Evidence map›Paper›PMID 36760602›Full record

ReviewDiabetes, metabolic syndrome and obesity : targets and therapy2023

Molecular Pathways of Diabetic Kidney Disease Inferred from Proteomics.

Lan Wei, Yuanyuan Han, Chao Tu

Open access · goldAbstract readReview
In one paragraph

Review 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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. 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

3 authors at 2 institutions in 1 country.

Lan WeiDepartment of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, People's Republic of China.ORCID 0000-0003-0673-725X
Yuanyuan HanInstitute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan Key Laboratory of Vaccine Research and Development on Severe Infectious Diseases, Kunming, People's Republic of China.
Chao TuDepartment of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, People's Republic of China.ORCID 0000-0003-2142-8666
Soochow University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) affects an estimated 20-40% of type 2 diabetes patients and is among the most prevalent microvascular complications in this patient population, contributing to high morbidity and mortality rates. Currently, changes in albuminuria status are thought to be a primary indicator of the onset or progression of DKD, yet progressive nephropathy and renal impairment can occur in certain diabetic individuals who exhibit normal urinary albumin levels, emphasizing the lack of sensitivity and specificity associated with the use of albuminuria as a biomarker for detecting diabetic kidney disease and predicting DKD risk. According to the study, a non-invasive method for early detection or prediction of DKD may involve combining proteomic analytical techniques such second generation sequencing, mass spectrometry, two-dimensional gel electrophoresis, and other advanced system biology algorithms. Another category of proteins of relevance may now be provided by renal tissue biomarkers. The establishment of reliable proteomic biomarkers of DKD represents a novel approach to improving the diagnosis, prognostic evaluation, and treatment of affected patients. In the present review, a series of protein biomarkers that have been characterized to date are discussed, offering a theoretical foundation for future efforts to aid patients suffering from this debilitating microvascular complication.

Indexed as

diabetic kidney diseasediagnostic biomarkersproteomicstherapeutic targets

Identifiers

PMID36760602
PMCPMC9842482
OpenAlexW4316654344

What Socratic 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 Socratic graph.