Evidence map›Paper›PMID 38162802›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023

Urinary PART1 and PLA2R1 Could Potentially Serve as Diagnostic Markers for Diabetic Kidney Disease Patients.

Qinglin Ye, Guiling Xu, Hao Yuan, Junhao Mi, Yuli Xie, Haoyu Li, Zhejun Li, Guanwen Huang, Xuesong Chen, Wei Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

11 authors at 1 institution in 2 countries.

Qinglin Ye *Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.
Guiling Xu *Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.ORCID 0009-0004-0148-9191
Hao YuanCentre for Genomic and Personalized Medicine, Guangxi key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021, People's Republic of China.
Junhao MiCentre for Genomic and Personalized Medicine, Guangxi key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021, People's Republic of China.
Yuli XieCentre for Genomic and Personalized Medicine, Guangxi key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021, People's Republic of China.
Haoyu LiDepartment of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.
Zhejun LiDepartment of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.
Guanwen HuangDepartment of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.
Xuesong ChenDepartment of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.ORCID 0009-0001-1185-8470
Wei LiDepartment of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, 530005, People's Republic of China.
Rirong YangCentre for Genomic and Personalized Medicine, Guangxi key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021, People's Republic of China.
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetic kidney disease (DKD) is a chronic renal disease which could eventually develop into renal failure. Though albuminuria and estimated glomerular filtration rate (eGFR) are helpful for the diagnosis of DKD, the lack of specific biomarkers reduces the efficiency of therapeutic interventions. Methods: Based on bulk-seq of 56 urine samples collected at different time points (including 11 acquired from DKD patients and 11 from healthy controls), in corporation of scRNA-seq data of urine samples and snRNA-seq data of renal punctures from DKD patients (retrieved from NCBI GEO Omnibus), urine-kidney specific genes were identified by Multiple Biological Information methods. Results: Forty urine-kidney specific genes/differentially expressed genes (DEGs) were identified to be highly related to kidney injury and proteinuria for the DKD patients. Most of these genes participate in regulating glucagon and apoptosis, among which, urinary PART1 (mainly derived from distal tubular cells) and PLA2R1 (podocyte cell surface marker) could be used together for the early diagnosis of DKD. Moreover, urinary PART1 was significantly associated with multiple clinical indicators, and remained stable over time in urine. Conclusion: Urinary PART1 and PLA2R1 could be shed lights on the discovery and development of non-invasive diagnostic method for DKD, especially in early stages.

Indexed as

biomarkerdiabetic kidney diseasediagnosisnon-invasiveurine

Identifiers

PMID38162802
PMCPMC10757812
OpenAlexW4390276466

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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 OpenQuestion graph.