ArticleInflammation2024
Single-Cell Sequencing Reveals the Expression of Immune-Related Genes in Macrophages of Diabetic Kidney Disease.
Article in Inflammation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Integrated bioinformatics analysis uncovers TNFSF10 as a key panoptosis-related gene in diabetic tubular injury.Renal failure · 2026Article
- Fcer1g and St3gal1: Macrophage-associated angiogenesis biomarkers and therapeutic targets in sepsis-induced acute lung injury.PloS one · 2026Article
- Current trends in single-cell RNA sequencing applications in diabetes mellitus.FEBS open bio · 2025Review
- Targeting to Intensify M2 Macrophage Polarization Ameliorate Podocyte Lipid Accumulation and Damage by Tea Polyphenols via Activating SIRT1 in the Aged Model Rats With DKD.Food science & nutrition · 2025Article
- Unraveling diabetic kidney disease: insights from single-cell RNA sequencing.International urology and nephrology · 2025Review
- Macrophages in Focus: Key Drivers and Therapeutic Opportunities in Diabetic Kidney Disease.International journal of biological sciences · 2025Review
- Depletion of intrinsic renal macrophages with moderate-to-high expression ofTranslational andrology and urology · 2024Article
- Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease.International journal of molecular sciences · 2024Article
- The role of intercellular communication in diabetic nephropathy.Frontiers in immunology · 2024Review
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic kidney disease (DKD) is characterized by macrophage infiltration, which requires further investigation. This study aims to identify immune-related genes (IRGs) in macrophage and explore their potential as therapeutic targets. This study analyzed isolated glomerular cells from three diabetic mice and three control mice. A total of 59 glomeruli from normal kidney samples and 66 from DKD samples were acquired from four kidney transcriptomic profiling datasets. Bioinformatics analysis was conducted using both single-cell RNA (scRNA) and bulk RNA sequencing data to investigate inflammatory responses in DKD. Additionally, the "AUCell" function was used to investigate statistically different gene sets. The significance of each interaction pair was determined by assigning a probability using "CellChat." The study also analyzed the biological diagnostic importance of immune hub genes for DKD and validated the expression of these immune genes in mice models. The top 2000 highly variable genes (HVGs) were identified after data normalization. Subsequently, a total of eight clusters were identified. It is worth mentioning that macrophages showed the highest percentage increase among all cell types in the DKD group. Furthermore, the present study observed significant differences in gene sets related to inflammatory responses and complement pathways. The study also identified several receptor-ligand pairs and co-stimulatory interactions between endothelial cells and macrophages. Notably, SYK, ITGB2, FCER1G, and VAV1 were identified as immunological markers of DKD with promising predictive ability. This study identified distinct cell clusters and four marker genes. SYK, ITGB2, FCER1G, and VAV1 may be important roles. Consequently, the present study extends our understanding regarding IRGs in DKD and provides a foundation for future investigations into the underlying mechanisms.
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