldfine, A. B. Inflammation and insulin resistance. J. Clin. Invest. 116, 1793–1801 (2006)

45 Backhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A. & Gordon, J. I. Host-bacterial mutualism in the human intestine. Science 307, 1915–1920 (2005)

46 Backhed, 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)

47 Mandard, S. et al. The fasting-induced adipose factor/angiopoietin-like protein 4 is physically associated with lipoproteins and governs plasma lipid levels and adiposity. J. Biol. Chem. 281, 934–944 (2006)

48 Membrez, M. et al. Gut microbiota modulation with norfloxacin and ampicillin enhances glucose tolerance in mice. FASEB J. 22, 2416–2426 (2008)

49 Ajslev, T. A., Andersen, C. S., Gamborg, M., Sorensen, T. I. & Jess, T. Childhood overweight after establishment of the gut microbiota: the role of delivery mode, pre-pregnancy weight and early administration of antibiotics. Int. J. Obes. 35, 522–529 (2011)

50 Sun, Y. et al. Advanced computational algorithms for microbial community analysis using massive 16S rRNA sequence data. Nucleic Acids Res. 38, e205 (2010)

51 Jørgensen, T. et al. A randomized non-pharmacological intervention study for prevention of ischaemic heart disease: baseline results Inter99. Eur. J. Cardiovasc. Prev. Rehabil. 10, 377–386 (2003)

52 World Health Organization. Preventing and managing the globalepidemic. Report of a WHO consultation. World Health Organ. Tech. Rep. Ser. 894, 1–253 (2000)

53 Treuth, M. S., Hunter, G. R. & Kekes-Szabo, T. Estimating intraabdominal adipose tissue in women by dual-energy X-ray absorptiometry. Am. J. Clin. Nutr. 62, 527–532 (1995)

54 Matthews, D. R. et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419 (1985)

55 Li, R. et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25, 1966–1967 (2009)

56 Jensen, L. J. et al. eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic Acids Res. 36, D250–D254 (2008)