Evidence map›Paper›PMID 36780038›Full record

ArticleInternational microbiology : the official journal of the Spanish Society for Microbiology2023

Variation of butyrate production in the gut microbiome in type 2 diabetes patients.

Julienne Siptroth, Olga Moskalenko, Carsten Krumbiegel, Jörg Ackermann, Ina Koch, Heike Pospisil

Open access · hybridAbstract read
In one paragraph

Article in International microbiology : the official journal of the Spanish Society for Microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
5.5field-weighted citation impact, top 4% 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

23 citing papers in PubMed, 36 citations in OpenAlex.

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  16. Characterising functional redundancy in microbiome communities via relative entropy.Computational and structural biotechnology journal · 2025
    Article
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  18. Beneficial Effects of ProbioticInternational journal of molecular sciences · 2024
    Article
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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

6 authors at 2 institutions in 1 country.

Julienne SiptrothHigh Performance Computing in Life Sciences, Technical University of Applied Sciences Wildau, Wildau, Germany. siptroth@th-wildau.de.
Olga MoskalenkoBIOMES NGS GmbH, Schwartzkopffstraße 1, 15745, Wildau, Germany.
Carsten KrumbiegelBIOMES NGS GmbH, Schwartzkopffstraße 1, 15745, Wildau, Germany.
Jörg AckermannDepartment of Molecular Bioinformatics, Institute of Computer Science, Goethe University Frankfurt, 60325, Frankfurt am Main, Germany.
Ina KochDepartment of Molecular Bioinformatics, Institute of Computer Science, Goethe University Frankfurt, 60325, Frankfurt am Main, Germany.
Heike PospisilHigh Performance Computing in Life Sciences, Technical University of Applied Sciences Wildau, Wildau, Germany.
Goethe University Frankfurt · DETechnical University of Applied Sciences Wildau · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetes mellitus type 2 is a common disease that poses a challenge to the healthcare system. The disease is very often diagnosed late. A better understanding of the relationship between the gut microbiome and type 2 diabetes can support early detection and form an approach for therapies. Microbiome analysis offers a potential opportunity to find markers for this disease. Next-generation sequencing methods can be used to identify the bacteria present in the stool sample and to generate a microbiome profile through an analysis pipeline. Statistical analysis, e.g., using Student's t-test, allows the identification of significant differences. The investigations are not only focused on single bacteria, but on the determination of a comprehensive profile. Also, the consideration of the functional microbiome is included in the analyses. The dataset is not from a clinical survey, but very extensive.

resultsBy examining 946 microbiome profiles of diabetes mellitus type 2 sufferers (272) and healthy control persons (674), a large number of significant genera (25) are revealed. It is possible to identify a large profile for type 2 diabetes disease. Furthermore, it is shown that the diversity of bacteria per taxonomic level in the group of persons with diabetes mellitus type 2 is significantly reduced compared to a healthy control group. In addition, six pathways are determined to be significant for type 2 diabetes describing the fermentation to butyrate. These parameters tend to have high potential for disease detection.

conclusionsWith this investigation of the gut microbiome of persons with diabetes type 2 disease, we present significant bacteria and pathways characteristic of this disease.

Indexed as

Diabetes Mellitus, Type 2Gastrointestinal MicrobiomeMicrobiotaBacteriaButyratesHumansButyratesButyrateGutNGSStatistical analysisType 2 diabetes

Identifiers

PMID36780038
PMCPMC10397123
OpenAlexW4320489621

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.