Evidence map›Paper›PMID 33469094›Full record

ArticleScientific reports2021

Multiple bacteria associated with the more dysbiotic genitourinary microbiomes in patients with type 2 diabetes mellitus.

Hua Zha, Fengping Liu, Zongxin Ling, Kevin Chang, Jiezuan Yang, Lanjuan Li

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. The gut microbiota in experimental abdominal aortic aneurysm.Frontiers in cardiovascular medicine · 2023
    Article
  3. Article
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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

6 authors at 3 institutions in 2 countries.

Hua Zha *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310000, China.
Fengping Liu *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310000, China.
Zongxin Ling *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310000, China.
Kevin ChangDepartment of Statistics, The University of Auckland, Auckland, New Zealand.
Jiezuan YangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310000, China.
Lanjuan LiState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310000, China. ljli@zju.edu.cn.
First Affiliated Hospital Zhejiang University · CNState Key Laboratory of Diagnosis and Treatment of Infectious DiseasesUniversity of Auckland · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) influences the human health and can cause significant illnesses. The genitourinary microbiome profiles in the T2DM patients remain poorly understood. In the current study, a series of bioinformatic and statistical analyses were carried out to determine the multiple bacteria associated with the more dysbiotic genitourinary microbiomes (i.e., those with lower dysbiosis ratio) in T2DM patients, which were sequenced by Illumina-based 16S rRNA gene amplicon sequencing. All the genitourinary microbiomes from 70 patients with T2DM were clustered into three clusters of microbiome profiles, i.e., Cluster_1_T2DM, Cluster_2_T2DM and Cluster_3_T2DM, with Cluster_3_T2DM at the most dysbiotic genitourinary microbial status. The three clustered T2DM microbiomes were determined with different levels of alpha diversity indices, and driven by distinct urinalysis variables. OTU12_Clostridiales and OTU28_Oscillospira were likely to drive the T2DM microbiomes to more dysbiotic status, while OTU34_Finegoldia could play a vital role in maintaining the least dysbiotic T2DM microbiome (i.e., Cluster_1_T2DM). The functional metabolites K08300_ribonuclease E, K01223_6-phospho-beta-glucosidase and K00029_malate dehydrogenase (oxaloacetate-decarboxylating) (NADP+) were most associated with Cluster_1_T2DM, Cluster_2_T2DM and Cluster_3_T2DM, respectively. The characteristics and multiple bacteria associated with the more dysbiotic genitourinary microbiomes in T2DM patients may help with the better diagnosis and management of genitourinary dysbiosis in T2DM patients.

Indexed as

DysbiosisMicrobiotaAdultAgedAged, 80 and overBacteriaCase-Control StudiesDiabetes Mellitus, Type 2FemaleHumansMiddle AgedUrogenital System

Identifiers

PMID33469094
PMCPMC7815922
OpenAlexW3122928942

What OpenQuestion holds

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LicenceCC BY
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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.