ArticleClinical kidney journal2021
The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasets.
Article in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 47 citations in OpenAlex.
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- RUNX3-activated apelin signaling inhibits cell proliferation and fibrosis in diabetic nephropathy by regulation of the SIRT1/FOXO pathway.Diabetology & metabolic syndrome · 2024Article
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- Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning.Frontiers in immunology · 2024Article
- Targeting ferroptosis: New perspectives of Chinese herbal medicine in the treatment of diabetes and its complications.Heliyon · 2023Review
- Title: Bioinformatic Identification of Genes Involved in Diabetic Nephropathy Fibrosis and their Clinical Relevance.Biochemical genetics · 2023Article
- Ferroptosis: new insight into the mechanisms of diabetic nephropathy and retinopathy.Frontiers in endocrinology · 2023Review
- Emerging Role of Ferroptosis in Diabetic Kidney Disease: Molecular Mechanisms and Therapeutic Opportunities.International journal of biological sciences · 2023Review
- Alterations in Protein Translation and Carboxylic Acid Catabolic Processes in Diabetic Kidney Disease.Cells · 2022Article
- Glutathione Peroxidase 4 Is a Predictor of Diabetic Kidney Disease Progression in Type 2 Diabetes Mellitus.Oxidative medicine and cellular longevity · 2022Article
- Anti-Diabesity Middle Eastern Medicinal Plants and Their Action Mechanisms.Evidence-based complementary and alternative medicine : eCAM · 2022Review
- Angiopoietin 2 as a Novel Potential Biomarker for Acute Aortic Dissection.Frontiers in cardiovascular medicine · 2021Article
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Authors and funding
16 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsDiabetic nephropathy (DN) is one of the main causes of end-stage kidney disease worldwide. Emerging studies have suggested that its pathogenesis is distinct from nondiabetic renal diseases in many aspects. However, it still lacks a comprehensive understanding of the unique molecular mechanism of DN.
methodsA total of 255 Affymetrix U133 microarray datasets (Affymetrix, Santa Calra, CA, USA) of human glomerular and tubulointerstitial tissues were collected. The 22 215 Affymetrix identifiers shared by the Human Genome U133 Plus 2.0 and U133A Array were extracted to facilitate dataset pooling. Next, a linear model was constructed and the empirical Bayes method was used to select the differentially expressed genes (DEGs) of each kidney disease. Based on these DEG sets, the unique DEGs of DN were identified and further analyzed using gene ontology and pathway enrichment analysis. Finally, the protein-protein interaction networks (PINs) were constructed and hub genes were selected to further refine the results.
resultsA total of 129 and 1251 unique DEGs were identified in the diabetic glomerulus (upregulated
conclusionsOur study not only reveals the unique molecular mechanism of DN but also provides a valuable resource for biomarker and therapeutic target discovery. Some of our findings are promising and should be explored in future work.
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