Evidence map›Paper›PMID 40597829›Full record

ArticleBMC nephrology2025

Bioinformatics and systems biology to identify underlying common pathogenesis of diabetic kidney disease and stenosis of arteriovenous fistula.

Mengru Fu, Fei Liu, Chengfa Ren, Qian Wu, Jun Xiao, Ying Wang, Yan Zeng, YuJuan Yang, Yan Yan

Abstract read
In one paragraph

Article in BMC nephrology, 2025. 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

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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

2 citing papers in PubMed.

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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

9 authors.

Mengru Fu *Department of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Fei Liu *Department of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Chengfa RenDepartment of Nephrology, Ganzhou People's Hospital Affiliated to Nanchang University, Ganzhou, Jiangxi, China.
Qian WuDepartment of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Jun XiaoDepartment of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Ying WangDepartment of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Yan ZengDepartment of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
YuJuan YangDepartment of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Yan YanDepartment of Nephrology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China. ndyfy01234@ncu.edu.cn.

Funding

National Natural Science Foundation of China 82360152
6 · The paper itself

Abstract

backgroundDiabetic nephropathy is an important cause of end-stage renal disease. Arteriovenous fistula (AVF) stenosis is closely associated with hyperglycemia. However, studies exploring biomarkers linking these two diseases are lacking, which may provide insight into the mechanisms underlying Diabetic kidney disease (DKD) comorbid AVF stenosis.

objectiveThis study investigated the common pathogenesis of DKD and AVF stenosis.

methodsBiomarkers were screened by identifying key genes common between DKD and AVF stenosis through differential gene analysis. GO, KEGG and GSEA enrichment analysis of DEGs were performed by cluster profiler. Immuno-infiltration analysis was performed by CIBERSORT. The predictive value of HPGD to distinguish DKD comorbid AVF stenosis was determined by ROC curves. Upstream miRNAs and transcription factors (TFs) of HPGD were predicted using hTFtarget and mirtarbase databases. After specifically knockdown six upstream miRNAs of HPGD in vascular smooth muscle cells (VSMCs), the expression levels of HPGD in each group were analyzed by quantitative reverse transcription PCR (qRT-PCR), and the empty vector was used as the control group. Clinical patient samples were collected to validate HPGD expression in DKD patients with AVF stenosis via qRT-PCR and immunofluorescence. Subsequently, the proliferation ability and the release level of inflammatory cytokines of VSMCs under high glucose culture conditions were evaluated by regulating the expression of HPGD.

resultsEleven shared DEGs were identified between DKD and AVF stenosis. Diagnostic efficacy of four hub genes (INHBA, PCK1, ALB, HPGD) was validated through receiver operating characteristic (ROC) curve analysis. qRT-PCR and immunofluorescence analyses showed that HPGD expression in the veins of patients with DKD combined with AVF stenosis was significantly decreased compared to the control group. Regulatory network analysis identified 691 TFs and 72 miRNAs modulating hub gene expression. Specific knockdown of six predicted upstream miRNAs of HPGD resulted in a significant increase in HPGD expression, with the hsa-miR-486-5p knockdown group showing the most pronounced effect. Overexpression of HPGD inhibited the proliferation of VSMCs and the release of inflammatory factors under high-glucose culture conditions. Significantly reduced infiltration of memory activated CD4 T cells was observed in AVF stenosis compared to normal veins. Pearson correlation analysis indicated that HPGD is positively correlated with resting mast cells, M1 macrophages, and M2 macrophages, while it is negatively correlated with naïve B cells and resting CD4 memory T cells.

conclusionHPGD may be a biomarker of DKD comorbid AVF stenosis. The targeted therapy of HPGD may prevent the occurrence of AVF stenosis in DKD patients, which is worthy of further study.

Indexed as

Arteriovenous FistulaBiomarkersDiabetic NephropathiesHydroxyprostaglandin DehydrogenasesComputational BiologyConstriction, PathologicGene Regulatory NetworksHumansMuscle, Smooth, VascularOligonucleotide Array Sequence AnalysisProtein Interaction MapsSystems Biology15-hydroxyprostaglandin dehydrogenaseBiomarkersHydroxyprostaglandin DehydrogenasesDiabetic kidney diseaseHPGDStenosis of arteriovenous fistula

Identifiers

PMID40597829
PMCPMC12211224

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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.