Evidence map›Paper›PMID 30088332›Full record

ArticleMicrobiologyOpen2019

Altered gut microbiota and microbial biomarkers associated with chronic kidney disease.

Hengzhong Lun, Weihua Yang, Shuping Zhao, Meijie Jiang, Mingjie Xu, Fenfen Liu, Yunshan Wang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in MicrobiologyOpen, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 6 pooled it
5.7field-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

100 citing papers in PubMed, 6 syntheses or guidelines pooled it, 155 citations in OpenAlex.

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  11. Effect of Dietary Inulin Supplementation on the Gut Microbiota Composition and Derived Metabolites of Individuals Undergoing Hemodialysis: A Pilot Study.Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation · 2021
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  13. Supplementation withThe veterinary quarterly · 2026
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40 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Hengzhong LunMedical Research & Laboratory Diagnostic Center, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China.ORCID 0000-0001-5421-0378
Weihua YangMedical Research & Laboratory Diagnostic Center, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China.
Shuping ZhaoThe Department of Clinical Laboratory, Taian City Central Hospital, Taian, Shandong, China.
Meijie JiangThe Department of Clinical Laboratory, Taian City Central Hospital, Taian, Shandong, China.
Mingjie XuMedical Research & Laboratory Diagnostic Center, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China.
Fenfen LiuThe Department of Nephrology, Taian City Central Hospital, Taian, Shandong, China.
Yunshan WangMedical Research & Laboratory Diagnostic Center, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China.
Shandong University · CNTaian City Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to determine the differences in gut microbiota between patients with chronic kidney disease (CKD) and healthy controls (HC) and search for better microbial biomarkers associated with CKD. The 16S rRNA gene sequencing approach was used to investigate the differences in gut microbiota between the CKD and HC groups. The study found that 12 phylotypes were overrepresented in the CKD group and 19 in the HC group at the genus level. Furthermore, genera Lachnospira and Ruminococcus_gnavus performed the best in differentiating between HC and CKD populations. In addition, this novel study found that the genera Holdemanella, Megamonas, Prevotella 2, Dielma, and Scardovia were associated with the progression of CKD and hemodialysis. In conclusion, the composition of gut microbiota was different in CKD populations compared with healthy populations, and Lachnospira and R._gnavus were better microbial biomarkers. In addition, five phylotypes, including Holdemanella, Megamonas, Prevotella2, Dielma, and Scardovia, served as an indicator of the progression of CKD and hemodialysis. However, large-scale prospective studies should be performed to identify the reliability of the set of these phylotypes as biomarkers.

Indexed as

Gastrointestinal MicrobiomeAdultAgedBacteriaBiodiversityBiomarkersCase-Control StudiesFecesFemaleHumansMaleMiddle AgedRenal Insufficiency, ChronicBiomarkerschronic kidney diseasegut microbiotahemodialysisintestinal dysbiosismicrobial biomarker

Identifiers

PMID30088332
PMCPMC6460263
OpenAlexW2887566140

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.