Evidence map›Paper›PMID 38890379›Full record

ArticleScientific reports2024

Candidate protein biomarkers in chronic kidney disease: a proteomics study.

Zhalaliddin Makhammajanov, Assem Kabayeva, Dana Auganova, Pavel Tarlykov, Rostislav Bukasov, Duman Turebekov, Mehmet Kanbay, Miklos Z Molnar, Csaba P Kovesdy, Syed Hani Abidi and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Plasma Proteomic Profile of Dietary Potassium and Incident CKD.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Article
  6. New Insights into the Role of Mitochondrial Dysfunction in Diabetic Kidney Disease in the Omics Era.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
    Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. 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

11 authors.

Zhalaliddin MakhammajanovDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, Kazakhstan.
Assem KabayevaDepartment of Internal Medicine, Astana Medical University, Astana, Kazakhstan.
Dana AuganovaDepartment of Proteomics and Mass Spectroscopy, National Center for Biotechnology, Astana, Kazakhstan.
Pavel TarlykovDepartment of Proteomics and Mass Spectroscopy, National Center for Biotechnology, Astana, Kazakhstan.
Rostislav BukasovDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, Astana, Kazakhstan.
Duman TurebekovDepartment of Internal Medicine, Astana Medical University, Astana, Kazakhstan.
Mehmet KanbayDivision of Nephrology, Department of Internal Medicine, Koc University, Istanbul, Turkey.
Miklos Z MolnarDivision of Nephrology & Hypertension, Department of Internal Medicine, Spencer Fox Eccles School of Medicine at the University of Utah, Salt Lake City, UT, USA.
Csaba P KovesdyDivision of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA.
Syed Hani AbidiDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, Kazakhstan.
Abduzhappar GaipovDepartment of Medicine, School of Medicine, Nazarbayev University, Astana, Kazakhstan. abduzhappar.gaipov@nu.edu.kz.

Funding

Nazarbayev University Collaborative Research Program 211123CRP1603
6 · The paper itself

Abstract

Proteinuria poses a substantial risk for the progression of chronic kidney disease (CKD) and its related complications. Kidneys excrete hundreds of individual proteins, some with a potential impact on CKD progression or as a marker of the disease. However, the available data on specific urinary proteins and their relationship with CKD severity remain limited. Therefore, we aimed to investigate the urinary proteome and its association with kidney function in CKD patients and healthy controls. The proteomic analysis of urine samples showed CKD stage-specific differences in the number of detected proteins and the exponentially modified protein abundance index for total protein (p = 0.007). Notably, specific urinary proteins such as B2MG, FETUA, VTDB, and AMBP exhibited robust negative associations with kidney function in CKD patients compared to controls. Also, A1AG2, CD44, CD59, CERU, KNG1, LV39, OSTP, RNAS1, SH3L3, and UROM proteins showed positive associations with kidney function in the entire cohort, while LV39, A1BG, and CERU consistently displayed positive associations in patients compared to controls. This study suggests that specific urinary proteins, which were found to be negatively or positively associated with the kidney function of CKD patients, can serve as markers of dysfunctional or functional kidneys, respectively.

Indexed as

BiomarkersProteomicsRenal Insufficiency, ChronicAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedProteinuriaProteomeBiomarkersProteomeBiomarkersChronic kidney diseaseProteinuriaUrinary proteomics

Identifiers

PMID38890379
PMCPMC11189417

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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.