Evidence map›Paper›PMID 40534883›Full record

ReviewFrontiers in immunology2025

Immune-mediated renal injury in diabetic kidney disease: from mechanisms to therapy.

Lingli Ma, Dianyuan Liu, Yue Yu, Zimeng Li, Qing Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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.

Lingli MaDepartment of Endocrinology and Metabolism, China-Japan Union Hospital of Jilin University, Changchun, China.
Dianyuan LiuDepartment of Endocrinology and Metabolism, China-Japan Union Hospital of Jilin University, Changchun, China.
Yue YuDepartment of Endocrinology and Metabolism, China-Japan Union Hospital of Jilin University, Changchun, China.
Zimeng LiDepartment of Endocrinology and Metabolism, China-Japan Union Hospital of Jilin University, Changchun, China.
Qing WangDepartment of Endocrinology and Metabolism, China-Japan Union Hospital of Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is now recognized as a multifactorial disorder, driven by the interplay of metabolic dysfunction, chronic inflammation, and immune-mediated renal injury. This review comprehensively synthesizes recent advancements in understanding immune dysregulation as a central driver of DKD pathogenesis, integrating molecular mechanisms with emerging therapeutic strategies. Innate immune activation, which includes macrophage polarization and adaptive immune perturbations, exacerbates glomerulosclerosis and interstitial fibrosis through cytokine storms and mitochondrial oxidative stress. Despite clinical guidelines emphasizing glycemic control and renin-angiotensin-aldosterone system (RAAS) inhibition, their limited efficacy in halting immune-mediated tubular atrophy highlights the unmet need for targeted immunotherapies. By connecting mechanistic discoveries to clinical translation, this work establishes a roadmap for the development of immune-centric therapies. Its critical synthesis of multi-omics data, clinical trial evidence, and preclinical models bridges the gap between laboratory discoveries and bedside applications, laying the groundwork for redefining DKD as a treatable immune-metabolic disorder.

Indexed as

Diabetic NephropathiesKidneyAnimalsHumansImmunity, InnateImmunotherapyRenin-Angiotensin Systemdiabetic kidney diseaseimmune cellimmunotherapymechanismstreatment methods

Identifiers

PMID40534883
PMCPMC12173918

What Socratic holds

Textmetadata
LicenceCC BY
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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.