Cited by 1,921Diabetes and associated disordersGut microbiota and healthT-cell and B-cell Immunology

Innate immunity and intestinal microbiota in the development of Type 1 diabetes

Open access
Wen, Li, Ley, Ruth E., Volchkov, Pavel Yu., Stranges, Peter B., Avanesyan, Lia, Stonebraker, Austin C., Hu, Changyun, Wong, F. Susan +4 more·2008·Nature

Abstract

Type 1 diabetes (T1D) is a debilitating autoimmune disease that results from T-cell-mediated destruction of insulin-producing beta-cells. Its incidence has increased during the past several decades in developed countries, suggesting that changes in the environment (including the human microbial environment) may influence disease pathogenesis. The incidence of spontaneous T1D in non-obese diabetic (NOD) mice can be affected by the microbial environment in the animal housing facility or by exposure to microbial stimuli, such as injection with mycobacteria or various microbial products. Here we show that specific pathogen-free NOD mice lacking MyD88 protein (an adaptor for multiple innate immune receptors that recognize microbial stimuli) do not develop T1D. The effect is dependent on commensal microbes because germ-free MyD88-negative NOD mice develop robust diabetes, whereas colonization of these germ-free MyD88-negative NOD mice with a defined microbial consortium (representing bacterial phyla normally present in human gut) attenuates T1D. We also find that MyD88 deficiency changes the composition of the distal gut microbiota, and that exposure to the microbiota of specific pathogen-free MyD88-negative NOD donors attenuates T1D in germ-free NOD recipients. Together, these findings indicate that interaction of the intestinal microbes with the innate immune system is a critical epigenetic factor modifying T1D predisposition.

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/nature07336

Cites

39 of 39 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?

  • Mice deficient in MyD88 display an altered microbiota composition.

    “Mice deficient in MyD88 display an altered microbiota composition.56”
  • TLR5 is important in shaping the gut microbiota, which might be confined to a critical time window during neonatal life.

    “TLR5 is of particular importance in shaping the gut microbiota,53–56 which might be confined to a critical time window during neonatal life.40”
  • Germ-free non-obese diabetic mice lacking MyD88 signaling robustly develop type 1 diabetes.

    “GF non-obese diabetic mice lacking MyD88 signaling robustly develop T1D”
  • Microbial colonization of germ-free non-obese diabetic mice lacking MyD88 signaling attenuates type 1 diabetes.

    “while microbial colonization of these mice attenuates the disease.56”
  • Changes in the proportions of specific taxa of gut microbiota have been observed in various disease states including obesity, inflammatory bowel disease, type 1 and type 2 diabetes mellitus, biliary disease, and intestinal cancers.

    “Changes in the proportions of specific taxa of gut microbiota have been observed in various disease states, including obesity68,69, inflammatory bowel disease70, type 1 and type 2 diabetes mellitus71,72, biliary disease73, and intestinal cancers74,75 among many others.”

    From Dietary metabolism, the gut microbiome, and heart failure (2019) · cites this paper as [71]

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

Cited by

Sorted by citations

Authors
Wen, L., Ley, R. E., Volchkov, P. Y., Stranges, P. B., Avanesyan, L., Stonebraker, A. C., Hu, C., Wong, F. S., Szot, G. L., Bluestone, J. A., Gordon, J. I., & Chervonsky, A. V.
Affiliations
  • Washington University in St. Louis (US)
  • University of Chicago (US)
  • Jackson Laboratory (US)
  • Yale University (US)
  • University of Bristol (GB)
  • University of California, San Francisco (US)
Corresponding author
Chervonsky, Alexander V.
Venue
Nature
Published
2008-09-21
Volume
455
Issue
7216
Pages
1109-1113
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2148067809
Cited by
1,921
References
39
Citations by year
2026: 23 · 2025: 49 · 2024: 75 · 2023: 69 · 2022: 105 · 2021: 86 · 2020: 112 · 2019: 137 · 2018: 134 · 2017: 128 · 2016: 141 · 2015: 137 · 2014: 138 · 2013: 119 · 2012: 132
FWCI
62.63
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • Explore Bristol Research (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
  • Bristol Research (University of Bristol) (submittedVersion)
Funders
  • National Institute of Allergy and Infectious Diseases (R37AI046643)
  • National Institute of Diabetes and Digestive and Kidney Diseases (R37DK030292, DK-30292, DK 45735, DK063452, R21DK063452, DK 70977, DK42086, R01DK070977, P30DK063720, P30DK042086, P30DK056341, R01DK030292, P30DK045735)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
Keywords
type 1 diabetes, innate immunity, gut microbiota, MyD88, Toll-like receptors, NOD mice, germ-free mice, commensal bacteria, autoimmune disease susceptibility, microbial products, mycobacteria, disease prevention, beta cell destruction, host-microbe interactions
MeSH terms
Animals, Bacteria, Diabetes Mellitus, Type 1, Female, Immunity, Innate, Interferon-gamma, Intestines, Islets of Langerhans, Male, Molecular Sequence Data, Phylogeny, Specific Pathogen-Free Organisms, Time Factors, Mice, SCID, Mice, Inbred NOD, Mice, Knockout, CD8-Positive T-Lymphocytes, Mice, Myeloid Differentiation Factor 88

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