Evidence map›Paper›PMID 32038574›Full record

ArticleFrontiers in microbiology2019

Integrated 16S rRNA Sequencing, Metagenomics, and Metabolomics to Characterize Gut Microbial Composition, Function, and Fecal Metabolic Phenotype in Non-obese Type 2 Diabetic Goto-Kakizaki Rats.

Weijun Peng, Jianhua Huang, Jingjing Yang, Zheyu Zhang, Rong Yu, Sharmeen Fayyaz, Shuihan Zhang, Yu-Hui Qin

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

52 citing papers in PubMed, 103 citations in OpenAlex.

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  6. Role of Gut Microbiota in Diabetic HFpEF: Mechanisms and Therapeutic Implications.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
    Review
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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

8 authors at 4 institutions in 2 countries.

Weijun PengDepartment of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Jianhua HuangHunan Academy of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Jingjing YangDepartment of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, China.
Zheyu ZhangDepartment of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
Rong YuHunan Key Laboratory of TCM Prescription and Syndromes Translational Medicine Hunan, Changsha, China.
Sharmeen FayyazH.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan.
Shuihan ZhangHunan Academy of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Yu-Hui QinHunan Academy of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Hunan University of Traditional Chinese Medicine · CNSecond Xiangya Hospital of Central South University · CNUniversity of Karachi · PKXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) is one of the most prevalent endocrine diseases in the world. Recent studies have shown that dysbiosis of the gut microbiota may be an important contributor to T2DM pathogenesis. However, the mechanisms underlying the roles of the gut microbiome and fecal metabolome in T2DM have not been characterized. Recently, the Goto-Kakizaki (GK) rat model of T2DM was developed to study the clinical symptoms and characteristics of human T2DM. To further characterize T2DM pathogenesis, we combined multi-omics techniques, including 16S rRNA gene sequencing, metagenomic sequencing, and metabolomics, to analyze gut microbial compositions and functions, and further characterize fecal metabolomic profiles in GK rats. Our results showed that gut microbial compositions were significantly altered in GK rats, as evidenced by reduced microbial diversity, altered microbial taxa distribution, and alterations in the interaction network of the gut microbiome. Functional analysis based on the cluster of orthologous groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations suggested that 5 functional COG categories belonged to the metabolism cluster and 33 KEGG pathways related to metabolic pathways were significantly enriched in GK rats. Metabolomics profiling identified 53 significantly differentially abundant metabolites in GK rats, including lipids and lipid-like molecules. These lipids were enriched in the glycerophospholipid metabolic pathway. Moreover, functional correlation analysis showed that some altered gut microbiota families, such as

Indexed as

fecal metabolomicsGK ratsglycerophospholipid metabolismgut microbiomeT2DMTenericutesVerrucomicrobia

Identifiers

PMID32038574
PMCPMC6984327
OpenAlexW3001183983

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.