Evidence map›Paper›PMID 41151540›Full record

ArticleDiabetes & metabolism journal2026

STING Promotes Renal Fibrosis in Diabetic Kidney Disease via ID1-Dependent Epithelial-Mesenchymal Transition.

Hongya Wang, Xiaobing Mao, Yuqing Huang, Xiaozhen Tan, Yuling Yang, Mengting Huang, Zongzhe Jiang, Yang Long, Xia Fang, Yong Xu

Abstract read
In one paragraph

Article in Diabetes & metabolism journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. S100A1 Promotes MDM2-Mediated KLF15 Ubiquitination to Regulate ID1-Driven Tubular Injury in Diabetic Kidney Disease.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
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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

10 authors.

Hongya Wang *Department of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Xiaobing Mao *Department of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yuqing Huang *Department of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Xiaozhen TanDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yuling YangDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Mengting HuangDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Zongzhe JiangDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yang LongDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Xia FangDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China. xiafang@swmu.edu.cn.
Yong XuDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, China. xywyll@swmu.edu.cn.

Funding

Luzhou Science and Technology Projects 2022-JYJ-162National Natural Science Foundation of China 82401001National Natural Science Foundation of China U22A20286Open Project Program of Metabolic Vascular Diseases Key Laboratory of Sichuan Province 2023MVDKL-G4Scientific research project of Southwest Medical University 2024LCYXZX02Sichuan Science and Technology Program 2022YFS0617Sichuan Science and Technology Program 2024NSFSC1616
6 · The paper itself

Abstract

backgruoundTubulointerstitial fibrosis (TIF) due to epithelial-mesenchymal transition (EMT) is an inseparable feature of diabetic renal fibrosis. Although stimulator of interferon genes (STING) has been shown to play a potential role in regulating EMT, whether and how it modulates EMT in diabetic kidney disease (DKD) mice remain unclear. Here, we investigated the role and underlying mechanisms of STING-mediated EMT in TIF in DKD.

methodsSTING expression was detected in human renal biopsy tissues and serum samples from patients with DKD. Mouse models with genetic STING deletion or pharmacological by a STING inhibitor (C176) were established to further investigate the functions of STING in vivo. The in vitro roles of STING were analyzed in human renal tubular epithelial (HK2) cells with STING overexpression or knockdown. RNA sequencing was used to explore the underlying mechanisms.

resultsSTING was upregulated in the kidneys and serum of patients with DKD and was negatively correlated with kidney function. STING deletion or pharmacological inhibition with C176 ameliorated pathological lesions, renal dysfunction and fibrosis in mouse models of DKD. STING deficiency alleviated renal fibrosis in DKD mice by inhibiting EMT. Mechanistically, RNA sequencing identified, inhibitor of differentiation 1 (ID1) as a downstream molecule of STING. Inhibition of ID1 in the setting of STING overexpression suppressed EMT and renal fibrosis.

conclusionOur study provides evidence that STING deficiency relieves renal fibrosis by inhibiting ID1-mediated EMT and that inhibition of STING and ID1 has therapeutic potential for patients with DKD.

Indexed as

Diabetic NephropathiesEpithelial-Mesenchymal TransitionInhibitor of Differentiation Protein 1KidneyMembrane ProteinsAnimalsDisease Models, AnimalFemaleFibrosisHumansMaleMiceMice, Inbred C57BLSTING ProteinInhibitor of Differentiation Protein 1Membrane ProteinsSTING1 protein, humanSting1 protein, mouseSTING ProteinDiabetic nephropathiesEpithelial-mesenchymal transitionFibrosisInhibitor of differentiation protein 1STING1 protein, human

Identifiers

PMID41151540
PMCPMC13366151

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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.