Evidence map›Paper›PMID 41845912›Full record

SynthesisRenal failure2026

Exosomes in diabetic kidney disease: pathogenesis, biomarker discovery, and emerging therapeutics-a comprehensive systematic review.

Lin Ding, Zuolin Li, Yan Xia, Shan Liu, Mingxia Zhang, Lunzhi Liu

Abstract readSystematic Review
In one paragraph

Synthesis in Renal failure, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

6 authors.

Lin DingDepartment of Nephrology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.ORCID 0009-0000-6349-3461
Zuolin LiInstitute of Nephrology, Zhong Da Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
Yan XiaHubei Provincial Clinical Medical Research Center for Nephropathy, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.
Shan LiuDepartment of Nephrology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.
Mingxia ZhangDepartment of Nephrology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.
Lunzhi LiuDepartment of Nephrology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD), characterized by progressive renal dysfunction, is a prevalent microvascular complication of diabetes mellitus and a leading cause of end-stage renal disease worldwide. Despite advances in glycemic and blood pressure control, the incidence and prevalence of DKD continue to escalate, posing a growing public health challenge. Extracellular vesicles, particularly exosomes, are nanometer-sized vesicles secreted by diverse cells and have emerged as key regulators of intercellular communication. By transferring molecular cargo-including proteins, lipids, and nucleic acids-they exert pleiotropic effects on cellular homeostasis and participate in both physiological and pathological processes. Accumulating evidence has revealed dynamic alterations in the quantity and composition of urinary exosomes under diabetic conditions, implicating these vesicles in the multifactorial pathogenesis of DKD and highlighting their promise as liquid biopsy biomarkers for DKD. This review provides a comprehensive overview of the landscape of research on exosomes in DKD. We elucidate their roles in molecular pathology, investigate their potential for diagnostic and prognostic biomarker discovery powered by multi-omics and machine learning approaches, and examine their implications for therapeutic applications, including their use as drug delivery vehicles and direct therapeutic agents. Looking forward, we highlight critical research gaps and future directions, emphasizing the need for artificial intelligence (AI)-integrated multi-omics analyses to decipher exosome heterogeneity, large-scale multicenter trials to validate biomarker efficacy, and innovative strategies to overcome barriers in clinical translation, ultimately paving the way for personalized medicine in DKD management.

Indexed as

Diabetic NephropathiesExosomesBiomarkersHumansMultiomicsBiomarkersDiabetic kidney diseasedrug delivery systemsexosomesextracellular vesiclesmulti-omicsurinary biomarkers

Identifiers

PMID41845912
PMCPMC13003845

What OpenQuestion holds

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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.