ArticleContributions to nephrology2011
Discovery of genes related to diabetic nephropathy in various animal models by current techniques.
Article in Contributions to nephrology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Identification of Key Genes Involved in Pancreatic Ductal Adenocarcinoma with Diabetes Mellitus Based on Gene Expression Profiling Analysis.Pathology oncology research : POR · 2021Pooled it
- Targeting METTL16 attenuates mesangial cell viability and fibrosis in a high-glucose state by suppressing m6A modification and the expression of RAP1B.BMC molecular and cell biology · 2025Article
- Efferocytosis: the art of cellular clearance and novel perspectives in disease therapy.Molecular cancer · 2025Review
- Contribution of TGF-β1 and Effects of Gene Silencer Pyrrole-Imidazole Polyamides Targeting TGF-β1 in Diabetic Nephropathy.Molecules (Basel, Switzerland) · 2020Article
- Dynamic Phenotypes and Molecular Mechanisms to Understand the Pathogenesis of Diabetic Nephropathy in Two Widely Used Animal Models of Type 2 Diabetes Mellitus.Frontiers in cell and developmental biology · 2020Article
- 2017 update on the relationship between diabetes and colorectal cancer: epidemiology, potential molecular mechanisms and therapeutic implications.Oncotarget · 2017Review
- New insight into the molecular drug target of diabetic nephropathy.International journal of endocrinology · 2014Review
- Transcriptomic analysis in diabetic nephropathy of streptozotocin-induced diabetic rats.International journal of molecular sciences · 2011Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
Abstract
One of the major problems facing clinical nephrology currently throughout the world is an exponential increase in patients with end-stage renal disease (ESRD), which is largely related to a high incidence of diabetic nephropathy. The latter is characterized by a multitude of metabolic and signaling events following excessive channeling of glucose, which leads to an increased synthesis of extracellular matrix (ECM) glycoproteins resulting in glomerulosclerosis, interstitial fibrosis and ultimately ESRD. With the incidence of nephropathy at pandemic levels and a high rate of ESRD, physicians around the world must treat a disproportionately large number of diabetic patients with upto-date innovative measures. In this regard, identification of genes that are crucially involved in the progression of diabetic nephropathy would enhance the discovery of new biomarkers and could also promote the development of novel therapeutic strategies. Over the last decade, we focused on the recent methodologies of high-throughput and genome-wide screening for identification of relevant genes in various animal models, which included the following: (1) single nucleotide polymorphism-based genome- wide screening; (2) the transcriptome approach, such as differential display reverse transcription polymerase chain reaction (DDRT-PCR), representational difference analysis of cDNA (cDNA-RDA)/suppressive subtractive hybridization, SAGE (serial analysis of gene expression) and DNA Microarray; and (3) the proteomic approach and 2- dimensional polyacrylamide gel electrophoresis (2D- PAGE) coupled with mass spectroscopic analysis. Several genes, such as Tim44 (translocase of inner mitochondrial membrane- 44), RSOR/MIOX (renal specific oxidoreductase/myo-inositol oxygenase), UbA52, Rap1b (Ras-related GTPase), gremlin, osteopontin, hydroxysteroid dehydrogenase- 3β isotype 4 and those of the Wnt signaling pathway, were identified as differentially expressed genes in kidneys of diabetic rodents. Functional analysis of these genes and the subsequent translational research in the clinical settings would be very valuable in the prevention and treatment of diabetic nephropathy. Future trends for identification of the biomarkers and therapeutic target genes should also include genome scale DNA/histonemethylation profiling, metabolomic approaches (e.g. metabolic phenotyping by 1H spectroscopy) and lectin microarray for glycan profiling along with the development of robust data-mining strategies.
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Registered trials
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