Evidence map›Paper›PMID 40775242›Full record

ArticleScientific reports2025

Identification and experimental validation of mitochondrial and endoplasmic reticulum stress related gene in diabetic nephropathy.

Ting Li, Li Li, Zijuan Sun, Huijuan Zeng, Guoyong He, Zhong Tian, Dong Chen, Jun Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
4 · The record

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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

8 authors.

Ting LiDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China.
Li LiDepartment of Nephrology, Kunming First People's Hospital, Kunming, 650000, China.
Zijuan SunDepartment of Critical Care Medicine, The Third People's Hospital of Yunnan Province, Kunming, 650000, China.
Huijuan ZengDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China.
Guoyong HeDepartment of Nephrology, Kunming First People's Hospital, Kunming, 650000, China.
Zhong TianDepartment of Nephrology, Zhaotong First People's Hospital, Zhaotong, 657000, China.
Dong ChenSurgery, Yongping Town Central Health Center, Jinggu Dai and Yi Autonomous County, Pu'er City, 666401, China.
Jun LiDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China. lijun2@kmmu.edu.cn.

Funding

Postgraduate Innovation fund of Kunming Medical University 2022S221Scientific Research Fund of Education Department of Yunnan Province 2022J0269Scientific Research Fund project of Education Department of Yunnan Province 2025J0781the "Famous Doctors" special program for high-level talents in Yunnan Province RLMY20200022This study was supported by the National Teaching Quality Project 2022JXD209
6 · The paper itself

Abstract

Diabetic nephropathy (DN) is a kidney disease. Mitochondrial and endoplasmic reticulum stress (ERS) significantly contribute to diabetic nephropathy (DN), although the precise mechanisms involved have not yet been fully understood. The objective of this research was to explore the potential of mitochondrial and ERS genes as pivotal genetic elements in individuals with DN and to elucidate their fundamental molecular mechanisms. The datasets GSE30528 and GSE30122 were obtained from the Gene Expression Omnibus (GEO) database. Firstly, differentially expressed genes (DEGs) (DN and control samples) were identified by differential expression analysis. Candidate genes were obtained by intersecting the DEGs with mitochondria and endoplasmic reticulum stress-related genes. The key genes were identified through three machine learning methods, the receiver operating characteristic (ROC) curve analysis and expression validation. Subsequently, a nomogram model for DN was constructed. Moreover, gene set enrichment analysis (GSEA), immune infiltration, molecular regulatory networks of key genes were explored, Later, predicted their drugs. Finally, three key genes (GPX1, PPIF and VDAC1) were identified by expression validation and ROC validation and three key genes were all down-regulated in DN. Meanwhile, RT-qPCR analysis yielded the same results. In addition, the nomogram model of key genes was constructed, and the model had a good prediction effect. GSEA showed that the top 3 most prominent pathways shared by the 3 key genes included oxidative phosphorylation, glutathione metabolism, and ribosome. Immune cells, including gamma-delta T cells, activated mast cells, and M2 macrophages, exhibited differential infiltration between the DN group and the control group. A total of 23 lncRNAs targeting intersecting miRNAs of three key genes. There were 4 drugs associated with the three key genes. In this research, three key genes (GPX1, PPIF and VDAC1) mitochondrial and endoplasmic reticulum stress-related gene in DN were identified, providing a potential theoretical basis for DN treatment. However, this study still has certain limitations. This study only used a single dataset for analysis and validation, so the results of the study may not fully reflect the diversity of DN patients.

Indexed as

Diabetic NephropathiesEndoplasmic Reticulum StressMitochondriaDatabases, GeneticGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansROC CurveVoltage-Dependent Anion Channel 1Voltage-Dependent Anion Channel 1Diabetic nephropathyEndoplasmic reticulum stressKey genesMachine learningMitochondria

Identifiers

PMID40775242
PMCPMC12332012

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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.