ArticleJournal of inflammation research2023
Decoding the Intercellular Cross-Talking Between Immune Cells and Renal Innate Cells in Diabetic Kidney Disease by Bioinformatics.
Article in Journal of inflammation research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Integrated bioinformatics analysis uncovers TNFSF10 as a key panoptosis-related gene in diabetic tubular injury.Renal failure · 2026Article
- Myeloid myeloid PRDM16 restrains macrophage inflammatory remodeling and renal fibrosis in diabetic kidney disease by limiting PI3K/AKT activation.Acta diabetologica · 2026Article
- Single-cell RNA sequencing revealed the association between proximal tubular epithelial cells and renal interstitial cells in chronic kidney disease progression.Scientific reports · 2025Article
- Oxidative-Inflammatory Crosstalk and Multi-Target Natural Agents: Decoding Diabetic Vascular Complications.Current issues in molecular biology · 2025Review
- Identification of increased dedifferentiation along the Prom1+ cancer cells in Müllerian adenosarcoma with sarcomatous overgrowth.British journal of cancer · 2025Article
- Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025Review
- Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.Scientific reports · 2025Article
- IGF1R Promotes Th17/Treg Cell Development in Experimental Autoimmune Prostatitis.Journal of inflammation research · 2025Article
- Immune-mediated renal injury in diabetic kidney disease: from mechanisms to therapy.Frontiers in immunology · 2025Review
- Article
- Mitochondrial pyruvate carrier 2 mitigates acute kidney injury via sustaining mitochondrial metabolism.International journal of biological sciences · 2024Article
- Cellular cross-talk drives mesenchymal transdifferentiation in diabetic kidney disease.Frontiers in medicine · 2024Review
- The Role of Immune Cells in DKD: Mechanisms and Targeted Therapies.Journal of inflammation research · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: Diabetic kidney disease (DKD) continues to be devastating complication of diabetes mellitus. Immune response and inflammatory reaction play essential roles in the progression of DKD. But the specific mechanism of immune cells, and their act on renal innate cells remains unclear. This article focused on immune cells and their communication with renal innate cells to provide bioinformatic evidence for further understanding the immune mechanism in DKD. Methods: Data were analyzed to evaluate the differentially expressed genes (DEGs) and their pathways in DKD patients and mice. Gene set enrichment analysis (GSEA) was used to explore the immune inflammation-related pathways. CIBERSORT was applied to evaluate the distribution of inflammatory cells in different states. Cell-type DEGs and their enrichment pathways were further explored in podocytes, proximal tubule cells and injured tubule cells. Cellchat was used to reveal the cellular communication between immune cells and renal innate cells in DKD. Results: GO and KEGG analysis showed that DEGs were mainly enriched in immune inflammation-related pathways. Monocytes, M2 macrophages and T cells were significantly increased in DKD samples, especially in renal tubule. ScRNA datasets showed that the immune cells number in DKD were significantly increased. Cell-type DEGs were involved in kidney growth and development. In DKD, the interaction numbers and strength between immune cells and innate cells were significantly increased. VISTANT, SPP1 and IGF signal flow were increased in DKD. SPP1-CD44, NRG1-ERBB4, NAMPT-INSR, and Igf1-Igf1r receptor ligand pairs were enhanced in DKD, which mediated the communication between immune-inflammatory cells and innate cells. Conclusion: Our study explored the pathogenesis of renal injury promoted by immunoinflammatory in DKD. VISTANT, SPP1, and IGF signaling pathways and SPP1-CD44, NRG1-ERBB4, NAMPT-INSR, and Igf1- Igf1r receptor ligand pairs might occupy essential place in the occurrence and progress of DKD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.