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pmid:40243723

PTEN: A Novel Diabetes Nephropathy Protective Gene Related to Cellular Senescence.

Kang Li · Huidi Tang · Xiaoqing Cao · Xiaoli Zhang · Xiaojie Wang

International journal of molecular sciences · 2025 doi:10.3390/ijms26073088

Paper

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Experiment

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Data

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title
PTEN: A Novel Diabetes Nephropathy Protective Gene Related to Cellular Senescence.
doi
10.3390/ijms26073088
pmid
40243723
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Kang Li
[1]
Huidi Tang
[2]
Xiaoqing Cao
[3]
Xiaoli Zhang
[4]
Xiaojie Wang
journal
International journal of molecular sciences
year
2025
abstract
Diabetic nephropathy (DN) is the leading cause of end-stage renal disease (ESRD). The current diagnostic and therapeutic approaches need to be improved. Cellular senescence has been implicated in the pathogenesis of DN, but its precise role remains unclear. This study aimed to identify key pathogenic genes related to cellular senescence in DN and explore their potential as diagnostic biomarkers. Using transcriptomic data from GEO datasets (GSE96804, GSE30122, GSE142025, and GSE104948) and cellular senescence-related genes sourced from the GenAge database, we integrated multiple bioinformatics approaches, including differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning and protein-protein interaction (PPI), to identify diagnostic genes. PTEN was identified as a key diagnostic gene. Immune infiltration analysis revealed that PTEN expression is positively correlated with macrophage M2 and dendritic cell resting infiltration and negatively correlated with monocytes and neutrophils. snRNA analysis revealed that PTEN is mainly expressed in mesangial cells. Finally, RT-PCR results revealed that the mRNA expression of PTEN was upregulated in kidneys from db/db mice. Additionally, high-glucose treatment significantly upregulated PTEN expression in cultured human mesangial cells. This study identifies PTEN as a potential diagnostic biomarker for DN which may contribute to early detection and personalized therapeutic strategies.
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The limma package (version 3.58.1) was used for differential analysis, defining genes with adjusted p value < 0.05 and |logFC| ≥ 0.5 as differentially expressed genes (DEGs), while the ggplot2 (version 3.5.1) and pheatmap packages (version 1.0.12) were used to generate volcano plots and heatmaps of DEGs, respectively.
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sections[18] "4.5. Identification of Differentially Expressed Genes and Functional Enrichment Analysis" paragraph 2
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The limma package (version 3.58.1) was used for differential analysis, defining genes with adjusted p value < 0.05 and |logFC| ≥ 0.5 as differentially expressed genes (DEGs), while the ggplot2 (version 3.5.1) and pheatmap packages (version 1.0.12) were used to generate volcano plots and heatmaps of DEGs, respectively.
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All data generated or analyzed in this study are included in the main text and the Supplementary Materials for this article. Other source data that support the findings of this study are available from the corresponding author upon reasonable request.
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PTEN was identified as a key diagnostic gene.
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title
Exon Level Expression Profiling of Diabetic Nephropathy
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2026-11-01T15:39:55Z
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The limma package (version 3.58.1) was used for differential analysis, defining genes with adjusted p value < 0.05 and |logFC| ≥ 0.5 as differentially expressed genes (DEGs), while the ggplot2 (version 3.5.1) and pheatmap packages (version 1.0.12) were used to generate volcano plots and heatmaps of DEGs, respectively.
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ir potential as diagnostic biomarkers. Using transcriptomic data from GEO datasets (GSE96804, GSE30122,
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significantly upregulated PTEN expression in cultured human mesangial cells. This study identifies
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The limma package (version 3.58.1) was used for differential analysis, defining genes with adjusted p value < 0.05 and |logFC| ≥ 0.5 as differentially expressed genes (DEGs), while the ggplot2 (version 3.5.1) and pheatmap packages (version 1.0.12) were used to generate volcano plots and heatmaps of DEGs, respectively.
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Cellular senescence has been implicated in the pathogenesis of DN, but its precise role remains unclear. This study aimed to identify key pathogenic genes related to cellular senescence in DN and explore their potential as diagnostic biomarkers. Using transcriptomic data from GEO datasets (GSE96804, GSE30122, GSE142025, and GSE104948) and cellular senescence-related genes sourced from the GenAge database, we integrated multiple bioinformatics approaches, including differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning and protein-protein interaction (PPI), to identify diagnostic genes. PTEN was identified as a key diagnostic gene. Immune infiltration analysis revealed that PTEN expression is positively correlated with macrophage M2 and dendritic cell resting infiltration and negatively correlated with monocytes and neutrophils. snRNA analysis revealed that PTEN is mainly expressed in mesangial cells. Finally, RT-PCR results revealed that the mRNA expression of PTEN was upregulated in kidneys from db/db mice. Additionally, high-glucose treatment significantly upregulated PTEN expression in cultured human mesangial cells. This study identifies PTEN as a potential diagnostic biomarker for DN which may contribute to early detection and personalized therapeutic strategies.", "claims": [{"id": "claim-method", "statement": "The limma package (version 3.58.1) was used for differential analysis, defining genes with adjusted p value < 0.05 and |logFC| ≥ 0.5 as differentially expressed genes (DEGs), while the ggplot2 (version 3.5.1) and pheatmap packages (version 1.0.12) were used to generate volcano plots and heatmaps of DEGs, respectively.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40243723", "locator": "sections[18] \"4.5. 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