Cited by 131Gut microbiota and healthOral microbiology and periodontitis researchAdipokines, Inflammation, and Metabolic Diseases

The stool microbiota of insulin resistant women with recent gestational diabetes, a high risk group for type 2 diabetes

Open access
Fugmann, Marina, Breier, Michaela, Rottenkolber, Marietta, Banning, Friederike, Ferrari, Uta, Sacco, Vanessa, Grallert, Harald, Parhofer, Klaus G. +3 more·2015·Scientific Reports

Abstract

The gut microbiota has been linked to metabolic diseases. However, information on the microbiome of young adults at risk for type 2 diabetes (T2D) is lacking. The aim of this cross-sectional analysis was to investigate whether insulin resistant women with previous gestational diabetes (pGDM), a high risk group for T2D, differ in their stool microbiota from women after a normoglycemic pregnancy (controls). Bacterial communities were analyzed by high-throughput 16S rRNA gene sequencing using fecal samples from 42 pGDM and 35 control subjects 3–16 months after delivery. Clinical characterization included a 5-point OGTT, anthropometrics, clinical chemistry markers and a food frequency questionnaire. Women with a Prevotellaceae-dominated intestinal microbiome were overrepresented in the pGDM group (p < 0.0001). Additionally, the relative abundance of the phylum Firmicutes was significantly lower in women pGDM (median 48.5 vs. 56.8%; p = 0.013). Taxa richness (alpha diversity) was similar between the two groups and with correction for multiple testing we observed no significant differences on lower taxonomic levels. These results suggest that distinctive features of the intestinal microbiota are already present in young adults at risk for T2D and that further investigations of a potential pathophysiological role of gut bacteria in early T2D development are warranted.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/srep13212

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • A study of stool bacteria in women with a past case of GDM reported a lower proportion of the phylum Firmicutes and higher proportion of the family Prevotellaceae as compared with normoglycemic pregnancy.

    “Furthermore, a study of stool bacteria in women with a past case of GDM reported a lower proportion of the phylum Firmicutes and higher proportion of the family Prevotellaceae as compared with normoglycemic pregnancy [128].”

    From The Pathophysiology of Gestational Diabetes Mellitus (2018) · cites this paper as [128]

    The Results section reports significantly lower Firmicutes abundance in women post-GDM than in controls after a normoglycemic pregnancy. It also reports that a Prevotellaceae-rich subgroup was overrepresented among women post-GDM, but found no significant family-level difference between the two study groups after correction for multiple testing. Thus, the claim overstates the Prevotellaceae finding as a group-wide difference in proportion. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 30

  1. Musso G., Gambino R. & Cassader M. Interactions between gut microbiota and host metabolism predisposing to obesity and diabetes. Annual review of medicine 62, 361– 380, 10.1146/annurev-med-012510-175505 (2011). 21226616 · DOI · Paper page
  2. Vrieze A.. The environment within: how gut microbiota may influence metabolism and body composition. Diabetologia 53, 606– 613, 10.1007/s00125-010-1662-7 (2010). 20101384 PMC2830587 · DOI
  3. Delzenne N. M. & Cani P. D. Interaction between obesity and the gut microbiota: relevance in nutrition. Annual review of nutrition 31, 15– 31, 10.1146/annurev-nutr-072610-145146 (2011). 21568707 · DOI
  4. Turnbaugh P. J.. A core gut microbiome in obese and lean twins. Nature 457, 480– 484, 10.1038/nature07540 (2009). 19043404 PMC2677729 · DOI · Paper page
  5. Ley R. E., Turnbaugh P. J., Klein S. & Gordon J. I. Microbial ecology: human gut microbes associated with obesity. Nature 444, 1022– 1023, 10.1038/4441022a (2006). 17183309 · DOI · Paper page
  6. Verdam F. J.. Human intestinal microbiota composition is associated with local and systemic inflammation in obesity. Obesity 21, E607– 615, 10.1002/oby.20466 (2013). 23526699 · DOI · Paper page
  7. Duncan S. H.. Human colonic microbiota associated with diet, obesity and weight loss. International journal of obesity 32, 1720– 1724, 10.1038/ijo.2008.155 (2008). 18779823 · DOI · Paper page
  8. Fernandes J., Su W., Rahat-Rozenbloom S., Wolever T. M. & Comelli E. M. Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans. Nutrition & diabetes 4, e121, 10.1038/nutd.2014.23 (2014). 24979150 PMC4079931 · DOI · Paper page
  9. Larsen N.. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PloS one 5, e9085, 10.1371/journal.pone.0009085 (2010). 20140211 PMC2816710 · DOI · Paper page
  10. Qin J.. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55– 60, 10.1038/nature11450 (2012). 23023125 · DOI · Paper page
  11. Zhang X.. Human gut microbiota changes reveal the progression of glucose intolerance. PloS one 8, e71108, 10.1371/journal.pone.0071108 (2013). 24013136 PMC3754967 · DOI · Paper page
  12. Koren O.. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell 150, 470– 480, 10.1016/j.cell.2012.07.008 (2012). 22863002 PMC3505857 · DOI · Paper page
  13. Tura A.. Progression to type 2 diabetes in women with former gestational diabetes: time trajectories of metabolic parameters. PloS one 7, e50419, 10.1371/journal.pone.0050419 (2012). 23185618 PMC3503894 · DOI
  14. Rottenkolber M.. The diabetes risk phenotype of young women with recent gestational diabetes. The Journal of clinical endocrinology and metabolism jc20143898, 10.1210/jc.2014-3898 (2015). 25742512 · DOI
  15. Feig D. S., Zinman B., Wang X. & Hux J. E. Risk of development of diabetes mellitus after diagnosis of gestational diabetes. CMAJ: Canadian Medical Association journal = journal de l’Association medicale canadienne 179, 229– 234, 10.1503/cmaj.080012 (2008). PMC2474881 18663202 · DOI · Paper page
  16. Kroke A.. Validation of a self-administered food-frequency questionnaire administered in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study: comparison of energy, protein, and macronutrient intakes estimated with the doubly labeled water, urinary nitrogen, and repeated 24-h dietary recall methods. The American journal of clinical nutrition 70, 439– 447 (1999). 10500011
  17. Bergstrom A.. Establishment of intestinal microbiota during early life: a longitudinal, explorative study of a large cohort of Danish infants. Applied and environmental microbiology 80, 2889– 2900, 10.1128/AEM.00342-14 (2014). 24584251 PMC3993305 · DOI · Paper page
  18. Roager H. M., Licht T. R., Poulsen S. K., Larsen T. M. & Bahl M. I. Microbial enterotypes, inferred by the prevotella-to-bacteroides ratio, remained stable during a 6-month randomized controlled diet intervention with the new nordic diet. Applied and environmental microbiology 80, 1142– 1149, 10.1128/AEM.03549-13 (2014). 24296500 PMC3911217 · DOI · Paper page
  19. Mouzaki M.. Intestinal microbiota in patients with nonalcoholic fatty liver disease. Hepatology 58, 120– 127, 10.1002/hep.26319 (2013). 23401313 · DOI · Paper page
  20. Scher J. U.. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2, e01202, 10.7554/eLife.01202 (2013). 24192039 PMC3816614 · DOI · Paper page
  21. Matsuda M. & DeFronzo R. A. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes care 22, 1462– 1470 (1999). 10480510
  22. Caporaso J. G.. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. The ISME journal 6, 1621– 1624, 10.1038/ismej.2012.8 (2012). 22402401 PMC3400413 · DOI · Paper page
  23. Berry D., Ben Mahfoudh K., Wagner M. & Loy A. Barcoded primers used in multiplex amplicon pyrosequencing bias amplification. Applied and environmental microbiology 77, 7846– 7849, 10.1128/AEM.05220-11 (2011). 21890669 PMC3209180 · DOI
  24. Edgar R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460– 2461, 10.1093/bioinformatics/btq461 (2010). 20709691 · DOI
  25. Edgar R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature methods 10, 996– 998, 10.1038/nmeth.2604 (2013). 23955772 · DOI
  26. Edgar R. C., Haas B. J., Clemente J. C., Quince C. & Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194– 2200, 10.1093/bioinformatics/btr381 (2011). 21700674 PMC3150044 · DOI · Paper page
  27. Wang Q., Garrity G. M., Tiedje J. M. & Cole J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and environmental microbiology 73, 5261– 5267, 10.1128/AEM.00062-07 (2007). 17586664 PMC1950982 · DOI
  28. Kim O. S.. Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. International journal of systematic and evolutionary microbiology 62, 716– 721, 10.1099/ijs.0.038075-0 (2012). 22140171 · DOI
  29. Price M. N., Dehal P. S. & Arkin A. P. FastTree 2—approximately maximum-likelihood trees for large alignments. PloS one 5, e9490, 10.1371/journal.pone.0009490 (2010). 20224823 PMC2835736 · DOI · Paper page
  30. Chao A. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43, 783– 791 (1987). 3427163

Cited by

Sorted by citations

Authors
Fugmann, M., Breier, M., Rottenkolber, M., Banning, F., Ferrari, U., Sacco, V., Grallert, H., Parhofer, K. G., Seissler, J., Clavel, T., & Lechner, A.
Affiliations
  • Helmholtz Munich (DE)
  • Ludwig-Maximilians-Universität München (DE)
  • LMU Klinikum (DE)
  • Technical University of Munich (DE)
Corresponding author
Lechner, Andreas
Venue
Scientific Reports
Published
2015-08-17
Volume
5
Issue
1
Pages
13212-13212
ISSN
2045-2322 (ISSN-L)
OpenAlex
W2396020709
Cited by
131
References
12
Citations by year
2026: 2 · 2025: 9 · 2024: 12 · 2023: 13 · 2022: 18 · 2021: 23 · 2020: 12 · 2019: 13 · 2018: 11 · 2017: 13 · 2016: 5
FWCI
4.20
Type
journal article
Language
en
Open access
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion)
  • Site cant be reached (submittedVersion, cc-by)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
Funders
  • Ludwig-Maximilians-Universität München
  • Helmholtz Zentrum München
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
Keywords
gut microbiota, gestational diabetes mellitus, type 2 diabetes risk, insulin resistance, Prevotellaceae, Firmicutes, fecal microbiota, young women, postpartum women, alpha diversity, dysbiosis
MeSH terms
Bacillota, Firmicutes, Adult, Cross-Sectional Studies, Demography, Diabetes Mellitus, Type 2, Feces, Female, Glucose Tolerance Test, Humans, Insulin Resistance, Intestines, Pregnancy, Risk Factors, RNA, Ribosomal, 16S, Diabetes, Gestational, Sequence Analysis, DNA, Actinobacteria, Bacteroidetes, Young Adult, Microbiota

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review