ArticleFrontiers in public health2023
Common gene signatures and molecular mechanisms of diabetic nephropathy and metabolic syndrome.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Mosaic: Single-Cell Atlas of Stress.Cells · 2026Review
- A systematic benchmark of high-accuracy PacBio long-read RNA sequencing for transcript-level quantification.Genome biology · 2026Article
- Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy.Scientific reports · 2025Article
- Radiomics models to predict axillary lymph node metastasis in breast cancer and analysis of the biological significance of radiomic features.Frontiers in oncology · 2025Article
- The advance of single cell transcriptome to study kidney immune cells in diabetic kidney disease.BMC nephrology · 2024Review
- Type 2 diabetes mellitus and the risk of male infertility: a Mendelian randomization study.Frontiers in endocrinology · 2023Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. Multiple metabolic toxicities, redox stress, and endothelial dysfunction contribute to the development of diabetic glomerulosclerosis and DN. Metabolic syndrome (MetS) is a pathological state in which the body's ability to process carbohydrates, fats, and proteins is compromised because of metabolic disorders, resulting in redox stress and renal remodeling. However, a causal relationship between MetS and DN has not been proven. This study aimed to provide valuable information for the clinical diagnosis and treatment of MetS with DN. Methods: Here, transcriptome data of DN and MetS patients were obtained from the Gene Expression Omnibus database, and seven potential biomarkers were screened using bioinformatics analysis. In addition, the relationship between these marker genes and metabolism and immune infiltration was explored. Among the identified marker genes, the relationship between Results: We found that Conclusion: Overall, our findings can aid in further investigation of the effects of drug treatment on single cells of patients with diabetes to validate PLEKHA1 as a therapeutic target and to inform the development of targeted therapies.
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Registered trials
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