Evidence map›Paper›PMID 28008148›Full record

ArticleOncotarget2017

Dysbiosis of urinary microbiota is positively correlated with type 2 diabetes mellitus.

Fengping Liu, Zongxin Ling, Yonghong Xiao, Longxian Lv, Qing Yang, Baohong Wang, Haifeng Lu, Li Zheng, Ping Jiang, Wei Wang and 1 more

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Strain-level differences inbioRxiv : the preprint server for biology · 2025
    Article
  6. The microbiota and renal cell carcinoma.Cellular oncology (Dordrecht, Netherlands) · 2024
    Review
  7. Article
  8. Health and Disease:Research (Washington, D.C.) · 2023
    Article
  9. Review
  10. Review
  11. Article
  12. Frontiers in gastroenterology (Lausanne, Switzerland) · 2022
    Review
  13. Article
  14. Article
  15. Observational
  16. Review
  17. Article
  18. Review
  19. Review
  20. Article
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.

Fengping LiuDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Zongxin LingState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Yonghong XiaoState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Longxian LvState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Qing YangCollaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Baohong WangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Haifeng LuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Li ZhengDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Ping JiangDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Wei WangDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Lanjuan LiState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) may be associated with altered urinary microbiota in female patients. We investigated alterations of urinary microbiota in Chinese female T2DM patients, and explored the associations between urinary microbiota and a patient's fasting blood glucose (FBG), urine glucose (UGLU), age, menstrual status, and body mass index (BMI). Midstream urine was collected from 70 female T2DM patients and 70 healthy females. Microbial diversity and composition were analyzed using the Illumina MiSeq sequencing platform by targeting the hypervariable V3-V4 regions of the 16S rRNA gene. We found that bacterial diversity was decreased in T2DM patients. Increased Actinobacteria phylum was positively correlated with FBG, UGLU, and BMI; Lactobacillus abundance decreased with age and menopause; and increased Lactobacillus correlated positively with FBG and UGLU. Decreased Akkermansia muciniphila was associated with FBG and UGLU. Escherichia coli abundance did not differ between the two cohorts. Carbohydrate and amino acid metabolism was reduced in T2DM patients, which were associated with bacterial richness indices such as Chao1 and ACE. Detailed microbiota analysis of well-characterized T2DM patients and healthy controls indicate that Chinese T2DM female patients exhibit dysbiosis of urinary microbiota.

Indexed as

AdultAgedAge DistributionBacteriaBody Mass IndexChinaDiabetes Mellitus, Type 2DysbiosisFemaleGlucoseHigh-Throughput Nucleotide SequencingHumansMenarcheMiddle AgedPhylogenyRNA, Ribosomal, 16SGlucoseRNA, Ribosomal, 16SAkkermansia muciniphilaEscherichia coliImmune responseImmunityImmunology and Microbiology Sectionlactobacillustype 2 diabetes mellitusurinary microbiota

Identifiers

PMID28008148
PMCPMC5354796

What OpenQuestion holds

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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.