Evidence map›Paper›PMID 36774467›Full record

ArticleJournal of translational medicine2023

Alternation of the gut microbiota in irritable bowel syndrome: an integrated analysis based on multicenter amplicon sequencing data.

Han Chen, Rong Ou, Nana Tang, Wei Su, Ruoyun Yang, Xin Yu, Guoxin Zhang, Jianhua Jiao, Xiaoying Zhou

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.9field-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

26 citing papers in PubMed, 32 citations in OpenAlex.

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  16. Nutrients · 2024
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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

9 authors at 1 institution in 1 country.

Han Chen *Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
Rong Ou *Department of Gastroenterology and Hepatology, Jinhu County People's Hospital, Huaian, China.
Nana Tang *Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
Wei SuDepartment of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
Ruoyun YangDepartment of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
Xin YuDepartment of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
Guoxin ZhangDepartment of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
Jianhua JiaoDepartment of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China. jiaojh1968@aliyun.com.
Xiaoying ZhouDepartment of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China. zhouxiaoying0926@njmu.edu.cn.ORCID 0000-0002-6529-0243
Jiangsu Province Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGut dysbacteriosis has been reported as one of the etiologies for irritable bowel syndrome (IBS). However, the association between gut microbiota and IBS is still inconclusive.

methodA paired-sample study was designed by retrieving original multicenter 16 s-rRNA data of IBS patients and healthy controls from the GMrepo database. The propensity score matching (PSM) algorithm was applied to reduce confounding bias. The differential analysis of microbiota composition was performed at different taxonomic levels. The co-occurrence network was established. Subgroup analysis was performed to identify specific microbial compositions in different IBS subtypes.

resultsA total of 1522 amplicon samples were initially enrolled. After PSM, 708 individuals (354 IBS and 354 healthy controls) were eligible for further analysis. A total of 1,160 genera were identified. We identified significantly changed taxa in IBS groups (IBS-enriched: the families Enterobacteriaceae, Moraxellaceae and Sphingobacteriaceae; the genera Streptococcus, Bacillus, Enterocloster, Sphingobacterium, Holdemania and Acinetobacter. IBS-depleted: the phyla Firmicutes, Euryarchaeota, Cyanobacteria, Acidobacteria and Lentisphaerae; the families Bifidobacteriaceae, Ruminococcaceae, Methanobacteriaceae and the other 25 families; the genera Faecalibacterium, Bifidobacterium and other 68 genera). The co-occurrence network identified three hub genera and six hub species (including Faecalibacterium prausnitzii) that may be involved in IBS pathophysiology. Strong positive interactions were identified among the Bifidobacterium longum, Bifidobacterium breve and Bifidobacterium adolescentis in the Bifidobacterium community.

conclusionThis study provides quantitative analysis and visualization of the interaction between the gut microbiota and IBS. The identification of key species should be further validated to evaluate their causal relationships with the pathogenesis of IBS.

Indexed as

Gastrointestinal MicrobiomeIrritable Bowel SyndromeBacteriaFecesHumansRNA, Ribosomal, 16SRNA, Ribosomal, 16SAmplicon sequencing analysisGMrepo databaseGut microbiotaIrritable bowel syndromePropensity score matching

Identifiers

PMID36774467
PMCPMC9921069
OpenAlexW4320039706

What OpenQuestion holds

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LicenceCC BY
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.