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A single-cell transcriptomic atlas characterizes the kidney in the diabetic kidney disease

GSE209781 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/01/07 Platform GPL24676
Summary
Diabetic kidney disease (DKD), a common and devastating microvascular complication of diabetes, is the leading cause of end-stage renal disease (ESRD). Since mechanisms of kidney injury in DKD were largely unknown, we performed single-cell RNA sequencing (scRNA-seq) on human kidneys collected from 3 DKD and 3 normal samples using 10×Genomics. In our study, a total of 51315 cells were enrolled for analyses and nine kidney cell types and seven immune cell types were identified. The cell-type-specific changes in gene expression and signaling pathways of podocyte, mesangial cells, endothelial cells, proximal tubule and macrophages indicate abnormal regulation associated with inflammation, apoptosis, oxidative stress, extracelluar matrix accumulation, and immune activation. In particular, we show that podocytes and renal tubular epithelial cells have a tremendous capacity to regenerate, which is involved in the repairment of injury. And extracellular vesicles, an important mediator of intercellular communication, might play a vital role for this progress. Besides, we identified new candidate transcription factors responsible for the progression of DKD. We also revealed a M1-M2 hybrid pattern, in which M1 and M2 are coupled activation in macrophages of DKD. Furthermore, we demonstrated a complex intercellular interaction between kidney cells and kidney cells or kidney cells and immune cells. Thus, our study will further the understanding of DKD pathogenesis and provide novel therapeutic targets for its treatment in the future.
Published in
TRAIL induces podocyte PANoptosis via death receptor 5 in diabetic kidney disease
Lv Z, Hu J, Su H et al. · Kidney international 2025 · PMID 39571905 · doi:10.1016/j.kint.2024.10.026
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Also filed as BioProject PRJNA862452 and SRA study SRP388199. Searching any of these in the dataset finder brings you back here.

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