ArticleFrontiers in endocrinology2025
Bioinformatic analysis identifies LPL as a critical gene in diabetic kidney disease via lipoprotein metabolism.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- GPIHBP1 as a Biomarker of Diabetic Polyneuropathy and Vascular Complications in Type 2 Diabetes Mellitus.Biomolecules · 2026Observational
- Preterm Birth Increases Susceptibility to Hyperglycemia-Induced Kidney Injury With Sex-Specific Differences in Structural and Molecular Responses.Endocrinology, diabetes & metabolism · 2026Article
- Lifestyles, metabolome and diabetic kidney disease: a cohort study.QJM : monthly journal of the Association of Physicians · 2026Article
- Changes of retinal microvascular parameters in patients with type 2 diabetes mellitus with or without diabetic kidney disease.Frontiers in endocrinology · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic kidney disease (DKD) is a common and serious complication of diabetes, affecting approximately 40% of patients with the condition. The pathogenesis of DKD is complex, involving multiple processes such as metabolism, inflammation, and fibrosis. Given its increasing incidence and associated mortality, there is an urgent need to identify novel pathogenic genes and therapeutic targets. Methods: This study systematically identified hub DKD-associated genes and their potential molecular mechanisms through bioinformatic analysis. Gene expression datasets from DKD patients and healthy controls were obtained from the GEO database. Hub genes were screened using differential expression analysis, weighted gene co-expression network analysis (WGCNA), LASSO regression, random forest (RF) algorithms, and consensus clustering for DKD patient classification. Additionally, immune cell infiltration analysis was performed on differentially expressed genes to explore the relationship between hub genes and the immune microenvironment. Potential drugs targeting LPL were predicted based on gene-drug interaction analysis. Immunohistochemistry was used to verify the expression of LPL and TNF-α in kidney tissues from patients with varying degrees of DKD severity, as well as their relationship with kidney function impairment. Results: This study revealed that LPL, a lipoprotein metabolism gene, plays a crucial role in DKD, participating in cholesterol and glycerolipid metabolism as well as PPAR signaling. LPL expression was negatively correlated with pro-inflammatory M1 macrophages and various subsets of T cells, including naïve CD4 T cells and gamma delta T cells, while positively correlated with follicular helper T cells, suggesting its immune-regulation effects in DKD progression. Potential LPL-targeting drugs, such as Ibrolipim, anabolic steroid, and acarbose, might mitigate DKD. LPL expression was decreased with DKD severity and was correlated with TNF-α and kidney dysfunction markers, indicating its key role in DKD progression. Conclusion: LPL is a pivotal regulator of lipid metabolism and immune inflammation in DKD. Potential drugs targeting LPL offer new candidates for precision treatment of DKD. These findings lay a theoretical foundation for understanding the molecular mechanisms of DKD and developing LPL-based therapeutic strategies.
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