Evidence map›Paper›PMID 39215072›Full record

ArticleScientific reports2024

Characterization of gut microbiota in the Uyghur osteopenia population.

Kunchen Teng, Xin Li, Ting Huang, Shuang Zhang, Qiuxi Zhang, Namuna Rousitemu, Ting Lan, Youfeng Wen

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kunchen TengInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Xin LiInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Ting HuangInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Shuang ZhangInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Qiuxi ZhangInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Namuna RousitemuInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Ting LanInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China.
Youfeng WenInstitute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China. wenyf@jzmu.edu.cn.

Funding

National Natural Science Foundation of China No.32171151
6 · The paper itself

Abstract

The objectives of this study were to investigate the composition of gut microbiota and its relationship with bone loss in the Uyghur osteopenia population, identify potential disease-related taxa and collect information for the prevention and treatment of osteopenia in different people by regulating gut microbiota. We selected Uyghur residents, measured their heel BMD, collected faeces and general information, grouped them by BMD level, obtained faecal 16S rRNA sequences, and compared and analysed the differences between the groups. This study showed that the numbers of OTUs and species in the gut microbiota in the osteopenia group were higher than those in the control. At the phylum level, Erysipelotrichia was more abundant in the osteopenia group. At the genus level, Phascolarctobacterium was less abundant, and Ruminiclostridium_5 was more abundant in the osteopenia group compared to the control. Phascolarctobacterium and Z-score were positively correlated, and Ruminiclostridium_5 was negatively correlated with T and Z score. The different composition of the gut microbiota in Uyghur osteopenia patients and controls found in this study fills a knowledge gap in this ethnic group. The relationship between Uyghur osteopenia and BMD-associated bacterial genera deserves further exploration.

Indexed as

Bone Diseases, MetabolicCentral Asian PeopleGastrointestinal MicrobiomeBacteriaBiodiversityCase-Control StudiesFecesFemaleHumansMaleMiddle AgedPhylogenyBone mineral densityGut microbiotaOsteopeniaUyghur

Identifiers

PMID39215072
PMCPMC11364662

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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.