ArticleAnnals of translational medicine2020
Identification of hub genes in diabetic kidney disease via multiple-microarray analysis.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Transcriptomic Approach in Understanding Fabry Nephropathy: A Review of the Literature and Proof-of-Concept.Genes · 2025Pooled it
- Unveiling the molecular toxicity of plasticizers derived from microplastics (DMP and DEP) in diabetic kidney disease: integrative insights from network toxicology and multi-omics analysis.Frontiers in immunology · 2026Article
- Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients.Scientific reports · 2025Article
- Single-cell RNA sequencing in diabetic kidney disease: a literature review.Renal failure · 2024Review
- Single-cell transcriptomics and chromatin accessibility profiling elucidate the kidney-protective mechanism of mineralocorticoid receptor antagonists.The Journal of clinical investigation · 2024Article
- Mannose and glycine: Metabolites with potentially causal implications in chronic kidney disease pathogenesis.PloS one · 2024Article
- The role of intercellular communication in diabetic nephropathy.Frontiers in immunology · 2024Review
- Prediction of cellular targets in diabetic kidney diseases with single-cell transcriptomic analysis of db/db mouse kidneys.Journal of cell communication and signaling · 2023Article
- Regulon active landscape reveals cell development and functional state changes of human primary osteoblasts in vivo.Human genomics · 2023Article
- Bioinformatics analysis identifies diagnostic biomarkers and their correlation with immune infiltration in diabetic nephropathy.Annals of translational medicine · 2022Article
- Identification of ferroptosis-related genes as potential biomarkers of tongue squamous cell carcinoma using an integrated bioinformatics approach.FEBS open bio · 2022Article
- Integrated analysis of potential gene crosstalk between non-alcoholic fatty liver disease and diabetic nephropathy.Frontiers in endocrinology · 2022Article
- Identification of Type 2 Diabetes Based on a Ten-Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm.BioMed research international · 2022Article
- The role of CDH2 and MCP-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy.PloS one · 2022Article
- Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy.SAGE open medicine · 2022Article
- Studying Kidney Diseases at the Single-Cell Level.Kidney diseases (Basel, Switzerland) · 2021Review
- Comprehensive analysis of diabetic nephropathy expression profile based on weighted gene co-expression network analysis algorithm.BMC nephrology · 2021Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDiabetic kidney disease (DKD) is a leading cause of end-stage renal disease; however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics analysis has provided a comprehensive insight toward the molecular mechanisms of DKD. Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with DKD and contribute to a better understanding of DKD pathogenesis.
methodsThree datasets including GSE131882, GSE30122, and GSE30529 were utilized to find differentially expressed genes (DEGs). The potential functions of DEGs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein-protein interaction (PPI) network was constructed, and hub genes were selected with the top three molecular complex detection (MCODE) score. A correlation analysis between hub genes and clinical indicators was also performed.
resultsIn total, 84 upregulated DEGs and 49 downregulated DEGs were identified. Enriched pathways of the upregulated DEGs included extracellular matrix (ECM) receptor interaction, focal adhesion, human papillomavirus infection, malaria, and cell adhesion molecules. The downregulated DEGs were mainly enriched in ascorbate and aldarate metabolism, arginine and proline metabolism, endocrine- and other factor-regulated calcium reabsorption, mineral absorption and longevity regulating pathway, and multiple species signaling pathway. Seventeen hub genes were identified, and correlation analysis between unexplored hub genes and clinical features of DKD suggested that EGF, KNG1, GADD45B, and CDH2 might have reno-protective roles in DKD. Meanwhile, ATF3, B2M, VCAM1, CLDN4, SPP1, SOX9, JAG1, C3, and CD24 might promote the progression of DKD. Finally, most hub genes were found present in the immune cells of diabetic kidneys, which suggest the important role of inflammation infiltration in DKD pathogenesis.
conclusionsIn this study, we found seventeen hub genes using a scRNA-seq contained multiple-microarray analysis, which enriched the present understanding of molecular mechanisms underlying the pathogenesis of DKD in cells' level and provided candidate targets for diagnosis and treatment of DKD.
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