ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2022
Comprehensive Diagnostics of Diabetic Nephropathy by Transcriptome RNA Sequencing.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 11 citations in OpenAlex.
- Reduced FGF9 Leads to Kidney Injury Through Regulating Renal Tubular Epithelial Cell EMT in Diabetes.Journal of cellular and molecular medicine · 2025Article
- Machine learning-based stratification of prediabetes and type 2 diabetes progression.Diabetology & metabolic syndrome · 2025Article
- Silencing LncRNA SNHG14 alleviates renal tubular injury via the miR-483-5p/HDAC4 axis in diabetic kidney disease.Hormones (Athens, Greece) · 2025Article
- AlteredExperimental biology and medicine (Maywood, N.J.) · 2025Article
- Depression of LncRNA DANCR alleviates tubular injury in diabetic nephropathy by regulating KLF5 through sponge miR-214-5p.BMC nephrology · 2024Article
- Comprehensive Analysis of Fatty Acid Metabolism in Diabetic Nephropathy from the Perspective of Immune Landscapes, Diagnosis and Precise Therapy.Journal of inflammation research · 2024Article
- Comprehensive machine learning models for predicting therapeutic targets in type 2 diabetes utilizing molecular and biochemical features in rats.Frontiers in endocrinology · 2024Article
- Bioinformatics-Based Analysis of Key Genes in Steroid-Induced Osteonecrosis of the Femoral Head That Are Associated with Copper Metabolism.Biomedicines · 2023Article
- Molecular Pathways of Diabetic Kidney Disease Inferred from Proteomics.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Review
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic nephropathy (DN) is a primary driver of end-stage renal disease. Given the heterogeneity of renal lesions and the complex mechanisms of DN, the present-day diagnostic approach remains highly controversial. We aimed to design a diagnostic model by bioinformatics methods for discriminating DN patients from normal subjects. Methods: In this study, transcriptome sequencing was performed on 6 clinical samples (3 from DN patients and 3 from healthy volunteers) from the Second Affiliated Hospital of Kunming Medical University. Construction of a competing endogenous RNA (ceRNA) network based on differentially expressed (DE)-mRNAs and -long noncoding RNAs (lncRNAs). Subsequently, the CytoHubba plugin was used to identify hub genes from DE-mRNAs in the ceRNA network and to perform functional enrichment analysis on them. The least absolute shrinkage and selection operator (LASSO) regression analysis was responsible for screening the diagnostic biomarkers from hub genes and assessing their diagnostic power using ROC curves. The pathways involved in hub genes were revealed by single-gene Gene Set Enrichment Analysis (GSEA). Moreover, we verified the expression levels of diagnostic biomarkers by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. Results: A total of 10 hub genes were screened from the ceRNA network, which appeared to be associated with the viral infection, kidney development, and regulation of immune and inflammatory responses. Subsequently, LASSO regression analysis established a diagnostic model consisting of Conclusion: We confirmed that differentially expressed hub genes may be novel diagnostic biomarkers in DN.
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