Identification of key genes and immune infiltration of diabetic peripheral neuropathy in mice and humans based on bioinformatics analysis DOI Creative Commons
Yumin Zhang, Hui Zhou,

Juan Liu

et al.

Frontiers in Endocrinology, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 18, 2024

Background Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes, while the underlying molecular mechanisms are still unclear. The aim this study was to screen key genes and roles immune infiltration in DPN using bioinformatics analysis. Methods mice datasets including GSE222778, GSE11343, GSE70852, GSE27382, GSE34889 were retrieved from GEO database. Data human dbGaP. differentially expressed (DEGs) selected further analyzed by Gene Ontology, Kyoto Encyclopedia Genes Genomes enrichment analysis, Set Enrichment Analysis (GSEA) find shared pathway. Protein–protein interaction networks built mouse DEGs. hub verified vitro high- glucose-treated PC12 cells Schwann cells. single-sample GSEA (ssGSEA) algorithm used analyze proportions infiltrating subsequent correlations with genes. Results A total 323 DEGs 501 selected, they found significantly enriched immune-related biological functions pathways. 13 datasets, among them, there 7 genes, namely, PLAUR, S100A8, IL7R, CXCL13, SRPX2, CD300LB, CFI. expression Cfi, S100a8, Cxcl13, Cd300lb consistently confirmed . scores neutrophils NK CD56bright varied most cell analysis ( p < 0.01). Furthermore, be highly correlated infiltration. Conclusion Our indicated importance dysregulations identified several through combined samples, thus providing potential diagnostic therapeutic targets future.

Language: Английский

Cellular cross-talk drives mesenchymal transdifferentiation in diabetic kidney disease DOI Creative Commons

Arunita Chatterjee,

Jacqueline Tumarin,

Sharma Prabhakar

et al.

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 11

Published: Jan. 7, 2025

While changes in glomerular function and structure may herald diabetic kidney disease (DKD), many studies have underscored the significance of tubule-interstitial progression DKD. Indeed, fibrosis be most important determinant DKD as forms chronic glomerulopathies. The mechanisms underlying effects tubular on intrigued investigators, therefore, signaling cross-talk between cells been focus investigation recent studies. Additionally, observations slowing filtration rate (GFR) decline reduction proteinuria by drugs such SGLT-2 blockers, whose primary mechanism action is proximal tubules, further strengthen concept cells. Recently, research pathogenesis has primarily centered around exploring various pathways well endothelial podocytes with special relevance to epithelial-to-mesenchymal transition (EMT) endothelial-to-mesenchymal (EndoMT). this review provide a general description cell-to-cell highlight these concepts evidence relation physiology pathophysiology

Language: Английский

Citations

2
Unraveling Diabetic Kidney Disease: The Roles of Mitochondrial Dysfunction and Immunometabolism DOI Creative Commons
Phoom Narongkiatikhun, Ye Ji Choi,

Hailey Hampson

et al.

Kidney International Reports, Journal Year: 2024, Volume and Issue: 9(12), P. 3386 - 3402

Published: Oct. 4, 2024

Language: Английский

Citations

4
Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision DOI Creative Commons
Chun‐Po Steve Fan, Guanglin Yang, Cheng Li

et al.

Biology Direct, Journal Year: 2025, Volume and Issue: 20(1)

Published: Jan. 21, 2025

Diabetic nephropathy (DN) is a common diabetes-related complication with unclear underlying pathological mechanisms. Although recent studies have linked glycolysis to various states, its role in DN remains largely underexplored. In this study, the expression patterns of glycolysis-related genes (GRGs) were first analyzed using GSE30122, GSE30528, and GSE96804 datasets, followed by an evaluation immune landscape DN. An unsupervised consensus clustering samples from same dataset was conducted based on differentially expressed GRGs. The hub associated clusters identified via weighted gene co-expression network analysis (WGCNA) machine learning algorithms. Finally, these validated single-cell sequencing data quantitative real-time polymerase chain reaction (qRT-PCR). Eleven GRGs showed abnormal samples, leading identification two distinct clusters, each own profile functional pathways. GSE142153 that had specific characteristics. Furthermore, Extreme Gradient Boosting (XGB) model most effective diagnosing five significant variables, including GATM, PCBD1, F11, HRSP12, G6PC, as for further investigation. Single-cell predominantly proximal tubular epithelial cells. vitro experiments confirmed pattern NC. Our study provides valuable insights into molecular mechanisms DN, highlighting involvement cell infiltration.

Language: Английский

Citations

0
Personalized federated learning via decoupling self-knowledge distillation and global adaptive aggregation DOI

Zhiwei Tang,

Shuguang Xu, Haozhe Jin

et al.

Multimedia Systems, Journal Year: 2025, Volume and Issue: 31(2)

Published: Feb. 27, 2025

Language: Английский

Citations

0
Identification of key genes and immune infiltration of diabetic peripheral neuropathy in mice and humans based on bioinformatics analysis DOI Creative Commons
Yumin Zhang, Hui Zhou,

Juan Liu

et al.

Frontiers in Endocrinology, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 18, 2024

Background Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes, while the underlying molecular mechanisms are still unclear. The aim this study was to screen key genes and roles immune infiltration in DPN using bioinformatics analysis. Methods mice datasets including GSE222778, GSE11343, GSE70852, GSE27382, GSE34889 were retrieved from GEO database. Data human dbGaP. differentially expressed (DEGs) selected further analyzed by Gene Ontology, Kyoto Encyclopedia Genes Genomes enrichment analysis, Set Enrichment Analysis (GSEA) find shared pathway. Protein–protein interaction networks built mouse DEGs. hub verified vitro high- glucose-treated PC12 cells Schwann cells. single-sample GSEA (ssGSEA) algorithm used analyze proportions infiltrating subsequent correlations with genes. Results A total 323 DEGs 501 selected, they found significantly enriched immune-related biological functions pathways. 13 datasets, among them, there 7 genes, namely, PLAUR, S100A8, IL7R, CXCL13, SRPX2, CD300LB, CFI. expression Cfi, S100a8, Cxcl13, Cd300lb consistently confirmed . scores neutrophils NK CD56bright varied most cell analysis ( p < 0.01). Furthermore, be highly correlated infiltration. Conclusion Our indicated importance dysregulations identified several through combined samples, thus providing potential diagnostic therapeutic targets future.

Language: Английский

Citations

0