Evidence map›Paper›PMID 36209079›Full record

ArticleJournal of translational medicine2022

Pivotal interplays between fecal metabolome and gut microbiome reveal functional signatures in cerebral ischemic stroke.

Lanlan Zhao, Cheng Wang, Shanxin Peng, Xiaosong Zhu, Ziyi Zhang, Yanyan Zhao, Jinling Zhang, Guoping Zhao, Tao Zhang, Xueyuan Heng and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
3.0field-weighted citation impact, top 7% 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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 43 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Lanlan Zhao *Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China.
Cheng Wang *Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China.
Shanxin PengDepartment of Neurology, Lin Yi People's Hospital, Shandong University, Linyi, China.
Xiaosong ZhuDepartment of Neurology, Lin Yi People's Hospital, Shandong University, Linyi, China.
Ziyi ZhangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China.
Yanyan ZhaoDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China.
Jinling ZhangDepartment of Neurology, Lin Yi People's Hospital, Shandong University, Linyi, China.
Guoping ZhaoDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China.
Tao ZhangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China. taozhang@sdu.edu.cn.
Xueyuan HengDepartment of Neurology, Lin Yi People's Hospital, Shandong University, Linyi, China. xueyuanheng@yahoo.com.
Lei ZhangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250003, China. zhanglei7@sdu.edu.cn.ORCID 0000-0003-4284-2604
Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntegrative analysis approaches of metagenomics and metabolomics have been widely developed to understand the association between disease and the gut microbiome. However, the different profiling patterns of different metabolic samples in the association analysis make it a matter of concern which type of sample is the most closely associated with gut microbes and disease. To address this lack of knowledge, we investigated the association between the gut microbiome and metabolomic profiles of stool, urine, and plasma samples from ischemic stroke patients and healthy subjects.

methodsWe performed metagenomic sequencing (feces) and untargeted metabolomics analysis (feces, plasma, and urine) from ischemic stroke patients and healthy volunteers. Differential analyses were conducted to find key differential microbiota and metabolites for ischemic stroke. Meanwhile, Spearman's rank correlation and linear regression analyses were used to study the association between microbiota and metabolites of different metabolic mixtures.

resultsUntargeted metabolomics analysis shows that feces had the most abundant features and identified metabolites, followed by urine and plasma. Feces had the highest number of differential metabolites between ischemic stroke patients and the healthy group. Based on the association analysis between metagenomics and metabolomics of fecal, urine, and plasma, fecal metabolome showed the strongest association with the gut microbiome. There are 1073, 191, and 81 statistically significant pairs (P < 0.05) in the correlation analysis for fecal, urine, and plasma metabolome. Fecal metabolites explained the variance of alpha-diversity of the gut microbiome up to 31.1%, while urine and plasma metabolites only explained the variance of alpha-diversity up to 13.5% and 10.6%. Meanwhile, there were more significant differential metabolites in feces than urine and plasma associated with the stroke marker bacteria.

conclusionsThe systematic association analysis between gut microbiome and metabolomics reveals that fecal metabolites show the strongest association with the gut microbiome, followed by urine and plasma. The findings would promote the association study between the gut microbiome and fecal metabolome to explore key factors that are associated with diseases. We also provide a user-friendly web server and a R package to facilitate researchers to conduct the association analysis of gut microbiome and metabolomics.

Indexed as

Gastrointestinal MicrobiomeIschemic StrokeFecesHumansMetabolomeMetabolomicsRNA, Ribosomal, 16SRNA, Ribosomal, 16SGut microbiotaIntegrative analysisIschemic strokeMetabolomicsMicrobiome

Identifiers

PMID36209079
PMCPMC9548195
OpenAlexW4303672040

What OpenQuestion holds

Textmetadata
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.