Subjects

Abstract

Alterations in intestinal microbiota composition are associated with several chronic conditions, including obesity and inflammatory diseases. The microbiota of older people displays greater inter-individual variation than that of younger adults. Here we show that the faecal microbiota composition from 178 elderly subjects formed groups, correlating with residence location in the community, day-hospital, rehabilitation or in long-term residential care. However, clustering of subjects by diet separated them by the same residence location and microbiota groupings. The separation of microbiota composition significantly correlated with measures of frailty, co-morbidity, nutritional status, markers of inflammation and with metabolites in faecal water. The individual microbiota of people in long-stay care was significantly less diverse than that of community dwellers. Loss of community-associated microbiota correlated with increased frailty. Collectively, the data support a relationship between diet, microbiota and health status, and indicate a role for diet-driven microbiota alterations in varying rates of health decline upon ageing.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    & Gut microbiota: changes throughout the lifespan from infancy to elderly. Int. Dairy J. 20, 281–291 (2010)

  2. 2.

    et al. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc. Natl Acad. Sci. USA 104, 13780–13785 (2007)

  3. 3.

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

  4. 4.

    et al. The fecal microbiota of irritable bowel syndrome patients differs significantly from that of healthy subjects. Gastroenterology 133, 24–33 (2007)

  5. 5.

    et al. An irritable bowel syndrome subtype defined by species-specific alterations in faecal microbiota. Gut 61, 997–1006 (2012)

  6. 6.

    , , & Microbial ecology: human gut microbes associated with obesity. Nature 444, 1022–1023 (2006)

  7. 7.

    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)

  8. 8.

    et al. Composition, variability, and temporal stability of the intestinal microbiota of the elderly. Proc. Natl Acad. Sci. USA 108 (Suppl 1). 4586–4591 (2011)

  9. 9.

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

  10. 10.

    et al. Inflamm-aging: an evolutionary perspective on immunosenescence. Ann. NY Acad. Sci. 908, 244–254 (2000)

  11. 11.

    , & Homeostasis and inflammation in the intestine. Cell 140, 859–870 (2010)

  12. 12.

    , & The inflammatory status of old age can be nurtured from the intestinal environment. Curr. Opin. Clin. Nutr. Metab. Care 11, 13–20 (2008)

  13. 13.

    , , & Fecal microbiota composition and frailty. Appl. Environ. Microbiol. 71, 6438–6442 (2005)

  14. 14.

    Age related changes in gut physiology and nutritional status. Gut 38, 306–309 (1996)

  15. 15.

    et al. High-fat diet determines the composition of the murine gut microbiome independently of obesity. Gastroenterology 137, 1716–1724 (2009)

  16. 16.

    , , & Associations between dietary habits and body mass index with gut microbiota composition and fecal water genotoxicity: an observational study in African American and Caucasian American volunteers. Nutr. J. 8, 49 (2009)

  17. 17.

    et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332, 970–974 (2011)

  18. 18.

    et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl Acad. Sci. USA 107, 14691–14696 (2010)

  19. 19.

    et al. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci. Transl. Med. 1, 6ra14 (2009)

  20. 20.

    , , & Predicting a human gut microbiota’s response to diet in gnotobiotic mice. Science 333, 101–104 (2011)

  21. 21.

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

  22. 22.

    & UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)

  23. 23.

    , & A new index to measure healthy food diversity better reflects a healthy diet than traditional measures. J. Nutr. 137, 647–651 (2007)

  24. 24.

    et al. Metabolomics reveals metabolic biomarkers of Crohn’s disease. PLoS ONE 4, e6386 (2009)

  25. 25.

    , , , & The microbiology of butyrate formation in the human colon. FEMS Microbiol. Lett. 217, 133–139 (2002)

  26. 26.

    , , & How to measure comorbidity. a critical review of available methods. J. Clin. Epidemiol. 56, 221–229 (2003)

  27. 27.

    & Functional evaluation: the Barthel index. Md. State Med. J. 14, 61–65 (1965)

  28. 28.

    et al. The functional independence measure: a comparative validity and reliability study. Disabil. Rehabil. 17, 10–14 (1995)

  29. 29.

    , & “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 12, 189–198 (1975)

  30. 30.

    , , , & The mini nutritional assessment–its history, today’s practice, and future perspectives. Nutr. Clin. Pract. 23, 388–396 (2008)

  31. 31.

    et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing 39, 412–423 (2010)

  32. 32.

    , & Probabilistic principal component analysis for metabolomic data. BMC Bioinformatics 11, 571 (2010)

  33. 33.

    et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472, 57–63 (2011)

  34. 34.

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

  35. 35.

    . Population structure and ageing (2011)

  36. 36.

    & An Aging World: 2008 (US Government Printing Office, 2009)

  37. 37.

    , , , & Human nutrition, the gut microbiome and the immune system. Nature 474, 327–336 (2011)

  38. 38.

    et al. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. ISME J. 5, 220–230 (2011)

  39. 39.

    et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

  40. 40.

    , , & Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007)

  41. 41.

    , & Dietary intake patterns are reflected in metabolomic profiles: potential role in dietary assessment studies. Am. J. Clin. Nutr. 93, 314–321 (2011)

  42. 42.

    et al. Sociodemographic, health and lifestyle predictors of poor diets. Public Health Nutr. 14, 2166–2175 (2011)

  43. 43.

    & The composition of foods 6th edn (Royal Soc. Chemistry, 2002)

  44. 44.

    et al. Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine. PLoS ONE 4, e6669 (2009)

  45. 45.

    & Exploring prokaryotic taxonomy. Int. J. Syst. Evol. Microbiol. 54, 7–13 (2004)

  46. 46.

    et al. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26, 266–267 (2010)

  47. 47.

    , & FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010)

  48. 48.

    , & Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J. 4, 17–27 (2010)

  49. 49.

    , , & in ACM Conference on Bioinformatics Computational Biology and Biomedicine (Association for Computing Machinery, 2011)

  50. 50.

    et al. Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs. Genome Res. 14, 1147–1159 (2004)

  51. 51.

    , & MetaGene: prokaryotic gene finding from environmental genome shotgun sequences. Nucleic Acids Res. 34, 5623–5630 (2006)

  52. 52.

    & Regression quantiles. Econometrica 46, 33–50 (1978)

  53. 53.

    , & Wild bootstrap for quantile regression. Biometrika 98, 995–999 (2011)

  54. 54.

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

  55. 55.

    , & qvalue: Q-value estimation for false discovery rate control; R package version 1.24.20. (2010)

Download references

Acknowledgements

This work was supported by the Government of Ireland National Development Plan by way of a Department of Agriculture Food and Marine, and Health Research Board FHRI award to the ELDERMET project, as well as by a Science Foundation Ireland award to the Alimentary Pharmabiotic Centre. M.J.C. is funded by a fellowship from the Health Research Board of Ireland. We thank K. O’Donovan and P. Egan for clinical assistance, staff in Cork City and County hospitals for facilitating subject recruitment, S. Wong and B. Clayton for supercomputer access.

Author information

Author notes

    • Marcus J. Claesson
    •  & Ian B. Jeffery

    These authors contributed equally to this work.

Affiliations

  1. Department of Microbiology, University College Cork, Ireland

    • Marcus J. Claesson
    • , Ian B. Jeffery
    • , Susan E. Power
    • , Eibhlís M. O’Connor
    • , Siobhán Cusack
    • , Hugh M. B. Harris
    • , Gerald F. Fitzgerald
    • , Jennifer Deane
    • , Douwe van Sinderen
    • , Colin Hill
    •  & Paul W. O’Toole
  2. Alimentary Pharmabiotic Centre, University College Cork, Ireland

    • Marcus J. Claesson
    • , Ian B. Jeffery
    • , Eibhlís M. O’Connor
    • , Gerald F. Fitzgerald
    • , Douwe van Sinderen
    • , Catherine Stanton
    • , Fergus Shanahan
    • , Colin Hill
    • , R. Paul Ross
    •  & Paul W. O’Toole
  3. Department of Statistics, University College Cork, Ireland

    • Susana Conde
    •  & Anthony P. Fitzgerald
  4. Teagasc, Moorepark Food Research Centre, Moorepark, Fermoy, Co, Cork, Ireland

    • Mairead Coakley
    • , Bhuvaneswari Lakshminarayanan
    • , Orla O’Sullivan
    • , Catherine Stanton
    •  & R. Paul Ross
  5. Cork University Hospital, Wilton, Cork, Ireland

    • Michael O’Connor
    • , Norma Harnedy
    •  & Denis O’Mahony
  6. St. Finbarr’s Hospital, Douglas Road, Cork, Ireland

    • Michael O’Connor
    • , Norma Harnedy
    • , Kieran O’Connor
    •  & Denis O’Mahony
  7. Mercy University Hospital, Grenville Place, Cork, Ireland

    • Kieran O’Connor
  8. South Infirmary, Victoria University Hospital, Cork, Ireland

    • Kieran O’Connor
    •  & Denis O’Mahony
  9. Institute of Food and Health, University College Dublin, Ireland

    • Martina Wallace
    •  & Lorraine Brennan
  10. School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AT, UK

    • Julian R. Marchesi
  11. Department of Epidemiology and Public Health, University College Cork, Ireland

    • Anthony P. Fitzgerald
  12. Department of Medicine, University College Cork, Ireland

    • Fergus Shanahan

Authors

  1. Search for Marcus J. Claesson in:

  2. Search for Ian B. Jeffery in:

  3. Search for Susana Conde in:

  4. Search for Susan E. Power in:

  5. Search for Eibhlís M. O’Connor in:

  6. Search for Siobhán Cusack in:

  7. Search for Hugh M. B. Harris in:

  8. Search for Mairead Coakley in:

  9. Search for Bhuvaneswari Lakshminarayanan in:

  10. Search for Orla O’Sullivan in:

  11. Search for Gerald F. Fitzgerald in:

  12. Search for Jennifer Deane in:

  13. Search for Michael O’Connor in:

  14. Search for Norma Harnedy in:

  15. Search for Kieran O’Connor in:

  16. Search for Denis O’Mahony in:

  17. Search for Douwe van Sinderen in:

  18. Search for Martina Wallace in:

  19. Search for Lorraine Brennan in:

  20. Search for Catherine Stanton in:

  21. Search for Julian R. Marchesi in:

  22. Search for Anthony P. Fitzgerald in:

  23. Search for Fergus Shanahan in:

  24. Search for Colin Hill in:

  25. Search for R. Paul Ross in:

  26. Search for Paul W. O’Toole in:

Contributions

All authors are members of the ELDERMET consortium (http://eldermet.ucc.ie). P.W.O.T., E.M.O.C., S.Cu.1 and R.P.R. managed the project; D.v.S., G.F.F., C.S., J.R.M., F.S., C.H., R.P.R. and PWOT designed the analyses; M.J.C., I.B.J., S.Co.3, E.M.O.C., H.M.B.H., M.C., B.L., O.O.S., A.P.F., S.E.P., M.W. and L.B. performed the analyses; J.D. performed DNA extraction and PCR; M.W. and L.B. performed NMR metabolomics; M.O.C., N.H., K.O.C. and D.O.M. performed clinical analyses; M.J.C., I.B.J., S.Co.3, E.M.O.C., L.B., J.R.M., A.P.F., R.P.R., C.H., F.S. and P.W.O.T. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Paul W. O’Toole.

Amplicon sequence data, shotgun sequence data, contigs, genes and annotations have been deposited inMG-RAST under the Project ID 154 (http://metagenomics.anl.gov/linkin.cgi?project154).

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Figures 1–17, Supplementary Tables 1–6 and 8–9 (see separate fie for Supplementary Table 7), Supplementary Notes and Supplementary References.

Excel files

  1. 1.

    Supplementary Table 7

    This table contains the clinical and dietary metadata.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature11319

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.