Evidence map›Paper›PMID 30337545›Full record

ArticleScientific reports2018

Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice.

Youjia Hu, Jian Peng, Fangyong Li, F Susan Wong, Li Wen

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  6. Review
  7. Article
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  10. Article
  11. The Impact of Intestinal Microorganisms and Their Metabolites on Type 1 Diabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022
    Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Inflammasomes and Type 1 Diabetes.Frontiers in immunology · 2021
    Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Youjia HuSection of Endocrinology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA.
Jian PengSection of Endocrinology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA.
Fangyong LiYale Center for Analytical Sciences, Yale University School of Public Health, New Haven, CT, 06510, USA.
F Susan WongDivision of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK. wongfs@cardiff.ac.uk.
Li WenSection of Endocrinology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA. li.wen@yale.edu.
Yale University · USCardiff University · GB

Funding

Yale Diabetes Research CenterP30DK045735 · NIDDK · YALE UNIVERSITY · PI Kevan C Herold, GERALD I SHULMAN · 1993 to 2026
$44.0M
Role of TLR9 in Beta Cell Function and DiabetesR01DK092882 · NIDDK · YALE UNIVERSITY · PI WEN, LI · 2012 to 2016
$1.8M
Dendritic cells in immuno-metabolic disorder in mouse and manR01DK100500 · NIDDK · YALE UNIVERSITY · PI WEN, LI · 2014 to 2017
$1.4M
Medical Research Council MR/K021141/1NIDDK NIH HHS P30 DK045735NIDDK NIH HHS R01 DK092882NIDDK NIH HHS R01 DK100500
6 · The paper itself

Abstract

Type 1 diabetes (T1D) is a progressive autoimmune disease in which the insulin-producing beta cells are destroyed by auto-reactive T cells. Recent studies suggest that microbiota are closely associated with disease development. We studied gut, oral and vaginal microbiota longitudinally in non-obese diabetic (NOD) mice. We showed that the composition of microbiota is very different at the different mucosal sites and between young and adult mice. Gut microbiota are more diverse than oral or vaginal microbiota and the changes were more evident in the mice before and after onset of diabetes. Using alpha-diversity, Gram-positive/Gram-negative ratio as well as the relative abundance of Bacteroidetes and Erysipelotrichaceae in the gut microbiota, at 8 weeks of age, we formulated a predictive algorithm for T1D development in a cohort of 63 female NOD mice. Using this algorithm, we obtained 80% accuracy of prediction of diabetes onset, in two independent experiments, totaling 29 mice, with Area Under the Curve of 0.776 by ROC analysis. Interestingly, we did not find differences in peripheral blood mononuclear cells of the mice at 8 weeks of age, regardless of later diabetes development. Our results suggest that the algorithm could potentially be used in early prediction of future T1D development.

Indexed as

AnimalsDiabetes Mellitus, ExperimentalDiabetes Mellitus, Type 1DNA, BacterialFecesFemaleGastrointestinal MicrobiomeMiceMice, Inbred NODMucous MembraneVaginaDNA, Bacterial

Identifiers

PMID30337545
PMCPMC6193974
OpenAlexW2895837914

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.