Evidence map›Paper›PMID 36368309›Full record

ArticleRenal failure2022

Extracellular vesicles metabolic changes reveals plasma signature in stage-dependent diabetic kidney disease.

Youjin Pan, Hui Yang, Tucan Chen, Jian Jin, Luya Ruan, Liang Hu, Li Chen

Open access · goldAbstract read
In one paragraph

Article in Renal failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 25% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Research progress on small extracellular vesicles in diabetic nephropathy.Frontiers in cell and developmental biology · 2025
    Review
  7. Review
  8. Article
  9. Article
  10. Review
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 3 institutions in 1 country.

Youjin PanDepartment of Endocrinology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Hui YangDepartment of Ophthalmology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Tucan ChenSchool of Ophthalmology & Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, China.
Jian JinDepartment of Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Luya RuanDepartment of Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Liang HuSchool of Ophthalmology & Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, China.
Li ChenDepartment of Endocrinology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Wenzhou Medical University · CNSecond Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University · CNShandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveEarly diagnosis of diabetic kidney disease (DKD) has long been a complex problem. This study aimed to analyze the metabolomic characteristics of plasma extracellular vesicles (EVs) at different stages of DKD in order to evaluate the metabolites of plasma EVs and select new biomarkers for the early diagnosis of DKD. PATIENTS AND

methodsA total of 78 plasma samples were collected, including samples from 20 healthy controls, 20 patients with type 2 diabetes mellitus (T2DM), 18 patients with DKD stage III, and 20 patients with DKD stage IV. In addition, EVs were isolated for metabolomics analysis.

resultsThe results identified differences in EV metabolomic characteristics in DKD patients at different stages, as well as significant differences in EV metabolomics between T2DM patients without DKD and patients with DKD. Ten Significantly differential metabolites were associated with the occurrence and progression of DKD. Uracil, LPC(O-18:1/0:0), sphingosine 1-phosphate, and 4-acetamidobutyric acid were identified as potential early biomarkers for DKD, showing excellent predictive performance.

conclusionUracil, LPC(O-18:1/0:0), sphingosine 1-phosphate, and 4-acetamidobutyric acid exhibited potential as suitable biomarkers for early DKD diagnosis. Unexpectedly, combining these four candidate metabolites resulted in enhanced predictive ability for DKD.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesExtracellular VesiclesBiomarkersHumansLysophospholipidsOxygen IsotopesSphingosineUracilBiomarkersLysophospholipidsOxygen-18Oxygen IsotopesSphingosinesphingosine 1-phosphateUracildiabetes mellitusdiabetic kidney diseaseexosomesExtracellular vesicle

Identifiers

PMID36368309
PMCPMC9662026
OpenAlexW4308917876

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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.