Evidence map›Paper›PMID 37605183›Full record

ArticleBMC endocrine disorders2023

Exploring the gut microbiota in patients with pre-diabetes and treatment naïve diabetes type 2 - a pilot study.

Kristin Gravdal, Katrine H Kirste, Krzysztofa Grzelak, Graceline Tina Kirubakaran, Philippe Leissner, Adrien Saliou, Christina Casèn

Open access · goldAbstract read
In one paragraph

Article in BMC endocrine disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. UMI-guided single locus sequence typing method for phylotypingFrontiers in cellular and infection microbiology · 2026
    Article
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
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

7 authors at 2 institutions in 2 countries.

Kristin GravdalGenetic Analysis AS, Ulvenveien 80B, 0581, Oslo, Norway. kristin.gravdal@genetic-analysis.com.
Katrine H KirsteGenetic Analysis AS, Ulvenveien 80B, 0581, Oslo, Norway.
Krzysztofa GrzelakGenetic Analysis AS, Ulvenveien 80B, 0581, Oslo, Norway.
Graceline Tina KirubakaranGenetic Analysis AS, Ulvenveien 80B, 0581, Oslo, Norway.
Philippe LeissnerBIOASTER Microbiology Technology Institute, 40 Avenue Tony Garnier, 69007, Lyon, France.
Adrien SaliouBIOASTER Microbiology Technology Institute, 40 Avenue Tony Garnier, 69007, Lyon, France.
Christina CasènGenetic Analysis AS, Ulvenveien 80B, 0581, Oslo, Norway.
Genetic Analysis (Norway) · NOBIOASTER · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCompared to their healthy counterparts, patients with type 2 diabetes (T2D) can exhibit an altered gut microbiota composition, correlated with detrimental outcomes, including reduced insulin sensitivity, dyslipidemia, and increased markers of inflammation. However, a typical T2D microbiota profile is not established. The aim of this pilot study was to explore the gut microbiota and bacteria associated with prediabetes (pre-T2D) patients, and treatment naïve T2D patients, compared to healthy subjects.

methodsFecal samples were collected from patients and healthy subjects (from Norway). The bacterial genomic DNA was extracted, and the microbiota analyzed utilizing the bacterial 16S rRNA gene. To secure a broad coverage of potential T2D associated bacteria, two technologies were used: The GA-map® 131-plex, utilizing 131 DNA probes complementary to pre-selected bacterial targets (covering the 16S regions V3-V9), and the LUMI-Seq™ platform, a full-length 16S sequencing technology (V1-V9). Variations in the gut microbiota between groups were explored using multivariate methods, differential bacterial abundance was estimated, and microbiota signatures discriminating the groups were assessed using classification models.

resultsIn total, 24 pre-T2D patients, 18 T2D patients, and 52 healthy subjects were recruited. From the LUMI-Seq™ analysis, 10 and 9 bacterial taxa were differentially abundant between pre-T2D and healthy, and T2D and healthy, respectively. From the GA-map® 131-plex analysis, 10 bacterial markers were differentially abundant when comparing pre-T2D and healthy. Several of the bacteria were short-chain fatty acid (SCFA) producers or typical opportunistic bacteria. Bacteria with similar function or associated properties also contributed to the separation of pre-T2D and T2D from healthy as found by classification models. However, limited overlap was found for specific bacterial genera and species.

conclusionsThis pilot study revealed that differences in the abundance of SCFA producing bacteria, and an increase in typical opportunistic bacteria, may contribute to the variations in the microbiota separating the pre-T2D and T2D patients from healthy subjects. However, further efforts in investigating the relationship between gut microbiota, diabetes, and associated factors such as BMI, are needed for developing specific diabetes microbiota signatures.

Indexed as

Diabetes Mellitus, Type 2Gastrointestinal MicrobiomePrediabetic StateHumansPilot ProjectsRNA, Ribosomal, 16SRNA, Ribosomal, 16S16S rRNA bacterial geneBacterial profilingMicrobiota signaturesPrediabetesType 2 diabetes

Identifiers

PMID37605183
PMCPMC10440924
OpenAlexW4386030032

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.