Evidence map›Paper›PMID 37925575›Full record

ArticleScientific reports2023

The urinary RNA atlas of patients with chronic kidney disease.

Li-Zhi Lv

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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

1 author at 1 institution in 1 country.

Li-Zhi LvDepartment of Nephrology, Jurong People Hospital, No. 66, Ersheng Road, Jurong, 212499, Jiangsu Province, China. 844713944@qq.com.
Zoucheng People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) represents a significant global health burden. Currently employed CKD biomarkers are influenced by various factors and lack accuracy in reflecting early-stage renal fibrosis severity. Consequently, there is an urgent need for the identification of early, noninvasive CKD biomarkers. Urine, easily collectible and kidney-derived, has demonstrated potential as a diagnostic source for various kidney diseases by leveraging its RNA content. To address this, we obtained RNA-seq data pertaining to urinary RNAs from both CKD patients and healthy controls via the Gene Expression Omnibus database (GEO). The DEseq2 software was utilized to identify differentially expressed RNAs (DE-RNAs). To evaluate the overall accuracy of these DE-RNAs in urine, we performed Receiver Operating Characteristic analysis (ROC). Selected urinary RNAs were subsequently validated using reverse-transcription quantitative real-time Polymerase Chain Reaction (qRT-PCR) in conjunction with ROC analysis. Computational and experimental analyses revealed significant increases in miR-542-5p, miR-33b-5p, miR-190a-3p, miR-507, and CSAG4 within the urine of CKD patients, exhibiting high AUC values. In conclusion, our findings suggest that urinary RNAs hold promise as diagnostic biomarkers for CKD.

Indexed as

MicroRNAsRenal Insufficiency, ChronicBiomarkersHumansKidneyROC CurveBiomarkersMicroRNAs

Identifiers

PMID37925575
PMCPMC10625525
OpenAlexW4388340682

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.