Evidence map›Paper›PMID 30667580›Full record

ArticleMolecular nutrition & food research2019

Green Tea Polyphenols Modify the Gut Microbiome in db/db Mice as Co-Abundance Groups Correlating with the Blood Glucose Lowering Effect.

Tingting Chen, Anna B Liu, Shili Sun, Nadim J Ajami, Matthew C Ross, Hong Wang, Le Zhang, Kenneth Reuhl, Koichi Kobayashi, Janet C Onishi and 2 more

Open access · greenAbstract read
In one paragraph

Article in Molecular nutrition & food research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
5.1field-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

40 citing papers in PubMed, 99 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 1 country.

Tingting ChenDepartment of Chemical Biology, The State University of New Jersey, Piscataway, NJ, USA.
Anna B LiuDepartment of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Shili SunDepartment of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Nadim J AjamiThe Alkek Center for Metagenomics and Microbiome Research, Molecular Virology and Microbiology Department, Baylor College of Medicine, Houston, TX, USA.
Matthew C RossThe Alkek Center for Metagenomics and Microbiome Research, Molecular Virology and Microbiology Department, Baylor College of Medicine, Houston, TX, USA.
Hong WangDepartment of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Le ZhangDepartment of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Kenneth ReuhlDepartment of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, The State University of New Jersey, Piscataway, NJ, USA.
Koichi KobayashiDepartment of Microbial Pathogenesis & Immunology, Texas A&M Health Science Center, College Station, TX, USA.
Janet C OnishiDepartment of Chemical Biology, The State University of New Jersey, Piscataway, NJ, USA.
Liping ZhaoDepartment of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Chung S YangDepartment of Chemical Biology, The State University of New Jersey, Piscataway, NJ, USA.
Rutgers, The State University of New Jersey · USBaylor College of Medicine · USEnvironmental and Occupational Health Sciences Institute · USTexas A&M Health Science Center · US

Funding

Translational Research Support CoreP30ES005022 · NIEHS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI PANOS G. GEORGOPOULOS · 1988 to 2026
$47.4M
TARGETED GENOMICS FACILITY COREP30ES023512 · NIEHS · TEXAS A&M AGRILIFE RESEARCH · PI THREADGILL, DAVID W. · 2014 to 2017
$3.3M
NIEHS NIH HHS P30 ES005022NIEHS NIH HHS P30 ES023512
6 · The paper itself

Abstract

scopeThe effects of green tea polyphenols, Polyphenon E (PPE), and black tea polyphenols, theaflavins (TFs), on gut microbiota and development of diabetes in db/db mice are investigated and compared. METHODS AND

resultsSupplementation of PPE (0.1%) in the diet of female db/db mice for 7 weeks decreases fasting blood glucose levels and mesenteric fat while increasing the serum level of insulin, possibly through protection against β-cell damage. However, TFs are less or not effective. Microbiome analysis through 16S rRNA gene sequencing shows that PPE and TFs treatments significantly alter the bacterial community structure in the cecum and colon, but not in the ileum. The key bacterial phylotypes responding to the treatments are then clustered into 11 co-abundance groups (CAGs). CAGs 6 and 7, significantly increased by PPE but not by TFs, are negatively associated with blood glucose levels. The operational taxonomic units in these CAGs are from two different phyla, Firmicutes and Bacteroidetes. CAG 10, decreased by PPE and TFs, is positively associated with blood glucose levels.

conclusionGut microbiota respond to tea polyphenol treatments as CAGs instead of taxa. Some of the CAGs associated with the blood glucose lowering effect are enriched by PPE, but not TFs.

Indexed as

AnimalsBiflavonoidsBlood GlucoseBody WeightCatechinFemaleGastrointestinal MicrobiomeHypoglycemic AgentsInsulinInsulin-Secreting CellsMice, Mutant StrainsOrgan SizePolyphenolsRNA, Ribosomal, 16STeaBiflavonoidsBlood GlucoseCatechinHypoglycemic AgentsInsulinPolyphenolspolyphenon ERNA, Ribosomal, 16STeatheaflavindb/db micediabetesintestinal microbiotametabolismtea polyphenols

Identifiers

PMID30667580
PMCPMC6494111
OpenAlexW2913514700

What OpenQuestion holds

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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.