Evidence mapPaperPMID 42514233Full record

ReviewLife (Basel, Switzerland)2026

Biomarkers in Diabetic Kidney Disease: Early Detection, Prognostic Assessment, and Integration with Multi-Omics Signatures.

Merita Rroji, Flaviu Bob, Lorenzo Lo Cicero, Andreja Figurek, Goce Spasovski

Abstract readReview
In one paragraph

Review in Life (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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

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

5 authors.

Merita RrojiFaculty of Medicine, University of Medicine Tirana, 1001 Tirana, Albania.
Flaviu BobDepartment of Internal Medicine II-Nephrology, Victor Babes University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania.
Lorenzo Lo CiceroPhD Program in Molecular and Clinical Medicine, University of Palermo, 90100 Palermo, Italy.ORCID 0000-0002-9112-5540
Andreja FigurekDepartment of Nephrology and Transplantation Medicine, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland.ORCID 0000-0003-3766-0312
Goce SpasovskiDepartment of Nephrology, University Ss. Cyril and Methodius, 1000 Skopje, North Macedonia.ORCID 0000-0001-5628-2500

Funding

European Cooperation in Science and Technology CA21165
6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease and end-stage kidney disease worldwide, imposing a major clinical and economic burden. Conventional diagnostic markers, including albuminuria and estimated glomerular filtration rate (eGFR), have limited sensitivity and specificity for early disease detection and for accurately predicting progression. Increasing evidence suggests that DKD involves complex glomerular, tubular, inflammatory, fibrotic, and oxidative stress pathways that precede overt clinical manifestations. Consequently, considerable attention has focused on identifying novel noninvasive biomarkers, particularly urinary biomarkers, alongside selected circulating biomarkers and emerging multi-omics signatures. Proteins, peptides, extracellular vesicles, and RNA-based biomarkers have demonstrated promising diagnostic and prognostic potential for detecting early renal injury, improving risk stratification, and monitoring therapeutic response. This review summarizes recent advances in biomarker research for DKD, highlighting emerging molecular and omics-based signatures that may complement conventional markers in improving early detection, prognostic assessment, and disease phenotyping. While numerous biomarkers have shown promising associations with renal outcomes and disease progression, the majority remain investigational. Their translation into routine clinical practice will depend on rigorous external validation, standardized analytical methods, and demonstration of added value beyond established clinical measures.

Indexed as

biomarkersdiabetic kidney diseaseearly detectionprognosis

Identifiers

PMID42514233
PMCPMC13412889

What Socratic holds

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LicenceCC BY
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.