PTEN: A Novel Diabetes Nephropathy Protective Gene Related to Cellular Senescence DOI Open Access
Kang Li,

Huidi Tang,

Xiaoqing Cao

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(7), P. 3088 - 3088

Published: March 27, 2025

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 pathogenesis DN, but its precise role remains unclear. This study aimed identify key pathogenic genes related cellular DN explore their potential as biomarkers. Using transcriptomic data from GEO datasets (GSE96804, GSE30122, GSE142025, GSE104948) senescence-related sourced GenAge database, we integrated multiple bioinformatics approaches, including differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning protein-protein interaction (PPI), genes. PTEN was identified a gene. Immune infiltration revealed that positively correlated with macrophage M2 dendritic cell resting negatively monocytes neutrophils. snRNA mainly expressed mesangial cells. Finally, RT-PCR results mRNA upregulated kidneys db/db mice. Additionally, high-glucose treatment significantly cultured human identifies biomarker for which may contribute early detection personalized strategies.

Language: Английский

PTEN: A Novel Diabetes Nephropathy Protective Gene Related to Cellular Senescence DOI Open Access
Kang Li,

Huidi Tang,

Xiaoqing Cao

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(7), P. 3088 - 3088

Published: March 27, 2025

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 pathogenesis DN, but its precise role remains unclear. This study aimed identify key pathogenic genes related cellular DN explore their potential as biomarkers. Using transcriptomic data from GEO datasets (GSE96804, GSE30122, GSE142025, GSE104948) senescence-related sourced GenAge database, we integrated multiple bioinformatics approaches, including differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning protein-protein interaction (PPI), genes. PTEN was identified a gene. Immune infiltration revealed that positively correlated with macrophage M2 dendritic cell resting negatively monocytes neutrophils. snRNA mainly expressed mesangial cells. Finally, RT-PCR results mRNA upregulated kidneys db/db mice. Additionally, high-glucose treatment significantly cultured human identifies biomarker for which may contribute early detection personalized strategies.

Language: Английский

Citations

0