Evidence map›Paper›PMID 33990912›Full record

ArticleJournal of microbiology (Seoul, Korea)2021

Comparative analysis of type 2 diabetes-associated gut microbiota between Han and Mongolian people.

Shu-Chun Li, Yao Xiao, Ri-Tu Wu, Dan Xie, Huan-Hu Zhao, Gang-Yi Shen, En-Qi Wu

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of microbiology (Seoul, Korea), 2021. 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
1.3field-weighted citation impact, top 20% 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, 20 citations in OpenAlex.

  1. Pooled it
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  12. Effect of Benaglutide on Gut Microbiota and Fecal Metabolites in Patients with Type 2 Diabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023
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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

7 authors at 1 institution in 1 country.

Shu-Chun Li *School of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China.
Yao Xiao *School of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China.
Ri-Tu Wu *School of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China.
Dan XieSchool of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China.
Huan-Hu ZhaoSchool of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China.
Gang-Yi ShenSchool of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China. shengy@muc.edu.cn.
En-Qi WuSchool of Pharmacy, Minzu University of China, Key Laboratory of Ethnomedicine (Minzu University of China), Ministry of Education, Beijing, 100081, China. w1n2q3@163.com.
Minzu University of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the different rates of diabetes in different ethnic groups and the structural differences in intestinal microbiota, this study evaluated the changes in diabetes-related intestinal microbiota in two ethnic groups. Fifty-six stool samples were collected from subjects from the Han and Mongolian ethnic groups in China, including participants without diabetes (non-diabetic, ND) and with type 2 diabetes (T2D). The 16S rDNA gene V3 + V4 area was extracted from microbiota, amplified by PCR, and used to perform high-throughput sequencing and screen differential microbiota associated with ethnicity. The results showed that there were 44 T2D-related bacterial markers in the Han subjects, of which Flavonifractor, Alistipes, Prevotella, Oscillibacter, Clostridium XlVa, and Lachnospiracea_incertae_sedis were most closely related to diabetes. There were 20 T2D-related bacterial markers in the Mongolian subjects, of which Fastidiosipila and Barnesiella were most closely related to diabetes. The common markers of T2D bacteria in the two ethnic groups were Papillibacter and Bifidobacterium. There were 17 metabolic pathways with significant differences between the ND and T2D groups in the Han group, and 29 metabolic pathways in the Mongolian group. The glutamatergic metabolic pathway was the only common metabolic pathway in two ethnic groups. The composition and function of diabetes-related bacteria were significantly different among the different ethnic groups, which suggested that the influence of ethnic differences should be fully considered when studying the association between diabetes and bacteria. In addition, the common bacterial markers found in diabetic patients of different ethnic groups in this study can be used as potential targets to study the pathogenesis and treatment of diabetes.

Indexed as

Asian PeopleEthnicityGastrointestinal MicrobiomeAdultBacteriaBiomarkersChinaDiabetes Mellitus, Type 2FecesFemaleHigh-Throughput Nucleotide SequencingHumansMaleMetabolic Networks and PathwaysMiddle AgedRNA, Ribosomal, 16SBiomarkersRNA, Ribosomal, 16S16S rDNAdifferential microbiotaethnic groupHanMongoliantype 2 diabetes

Identifiers

PMID33990912
OpenAlexW3161344667

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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.