Evidence map›Paper›PMID 39858440›Full record

ArticleBiomolecules2025

Urinary Proteomic Shifts over Time and Their Associations with eGFR Decline in Chronic Kidney Disease.

Zhalaliddin Makhammajanov, Kamila Nurlybayeva, Zikrillo Artikov, Pavel Tarlykov, Mohamad Aljofan, Rostislav Bukasov, Duman Turebekov, Syed Hani Abidi, Mehmet Kanbay, Abduzhappar Gaipov

Abstract read
In one paragraph

Article in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Zhalaliddin MakhammajanovDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana 010000, Kazakhstan.ORCID 0000-0002-0971-227X
Kamila NurlybayevaSchool of Medicine, Koc University, Istanbul 34450, Turkey.
Zikrillo ArtikovDepartment of Therapy, National Scientific Medical Center, Astana 010000, Kazakhstan.
Pavel TarlykovDepartment of Proteomics and Mass Spectroscopy, National Center for Biotechnology, Astana 010000, Kazakhstan.ORCID 0000-0003-2075-307X
Mohamad AljofanDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana 010000, Kazakhstan.
Rostislav BukasovDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, Astana 010000, Kazakhstan.ORCID 0000-0002-7060-1632
Duman TurebekovDepartment of Internal Medicine, Astana Medical University, Astana 010000, Kazakhstan.
Syed Hani AbidiDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana 010000, Kazakhstan.ORCID 0000-0001-9497-0902
Mehmet KanbayDivision of Nephrology, Department of Internal Medicine, Koc University, Istanbul 34450, Turkey.ORCID 0000-0002-1297-0675
Abduzhappar GaipovDepartment of Medicine, School of Medicine, Nazarbayev University, Astana 010000, Kazakhstan.ORCID 0000-0002-9844-8772

Funding

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

Abstract

Chronic kidney disease (CKD) is a progressive condition characterized by declining renal function, with limited biomarkers to predict its progression. The early identification of prognostic biomarkers is crucial for improving patient care and therapeutic strategies. This follow-up study investigated urinary proteomics and clinical outcomes in 18 CKD patients (stages 1-3) and 15 healthy controls using liquid chromatography-mass spectrometry and Mascot-SwissProt for protein identification. The exponentially modified protein abundance index (emPAI) was used for peptide quantification. Regression analyses were used to evaluate relationships between urinary proteins and the estimated glomerular filtration rate (eGFR), adjusting for proteinuria. At baseline, 171 proteins (median emPAI 86) were identified in CKD patients, and 271 were identified (median emPAI 47) in controls. At follow-up, 285 proteins (median emPAI 44.8) were identified in CKD patients, and 252 were identified (median emPAI 34.2) in controls. FBN1 was positively associated with eGFR, while FETUA showed a significant negative correlation at baseline. At follow-up, VTDB shifted from a negative baseline to a positive association with eGFR over time. CD44 and FBN1 shifted from a positive baseline to a negative association over time. These findings highlight VTDB, FBN1, and CD44 as potential prognostic biomarkers, providing insights into CKD progression and therapeutic targets.

Indexed as

Glomerular Filtration RateProteomeProteomicsRenal Insufficiency, ChronicAdipokinesAdultAgedBiomarkersDisease ProgressionErbB ReceptorsFemaleFibrillin-1HumansMaleMiddle AgedProteinuriaAdipokinesBiomarkersEGFR protein, humanErbB ReceptorsFBN1 protein, humanFibrillin-1ProteomebiomarkersCD44chronic kidney diseaseFBN1proteinuriaurinary proteomicsVTDB

Identifiers

PMID39858440
PMCPMC11762955

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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.