Evidence map›Paper›PMID 40211272›Full record

ArticleJournal of translational medicine2025

Urobiome of patients with diabetic kidney disease in different stages is revealed by 2bRAD-M.

Nan Li, Ying Wang, Haojun Zhang, Liang Ma, Xinhui Huang, Yuhang Qiao, Han Li, Hailing Zhao, Ping Li

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

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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.

Nan LiBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Ying WangBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Haojun ZhangBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Liang MaBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Xinhui HuangBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Yuhang QiaoBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Han LiBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Hailing ZhaoBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China. zhly0167@163.com.
Ping LiBeijing Key Laboratory for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China. lp8675@163.com.

Funding

Elite Medical Professionals project of China-Japan Friendship Hospital ZRJY2024-GG11National High Level Hospital Clinical Research Funding 2023-NHLHCRFDJMS-05National Natural Science Foundation of China 82174144National Natural Science Foundation of China 82174296National Natural Science Foundation of China U23A20504The National Natural Science Foundation of China 82104601
6 · The paper itself

Abstract

backgroundKnowledge of the urinary microbiome (urobiome) in diabetic kidney disease (DKD) remains limited. The most commonly used 16S rRNA sequencing technique can only provide bacterial identification at the genus level. As a novel technique, 2bRAD sequencing for microbiome (2bRAD-M) can be used to identify the low-biomass microbiome at the species level. In this study, we used 2bRAD-M to compare the urobiome composition of patients with DKD at different stages with healthy individuals and those with type 2 diabetes mellitus (T2DM), with the expectation that we would find discriminative species correlated with DKD.

methodHealthy controls, patients with DKD with microalbuminuria (DKD1 group) or macroalbuminuria (DKD2 group), and patients with T2DM were recruited (n = 20 for each group). The first-morning urine was collected for 2bRAD-M testing. The albumin-to-creatinine ratio (ACR) was also measured with urine samples. Serum samples were collected for detecting clinical indicators. The microbial diversity and composition based on abundance were calculated. Differential bacteria for different groups were identified. Besides, the correlation between discriminative bacteria and clinical indices was also analyzed.

resultsUrobiome diversity was significantly reduced in the DKD groups. In the DKD1 group, was the dominant genus, followed by Pseudomonas_E, whereas in the DKD2 group, Pseudomonas_E became the dominant genus and Escherichia was notably reduced. Both Bifidobacterium and Streptococcus, which were the top genera in the control group, were substantially decreased in the DKD groups. The discriminative species for DKD1 included Escherichia coli and Acinetobacter johnsonii, while for DKD2, Pseudomonas_E oleovorans, Enterococcus faecalis, and Morganella morganii were identified. Pseudomonas_E, Enterococcus and Morganella showed a strong correlation with renal function indicators and urinary protein levels.

conclusionThe urobiome diversity and composition in patients with DKD were markedly different from those in healthy individuals and T2DM patients. These findings provide valuable insights into the onset and progression of DKD, driven by changes in the urinary bacterial community structure.

Indexed as

Diabetic NephropathiesMicrobiotaAgedBacteriaCase-Control StudiesDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedRNA, Ribosomal, 16SRNA, Ribosomal, 16S2bRAD-MDiabetic kidney diseaseType 2 diabetes mellitusUrinary microbiome

Identifiers

PMID40211272
PMCPMC11983741

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.